From fcaac3d758d64edd8b8ee5604daf512fefe227c9 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 2 Aug 2026 21:29:36 +0300 Subject: [PATCH 01/61] expert heatmap: decay-tracked usage counters per layer hooks into build_moe_ffn and process_ubatch, new file llama-expert-heatmap does the actual tracking, minimal diff on upstream files. --expert-heat-decay and --expert-heat-log-period for config. --- common/arg.cpp | 14 ++++++++ common/common.cpp | 3 ++ common/common.h | 3 ++ include/llama.h | 3 ++ src/CMakeLists.txt | 1 + src/llama-context.cpp | 31 ++++++++++++++++ src/llama-context.h | 5 +++ src/llama-expert-heatmap.cpp | 69 ++++++++++++++++++++++++++++++++++++ src/llama-expert-heatmap.h | 22 ++++++++++++ src/llama-graph.cpp | 3 ++ src/llama-graph.h | 2 ++ 11 files changed, 156 insertions(+) create mode 100644 src/llama-expert-heatmap.cpp create mode 100644 src/llama-expert-heatmap.h diff --git a/common/arg.cpp b/common/arg.cpp index 79480e06f9d..e5ff3eac35d 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2645,6 +2645,20 @@ common_params_context common_params_parser_init(common_params & params, llama_ex } } ).set_env("LLAMA_ARG_N_CPU_MOE")); + add_opt(common_arg( + {"--expert-heat-decay"}, "F", + "expert heatmap decay rate per update (default: 0.99)", + [](common_params & params, const std::string & value) { + params.expert_heat_decay = std::stof(value); + } + ).set_env("LLAMA_ARG_EXPERT_HEAT_DECAY")); + add_opt(common_arg( + {"--expert-heat-log-period"}, "N", + "expert heatmap log interval in updates (default: 100)", + [](common_params & params, int value) { + params.expert_heat_log_period = value; + } + ).set_env("LLAMA_ARG_EXPERT_HEAT_LOG_PERIOD")); GGML_ASSERT(params.n_gpu_layers < 0); // string_format would need to be extended for a default >= 0 add_opt(common_arg( {"-ngl", "--gpu-layers", "--n-gpu-layers"}, "N", diff --git a/common/common.cpp b/common/common.cpp index ff27d392fb2..2ac1190ea5d 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1660,6 +1660,9 @@ struct llama_context_params common_context_params_to_llama(const common_params & cparams.type_k = params.cache_type_k; cparams.type_v = params.cache_type_v; + cparams.expert_heat_decay = params.expert_heat_decay; + cparams.expert_heat_log_period = params.expert_heat_log_period; + return cparams; } diff --git a/common/common.h b/common/common.h index 919c0ea103a..8e3c7309201 100644 --- a/common/common.h +++ b/common/common.h @@ -532,6 +532,9 @@ struct common_params { int32_t verbosity = 3; // LOG_LEVEL_INFO int32_t control_vector_layer_start = -1; // layer range for control vector int32_t control_vector_layer_end = -1; // layer range for control vector + + float expert_heat_decay = 0.99f; // multiplicative decay per update + int expert_heat_log_period = 100; // log period in updates bool offline = false; int32_t ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used. diff --git a/include/llama.h b/include/llama.h index 6e53e229723..6339e99947d 100644 --- a/include/llama.h +++ b/include/llama.h @@ -403,6 +403,9 @@ extern "C" { struct llama_sampler_seq_config * samplers; size_t n_samplers; + float expert_heat_decay; // expert heatmap decay per update + int expert_heat_log_period; // expert heatmap log interval + // a source/target/parent context // can be utilized in various ways, for example by sharing results or llama_memory between 2 contexts struct llama_context * ctx_other; diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt index 320784c3a8c..e7799289029 100644 --- a/src/CMakeLists.txt +++ b/src/CMakeLists.txt @@ -17,6 +17,7 @@ add_library(llama llama-chat.cpp llama-context.cpp llama-cparams.cpp + llama-expert-heatmap.cpp llama-grammar.cpp llama-graph.cpp llama-hparams.cpp diff --git a/src/llama-context.cpp b/src/llama-context.cpp index 19cca7df1e9..63b65195520 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -463,6 +463,13 @@ llama_context::llama_context( } } + if (hparams.n_expert > 0 && !cparams.warmup) { + expert_heatmap = std::make_unique( + hparams.n_layer(), hparams.n_expert, + params.expert_heat_decay, + params.expert_heat_log_period); + } + // Initialize the full vocabulary token ids for backend samplers. { const int n_vocab = model.vocab.n_tokens(); @@ -574,6 +581,26 @@ void llama_context::resolve_fused_ops(const llama_memory_context_i * mctx, uint3 } } +void llama_context::update_expert_heatmap(const llm_graph_result * res) { + if (!expert_heatmap || res->moe_sel_experts.empty()) { + return; + } + + for (const auto & [il, tensor] : res->moe_sel_experts) { + int64_t n_expert_used = tensor->ne[0]; + int64_t n_tokens = tensor->ne[1]; + + if (!tensor->data) { + continue; + } + + std::vector expert_ids(n_expert_used * n_tokens); + ggml_backend_tensor_get(tensor, expert_ids.data(), 0, expert_ids.size() * sizeof(int32_t)); + + expert_heatmap->update(il, expert_ids.data(), n_expert_used, n_tokens); + } +} + void llama_context::sched_reserve() { if (!sched_need_reserve) { return; @@ -1385,6 +1412,8 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll return nullptr; } + update_expert_heatmap(res); + ret = GGML_STATUS_SUCCESS; return res; @@ -3517,6 +3546,8 @@ llama_context_params llama_context_default_params() { /*.kv_unified =*/ false, /*.sampler =*/ nullptr, /*.n_sampler =*/ 0, + /*.expert_heat_decay =*/ 0.99f, + /*.expert_heat_log_period =*/ 100, /*.ctx_other =*/ nullptr, }; diff --git a/src/llama-context.h b/src/llama-context.h index bf91daa8b56..22d32aef35b 100644 --- a/src/llama-context.h +++ b/src/llama-context.h @@ -7,6 +7,7 @@ #include "llama-adapter.h" #include "llama-impl.h" #include "llama-memory.h" +#include "llama-expert-heatmap.h" #include "ggml-cpp.h" #include "ggml-opt.h" @@ -266,6 +267,8 @@ struct llama_context { // that differs from the layer it belongs to (usually due to missing backend support) void resolve_fused_ops(const llama_memory_context_i * mctx, uint32_t n_seqs); + void update_expert_heatmap(const llm_graph_result * res); + // TODO: read/write lora adapters and cvec size_t state_write_data(llama_io_write_i & io); size_t state_read_data (llama_io_read_i & io); @@ -367,6 +370,8 @@ struct llama_context { llm_graph_result_ptr gf_res_prev; llm_graph_result_ptr gf_res_reserve; + std::unique_ptr expert_heatmap; + // host buffer for the model output (logits and embeddings) ggml_backend_buffer_ptr buf_output; diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp new file mode 100644 index 00000000000..344dc82cec1 --- /dev/null +++ b/src/llama-expert-heatmap.cpp @@ -0,0 +1,69 @@ +#include "llama-expert-heatmap.h" +#include "llama-impl.h" + +#include +#include +#include + +llama_expert_heatmap::llama_expert_heatmap( + int n_layers, int n_experts, + float decay_rate, int log_period) : + n_layers(n_layers), + n_experts(n_experts), + decay_rate(decay_rate), + log_period(log_period), + update_count(0), + heat(n_layers * n_experts, 0.0f) { +} + +void llama_expert_heatmap::update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens) { + decay_all(); + + float * layer_heat = heat.data() + layer_idx * n_experts; + + for (int t = 0; t < n_tokens; t++) { + for (int e = 0; e < n_expert_used; e++) { + int32_t id = expert_ids[t * n_expert_used + e]; + if (id >= 0 && id < n_experts) { + layer_heat[id] += 1.0f; + } + } + } + + update_count++; + if (log_period > 0 && update_count % log_period == 0) { + log(); + } +} + +void llama_expert_heatmap::decay_all() { + for (int i = 0; i < n_layers * n_experts; i++) { + heat[i] *= decay_rate; + } +} + +void llama_expert_heatmap::log() const { + LLAMA_LOG("=== Expert heatmap (update %d) ===\n", update_count); + + for (int l = 0; l < n_layers; l++) { + const float * layer_heat = heat.data() + l * n_experts; + int active_count = 0; + float max_heat = 0.0f; + int max_id = -1; + + for (int e = 0; e < n_experts; e++) { + if (layer_heat[e] > 0.01f) { + active_count++; + } + if (layer_heat[e] > max_heat) { + max_heat = layer_heat[e]; + max_id = e; + } + } + + if (active_count > 0) { + LLAMA_LOG(" layer %3d: %d warm experts, max heat=%.2f (expert %d)\n", + l, active_count, max_heat, max_id); + } + } +} diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h new file mode 100644 index 00000000000..510c7737b32 --- /dev/null +++ b/src/llama-expert-heatmap.h @@ -0,0 +1,22 @@ +#pragma once + +#include +#include + +struct llama_expert_heatmap { + int n_layers; + int n_experts; + float decay_rate; + int log_period; + int update_count; + + std::vector heat; + + llama_expert_heatmap(int n_layers, int n_experts, + float decay_rate = 0.99f, + int log_period = 100); + + void update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens); + void decay_all(); + void log() const; +}; diff --git a/src/llama-graph.cpp b/src/llama-graph.cpp index e12a8cdc2aa..7ea1bae4cce 100644 --- a/src/llama-graph.cpp +++ b/src/llama-graph.cpp @@ -1276,6 +1276,7 @@ void llm_graph_result::reset() { inputs.clear(); fused_nodes.clear(); + moe_sel_experts.clear(); buf_compute_meta.resize(ggml_tensor_overhead()*max_nodes + ggml_graph_overhead_custom(max_nodes, false)); @@ -1997,6 +1998,8 @@ ggml_tensor * llm_graph_context::build_moe_ffn( } cb(selected_experts, "ffn_moe_topk", il); + res->moe_sel_experts.emplace_back(il, selected_experts); + if (arch == LLM_ARCH_GROVEMOE && n_expert != hparams.n_expert) { // TODO: Use scalar div instead when/if implemented ggml_tensor * f_sel = ggml_cast(ctx0, selected_experts, GGML_TYPE_F32); diff --git a/src/llama-graph.h b/src/llama-graph.h index 160e2941355..5ad665be28f 100644 --- a/src/llama-graph.h +++ b/src/llama-graph.h @@ -888,6 +888,8 @@ class llm_graph_result { std::map t_sampled; std::map t_sampled_probs; + std::vector> moe_sel_experts; + std::vector inputs; std::vector fused_nodes; From 610802380f8a7aa4ac6dc1333d9509e78680bf66 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 2 Aug 2026 21:57:09 +0300 Subject: [PATCH 02/61] expert heatmap: add top-S ranking, log top-8 per layer --- src/llama-expert-heatmap.cpp | 32 +++++++++++++++++++++++++++++++- src/llama-expert-heatmap.h | 2 ++ 2 files changed, 33 insertions(+), 1 deletion(-) diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 344dc82cec1..2cdae9980ef 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -62,8 +62,38 @@ void llama_expert_heatmap::log() const { } if (active_count > 0) { - LLAMA_LOG(" layer %3d: %d warm experts, max heat=%.2f (expert %d)\n", + LLAMA_LOG(" layer %3d: %d warm experts, max heat=%.2f (expert %d)", l, active_count, max_heat, max_id); + + auto top = get_top_s(l, 8); + LLAMA_LOG(" top-8="); + for (size_t i = 0; i < top.size(); i++) { + LLAMA_LOG("%s%d", i > 0 ? "," : "{", top[i]); + } + LLAMA_LOG("}\n"); } } } + +std::vector llama_expert_heatmap::get_top_s(int layer_idx, int s) const { + std::vector result; + if (layer_idx < 0 || layer_idx >= n_layers || s <= 0) { + return result; + } + + const float * layer_heat = heat.data() + layer_idx * n_experts; + + std::vector indices(n_experts); + for (int i = 0; i < n_experts; i++) { + indices[i] = i; + } + + int k = std::min(s, n_experts); + std::partial_sort(indices.begin(), indices.begin() + k, indices.end(), + [layer_heat](int a, int b) { + return layer_heat[a] > layer_heat[b]; + }); + + result.assign(indices.begin(), indices.begin() + k); + return result; +} diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index 510c7737b32..bbc081635b9 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -19,4 +19,6 @@ struct llama_expert_heatmap { void update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens); void decay_all(); void log() const; + + std::vector get_top_s(int layer_idx, int s) const; }; From 21537c16f008f7acbed2932be20de7765d6f4c93 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 2 Aug 2026 22:09:06 +0300 Subject: [PATCH 03/61] expert heatmap: add --expert-hot-s flag for GPU hot store slot count --- common/arg.cpp | 7 +++++++ common/common.cpp | 1 + common/common.h | 1 + include/llama.h | 1 + src/llama-context.cpp | 4 +++- src/llama-expert-heatmap.cpp | 3 ++- src/llama-expert-heatmap.h | 4 +++- 7 files changed, 18 insertions(+), 3 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index e5ff3eac35d..a9080f6596f 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2659,6 +2659,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex params.expert_heat_log_period = value; } ).set_env("LLAMA_ARG_EXPERT_HEAT_LOG_PERIOD")); + add_opt(common_arg( + {"--expert-hot-s"}, "N", + "number of top expert slots for GPU hot store (default: 0 = disabled)", + [](common_params & params, int value) { + params.expert_hot_s = value; + } + ).set_env("LLAMA_ARG_EXPERT_HOT_S")); GGML_ASSERT(params.n_gpu_layers < 0); // string_format would need to be extended for a default >= 0 add_opt(common_arg( {"-ngl", "--gpu-layers", "--n-gpu-layers"}, "N", diff --git a/common/common.cpp b/common/common.cpp index 2ac1190ea5d..6620c090cc3 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1662,6 +1662,7 @@ struct llama_context_params common_context_params_to_llama(const common_params & cparams.expert_heat_decay = params.expert_heat_decay; cparams.expert_heat_log_period = params.expert_heat_log_period; + cparams.expert_hot_s = params.expert_hot_s; return cparams; } diff --git a/common/common.h b/common/common.h index 8e3c7309201..e7b4901dd92 100644 --- a/common/common.h +++ b/common/common.h @@ -535,6 +535,7 @@ struct common_params { float expert_heat_decay = 0.99f; // multiplicative decay per update int expert_heat_log_period = 100; // log period in updates + int expert_hot_s = 0; // top-S expert slots (0 = disabled) bool offline = false; int32_t ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used. diff --git a/include/llama.h b/include/llama.h index 6339e99947d..276b9621a46 100644 --- a/include/llama.h +++ b/include/llama.h @@ -405,6 +405,7 @@ extern "C" { float expert_heat_decay; // expert heatmap decay per update int expert_heat_log_period; // expert heatmap log interval + int expert_hot_s; // number of top-S expert slots for GPU hot store // a source/target/parent context // can be utilized in various ways, for example by sharing results or llama_memory between 2 contexts diff --git a/src/llama-context.cpp b/src/llama-context.cpp index 63b65195520..a123ba3505c 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -467,7 +467,8 @@ llama_context::llama_context( expert_heatmap = std::make_unique( hparams.n_layer(), hparams.n_expert, params.expert_heat_decay, - params.expert_heat_log_period); + params.expert_heat_log_period, + params.expert_hot_s); } // Initialize the full vocabulary token ids for backend samplers. @@ -3548,6 +3549,7 @@ llama_context_params llama_context_default_params() { /*.n_sampler =*/ 0, /*.expert_heat_decay =*/ 0.99f, /*.expert_heat_log_period =*/ 100, + /*.expert_hot_s =*/ 0, /*.ctx_other =*/ nullptr, }; diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 2cdae9980ef..4b256b8a849 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -7,9 +7,10 @@ llama_expert_heatmap::llama_expert_heatmap( int n_layers, int n_experts, - float decay_rate, int log_period) : + float decay_rate, int log_period, int hot_s) : n_layers(n_layers), n_experts(n_experts), + hot_s(hot_s), decay_rate(decay_rate), log_period(log_period), update_count(0), diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index bbc081635b9..7ace905ac49 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -6,6 +6,7 @@ struct llama_expert_heatmap { int n_layers; int n_experts; + int hot_s; float decay_rate; int log_period; int update_count; @@ -14,7 +15,8 @@ struct llama_expert_heatmap { llama_expert_heatmap(int n_layers, int n_experts, float decay_rate = 0.99f, - int log_period = 100); + int log_period = 100, + int hot_s = 0); void update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens); void decay_all(); From b27d2f59eba33d9f8e5da884a0092f5406921f3e Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 2 Aug 2026 23:24:59 +0300 Subject: [PATCH 04/61] expert heatmap: fix GPU tensor readback via ggml_set_output and synchronize --- src/llama-context.cpp | 5 ++++- src/llama-graph.cpp | 1 + 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/src/llama-context.cpp b/src/llama-context.cpp index a123ba3505c..95c488cba9f 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -1413,7 +1413,10 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll return nullptr; } - update_expert_heatmap(res); + if (expert_heatmap) { + synchronize(); + update_expert_heatmap(res); + } ret = GGML_STATUS_SUCCESS; diff --git a/src/llama-graph.cpp b/src/llama-graph.cpp index 7ea1bae4cce..b4a599baba7 100644 --- a/src/llama-graph.cpp +++ b/src/llama-graph.cpp @@ -1995,6 +1995,7 @@ ggml_tensor * llm_graph_context::build_moe_ffn( if (selected_experts == nullptr) { selected_experts = ggml_argsort_top_k(ctx0, selection_probs, n_expert_used); // [n_expert_used, n_tokens] cb(selected_experts->src[0], "ffn_moe_argsort", il); + ggml_set_output(selected_experts); } cb(selected_experts, "ffn_moe_topk", il); From 413e65dde9ee015043fc01615e96f11b2b67a6e6 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 2 Aug 2026 23:40:06 +0300 Subject: [PATCH 05/61] expert heatmap: move readback logic into heatmap module --- src/llama-context.cpp | 22 +--------------------- src/llama-context.h | 2 -- src/llama-expert-heatmap.cpp | 23 +++++++++++++++++++++++ src/llama-expert-heatmap.h | 4 ++++ 4 files changed, 28 insertions(+), 23 deletions(-) diff --git a/src/llama-context.cpp b/src/llama-context.cpp index 95c488cba9f..d1512a5275b 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -582,26 +582,6 @@ void llama_context::resolve_fused_ops(const llama_memory_context_i * mctx, uint3 } } -void llama_context::update_expert_heatmap(const llm_graph_result * res) { - if (!expert_heatmap || res->moe_sel_experts.empty()) { - return; - } - - for (const auto & [il, tensor] : res->moe_sel_experts) { - int64_t n_expert_used = tensor->ne[0]; - int64_t n_tokens = tensor->ne[1]; - - if (!tensor->data) { - continue; - } - - std::vector expert_ids(n_expert_used * n_tokens); - ggml_backend_tensor_get(tensor, expert_ids.data(), 0, expert_ids.size() * sizeof(int32_t)); - - expert_heatmap->update(il, expert_ids.data(), n_expert_used, n_tokens); - } -} - void llama_context::sched_reserve() { if (!sched_need_reserve) { return; @@ -1415,7 +1395,7 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll if (expert_heatmap) { synchronize(); - update_expert_heatmap(res); + expert_heatmap->update_from_graph(res->moe_sel_experts); } ret = GGML_STATUS_SUCCESS; diff --git a/src/llama-context.h b/src/llama-context.h index 22d32aef35b..a217f9dbf62 100644 --- a/src/llama-context.h +++ b/src/llama-context.h @@ -267,8 +267,6 @@ struct llama_context { // that differs from the layer it belongs to (usually due to missing backend support) void resolve_fused_ops(const llama_memory_context_i * mctx, uint32_t n_seqs); - void update_expert_heatmap(const llm_graph_result * res); - // TODO: read/write lora adapters and cvec size_t state_write_data(llama_io_write_i & io); size_t state_read_data (llama_io_read_i & io); diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 4b256b8a849..3513ae5607a 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -1,6 +1,9 @@ #include "llama-expert-heatmap.h" #include "llama-impl.h" +#include "ggml.h" +#include "ggml-backend.h" + #include #include #include @@ -37,6 +40,26 @@ void llama_expert_heatmap::update(int layer_idx, const int32_t * expert_ids, int } } +void llama_expert_heatmap::update_from_graph(const std::vector> & moe_sel_experts) { + if (moe_sel_experts.empty()) { + return; + } + + for (const auto & [il, tensor] : moe_sel_experts) { + int64_t n_expert_used = tensor->ne[0]; + int64_t n_tokens = tensor->ne[1]; + + if (!tensor->data) { + continue; + } + + std::vector expert_ids(n_expert_used * n_tokens); + ggml_backend_tensor_get(tensor, expert_ids.data(), 0, expert_ids.size() * sizeof(int32_t)); + + update(il, expert_ids.data(), n_expert_used, n_tokens); + } +} + void llama_expert_heatmap::decay_all() { for (int i = 0; i < n_layers * n_experts; i++) { heat[i] *= decay_rate; diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index 7ace905ac49..25082ac2e6a 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -2,6 +2,9 @@ #include #include +#include + +struct ggml_tensor; struct llama_expert_heatmap { int n_layers; @@ -19,6 +22,7 @@ struct llama_expert_heatmap { int hot_s = 0); void update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens); + void update_from_graph(const std::vector> & moe_sel_experts); void decay_all(); void log() const; From 23ff80ec312ca5c59f0ef5ca2194ad8aa5354a9d Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 3 Aug 2026 01:26:17 +0300 Subject: [PATCH 06/61] expert hotstore: add per-layer expert slot sizing --- src/CMakeLists.txt | 1 + src/llama-context.cpp | 7 +++++ src/llama-context.h | 2 ++ src/llama-expert-hotstore.cpp | 50 +++++++++++++++++++++++++++++++++++ src/llama-expert-hotstore.h | 24 +++++++++++++++++ 5 files changed, 84 insertions(+) create mode 100644 src/llama-expert-hotstore.cpp create mode 100644 src/llama-expert-hotstore.h diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt index e7799289029..5039af7bec2 100644 --- a/src/CMakeLists.txt +++ b/src/CMakeLists.txt @@ -18,6 +18,7 @@ add_library(llama llama-context.cpp llama-cparams.cpp llama-expert-heatmap.cpp + llama-expert-hotstore.cpp llama-grammar.cpp llama-graph.cpp llama-hparams.cpp diff --git a/src/llama-context.cpp b/src/llama-context.cpp index d1512a5275b..45952a32b44 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -471,6 +471,13 @@ llama_context::llama_context( params.expert_hot_s); } + if (hparams.n_expert > 0 && !cparams.warmup) { + expert_hotstore = std::make_unique( + &model, hparams.n_layer(), hparams.n_expert, + params.expert_hot_s); + expert_hotstore->log(); + } + // Initialize the full vocabulary token ids for backend samplers. { const int n_vocab = model.vocab.n_tokens(); diff --git a/src/llama-context.h b/src/llama-context.h index a217f9dbf62..a56ea564724 100644 --- a/src/llama-context.h +++ b/src/llama-context.h @@ -8,6 +8,7 @@ #include "llama-impl.h" #include "llama-memory.h" #include "llama-expert-heatmap.h" +#include "llama-expert-hotstore.h" #include "ggml-cpp.h" #include "ggml-opt.h" @@ -369,6 +370,7 @@ struct llama_context { llm_graph_result_ptr gf_res_reserve; std::unique_ptr expert_heatmap; + std::unique_ptr expert_hotstore; // host buffer for the model output (logits and embeddings) ggml_backend_buffer_ptr buf_output; diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp new file mode 100644 index 00000000000..4795cfa555a --- /dev/null +++ b/src/llama-expert-hotstore.cpp @@ -0,0 +1,50 @@ +#include "llama-expert-hotstore.h" +#include "llama-impl.h" +#include "llama-model.h" + +#include "ggml.h" + +#include + +// matches the weight tensor of an expert tensor, e.g.: +// blk.0.ffn_gate_exps.weight +// blk.3.ffn_down_chexps.weight +// follows the same convention as LLM_FFN_EXPS_REGEX in common.h +static const std::regex g_re_exps_weight("blk\\.(\\d+)\\.ffn_(up|down|gate|gate_up)_(ch|)exps\\.weight"); + +llama_expert_hotstore::llama_expert_hotstore( + const llama_model * model, int n_layers, int n_experts, int hot_s) : + n_layers(n_layers), + n_experts(n_experts), + hot_s(hot_s), + bytes_per_slot(n_layers, 0) { + if (n_layers <= 0) { + return; + } + + for (const auto & [name, tensor] : llama_internal_get_tensor_map(model)) { + std::smatch m; + if (std::regex_search(name, m, g_re_exps_weight)) { + const int il = std::stoi(m[1].str()); + if (il >= 0 && il < n_layers && tensor->ne[2] > 0) { + // a slot holds nbytes/n_experts of this tensor + bytes_per_slot[il] += ggml_nbytes(tensor) / (size_t) tensor->ne[2]; + } + } + } +} + +void llama_expert_hotstore::log() const { + LLAMA_LOG("=== Expert hotstore sizing (S=%d) ===\n", hot_s); + size_t total = 0; + for (int il = 0; il < n_layers; il++) { + total += bytes_per_slot[il]; + LLAMA_LOG(" layer %3d: bytes/slot = %zu\n", il, bytes_per_slot[il]); + } + LLAMA_LOG(" total bytes/slot across all layers = %zu (%zu MiB)\n", + total, total / (1024 * 1024)); + if (hot_s > 0) { + LLAMA_LOG(" estimated VRAM for %d slots = %zu (%zu MiB)\n", + hot_s, total * (size_t) hot_s, total * (size_t) hot_s / (1024 * 1024)); + } +} \ No newline at end of file diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h new file mode 100644 index 00000000000..30b9cd72c15 --- /dev/null +++ b/src/llama-expert-hotstore.h @@ -0,0 +1,24 @@ +#pragma once + +#include +#include +#include + +struct llama_model; + +// stores per-layer sizing for the Mixture of Experts GPU hot store. +// one "slot" holds a single expert's weights for one layer. +struct llama_expert_hotstore { + int n_layers; + int n_experts; + int hot_s; + + // bytes of a single expert slot per layer, summed over that layer's + // expert weight tensors (gate/up/down, incl. chexps variants) + std::vector bytes_per_slot; + + llama_expert_hotstore(const llama_model * model, int n_layers, + int n_experts, int hot_s); + + void log() const; +}; \ No newline at end of file From 289c41ef5cc3ca65e641982550387e3e1055f0d8 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 3 Aug 2026 02:26:20 +0300 Subject: [PATCH 07/61] expert hotstore: allocate GPU hot store buffers for S slots --- src/llama-context.cpp | 6 +++ src/llama-expert-hotstore.cpp | 70 +++++++++++++++++++++++++++++++++-- src/llama-expert-hotstore.h | 21 ++++++++++- 3 files changed, 92 insertions(+), 5 deletions(-) diff --git a/src/llama-context.cpp b/src/llama-context.cpp index 45952a32b44..62660989e9a 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -475,6 +475,12 @@ llama_context::llama_context( expert_hotstore = std::make_unique( &model, hparams.n_layer(), hparams.n_expert, params.expert_hot_s); + for (auto & backend : backends) { + if (ggml_backend_dev_type(ggml_backend_get_device(backend.get())) != GGML_BACKEND_DEVICE_TYPE_CPU) { + expert_hotstore->allocate(ggml_backend_get_default_buffer_type(backend.get())); + break; + } + } expert_hotstore->log(); } diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 4795cfa555a..bc06b020f7d 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -29,11 +29,68 @@ llama_expert_hotstore::llama_expert_hotstore( if (il >= 0 && il < n_layers && tensor->ne[2] > 0) { // a slot holds nbytes/n_experts of this tensor bytes_per_slot[il] += ggml_nbytes(tensor) / (size_t) tensor->ne[2]; + entries.push_back({il, tensor, nullptr}); } } } } +bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { + if (hot_s <= 0 || entries.empty()) { + return false; + } + if (hot_s > n_experts) { + throw std::runtime_error(format("%s: hot store S=%d exceeds n_experts=%d", + __func__, hot_s, n_experts)); + } + + // a no_alloc context just for the hot tensor metadata + ggml_init_params params = { + /*.mem_size =*/ ggml_tensor_overhead() * entries.size(), + /*.mem_buffer =*/ nullptr, + /*.no_alloc =*/ true, + }; + ctx = ggml_context_ptr(ggml_init(params)); + if (!ctx) { + LLAMA_LOG_ERROR("%s: hot store: failed to create ggml context\n", __func__); + return false; + } + + // one hot tensor per model expert tensor, trimmed to hot_s slots + for (auto & e : entries) { + e.dst = ggml_new_tensor_3d(ctx.get(), e.src->type, e.src->ne[0], e.src->ne[1], hot_s); + } + + // check whether the buffer would fit before committing any VRAM + const size_t need = ggml_backend_alloc_ctx_tensors_from_buft_size(ctx.get(), gpu_buft); + if (need == 0) { + LLAMA_LOG_ERROR("%s: hot store: zero-sized buffer, disabled\n", __func__); + ctx.reset(); + return false; + } + + size_t free_mem = 0, total_mem = 0; + ggml_backend_dev_t dev = ggml_backend_buft_get_device(gpu_buft); + if (dev) { + ggml_backend_dev_memory(dev, &free_mem, &total_mem); + } + if (dev && free_mem < need) { + throw std::runtime_error(format("%s: not enough memory to allocate the GPU hot store of %d slots (%zu MiB needed, %zu MiB free on %s)", + __func__, hot_s, need / (1024 * 1024), free_mem / (1024 * 1024), + ggml_backend_dev_name(dev))); + } + + ggml_backend_buffer_t b = ggml_backend_alloc_ctx_tensors_from_buft(ctx.get(), gpu_buft); + if (b == nullptr) { + throw std::runtime_error(format("%s: unable to allocate hot store buffer of %d slots (%zu MiB)", + __func__, hot_s, need / (1024 * 1024))); + } + buf = ggml_backend_buffer_ptr(b); + ggml_backend_buffer_set_usage(buf.get(), GGML_BACKEND_BUFFER_USAGE_WEIGHTS); + + return true; +} + void llama_expert_hotstore::log() const { LLAMA_LOG("=== Expert hotstore sizing (S=%d) ===\n", hot_s); size_t total = 0; @@ -43,8 +100,13 @@ void llama_expert_hotstore::log() const { } LLAMA_LOG(" total bytes/slot across all layers = %zu (%zu MiB)\n", total, total / (1024 * 1024)); - if (hot_s > 0) { - LLAMA_LOG(" estimated VRAM for %d slots = %zu (%zu MiB)\n", - hot_s, total * (size_t) hot_s, total * (size_t) hot_s / (1024 * 1024)); + if (buf) { + LLAMA_LOG(" GPU hot store allocated: %s, %zu bytes (%zu MiB) for %d slots\n", + ggml_backend_buffer_name(buf.get()), + ggml_backend_buffer_get_size(buf.get()), + ggml_backend_buffer_get_size(buf.get()) / (1024 * 1024), + hot_s); + } else if (hot_s > 0) { + LLAMA_LOG(" hot store DISABLED (%d slots requested)\n", hot_s); } -} \ No newline at end of file +} diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index 30b9cd72c15..658d4400e2f 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -2,8 +2,11 @@ #include #include +#include #include +#include "ggml-cpp.h" + struct llama_model; // stores per-layer sizing for the Mixture of Experts GPU hot store. @@ -17,8 +20,24 @@ struct llama_expert_hotstore { // expert weight tensors (gate/up/down, incl. chexps variants) std::vector bytes_per_slot; + // one hot tensor per expert weight tensor, shape {ne0, ne1, hot_s} + struct entry { + int layer_idx; + ggml_tensor* src; // model tensor holding all n_experts slices + ggml_tensor* dst; // hot tensor holding hot_s slots + }; + std::vector entries; + + // keeps the GPU buffer (and its no_alloc context) alive + ggml_context_ptr ctx; + ggml_backend_buffer_ptr buf; + llama_expert_hotstore(const llama_model * model, int n_layers, int n_experts, int hot_s); + // allocate the GPU hot store for `hot_s` slots. returns false (and + // leaves the store disabled) on failure or shortage of VRAM. + bool allocate(ggml_backend_buffer_type_t gpu_buft); + void log() const; -}; \ No newline at end of file +}; From 284215c048d985ef7cefbd637145c3d67d8a7b4f Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 3 Aug 2026 02:38:41 +0300 Subject: [PATCH 08/61] expert hotstore: reduced cross contamination when expert args off heatmap only allocated when log period or hot S is set, hot store only when hot S is set, defaults off --- common/common.h | 2 +- src/llama-context.cpp | 7 ++++--- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/common/common.h b/common/common.h index e7b4901dd92..d113485b13e 100644 --- a/common/common.h +++ b/common/common.h @@ -534,7 +534,7 @@ struct common_params { int32_t control_vector_layer_end = -1; // layer range for control vector float expert_heat_decay = 0.99f; // multiplicative decay per update - int expert_heat_log_period = 100; // log period in updates + int expert_heat_log_period = 0; // log period in updates (0 = off) int expert_hot_s = 0; // top-S expert slots (0 = disabled) bool offline = false; diff --git a/src/llama-context.cpp b/src/llama-context.cpp index 62660989e9a..dd8f710729b 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -463,7 +463,8 @@ llama_context::llama_context( } } - if (hparams.n_expert > 0 && !cparams.warmup) { + if (hparams.n_expert > 0 && !cparams.warmup && + (params.expert_heat_log_period != 0 || params.expert_hot_s != 0)) { expert_heatmap = std::make_unique( hparams.n_layer(), hparams.n_expert, params.expert_heat_decay, @@ -471,7 +472,7 @@ llama_context::llama_context( params.expert_hot_s); } - if (hparams.n_expert > 0 && !cparams.warmup) { + if (hparams.n_expert > 0 && !cparams.warmup && params.expert_hot_s != 0) { expert_hotstore = std::make_unique( &model, hparams.n_layer(), hparams.n_expert, params.expert_hot_s); @@ -3544,7 +3545,7 @@ llama_context_params llama_context_default_params() { /*.sampler =*/ nullptr, /*.n_sampler =*/ 0, /*.expert_heat_decay =*/ 0.99f, - /*.expert_heat_log_period =*/ 100, + /*.expert_heat_log_period =*/ 0, /*.expert_hot_s =*/ 0, /*.ctx_other =*/ nullptr, }; From 8e955700f3b8c6febe64fa0e52648b18d9d09f90 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 3 Aug 2026 02:45:22 +0300 Subject: [PATCH 09/61] expert heatmap: count updates in tokens not layers --- src/llama-expert-heatmap.cpp | 24 ++++++++++++------------ src/llama-expert-heatmap.h | 2 +- 2 files changed, 13 insertions(+), 13 deletions(-) diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 3513ae5607a..1504bb9010b 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -5,6 +5,7 @@ #include "ggml-backend.h" #include +#include #include #include @@ -16,7 +17,7 @@ llama_expert_heatmap::llama_expert_heatmap( hot_s(hot_s), decay_rate(decay_rate), log_period(log_period), - update_count(0), + tokens_total(0), heat(n_layers * n_experts, 0.0f) { } @@ -33,30 +34,29 @@ void llama_expert_heatmap::update(int layer_idx, const int32_t * expert_ids, int } } } - - update_count++; - if (log_period > 0 && update_count % log_period == 0) { - log(); - } } - void llama_expert_heatmap::update_from_graph(const std::vector> & moe_sel_experts) { if (moe_sel_experts.empty()) { return; } + int64_t n_tokens = 0; for (const auto & [il, tensor] : moe_sel_experts) { - int64_t n_expert_used = tensor->ne[0]; - int64_t n_tokens = tensor->ne[1]; + n_tokens = tensor->ne[1]; if (!tensor->data) { continue; } - std::vector expert_ids(n_expert_used * n_tokens); + std::vector expert_ids(tensor->ne[0] * n_tokens); ggml_backend_tensor_get(tensor, expert_ids.data(), 0, expert_ids.size() * sizeof(int32_t)); - update(il, expert_ids.data(), n_expert_used, n_tokens); + update(il, expert_ids.data(), tensor->ne[0], n_tokens); + } + + tokens_total += n_tokens; + if (log_period > 0 && tokens_total % log_period == 0) { + log(); } } @@ -67,7 +67,7 @@ void llama_expert_heatmap::decay_all() { } void llama_expert_heatmap::log() const { - LLAMA_LOG("=== Expert heatmap (update %d) ===\n", update_count); + LLAMA_LOG("=== Expert heatmap (tokens %" PRId64 ") ===\n", tokens_total); for (int l = 0; l < n_layers; l++) { const float * layer_heat = heat.data() + l * n_experts; diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index 25082ac2e6a..2458d9b07db 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -12,7 +12,7 @@ struct llama_expert_heatmap { int hot_s; float decay_rate; int log_period; - int update_count; + int64_t tokens_total; // real tokens seen (not multiplied by layers) std::vector heat; From 08e657d416148df403bfb6ab3ba856e6db489394 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 3 Aug 2026 02:50:45 +0300 Subject: [PATCH 10/61] expert heatmap: fix decay and log trigger decay_all once per batch, not once per layer; log on crossed boundaries instead of exact multiples Assisted-by: Gemini 3.1 Pro --- src/llama-expert-heatmap.cpp | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 1504bb9010b..8ea9c408e8d 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -22,8 +22,6 @@ llama_expert_heatmap::llama_expert_heatmap( } void llama_expert_heatmap::update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens) { - decay_all(); - float * layer_heat = heat.data() + layer_idx * n_experts; for (int t = 0; t < n_tokens; t++) { @@ -40,6 +38,8 @@ void llama_expert_heatmap::update_from_graph(const std::vectorne[1]; @@ -55,7 +55,7 @@ void llama_expert_heatmap::update_from_graph(const std::vector 0 && tokens_total % log_period == 0) { + if (log_period > 0 && tokens_total / log_period > (tokens_total - n_tokens) / log_period) { log(); } } From 1aefbbe58bb619220443afd1089d36c721036bc1 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 3 Aug 2026 03:07:59 +0300 Subject: [PATCH 11/61] expert hotstore: copy top-S experts to GPU after first ubatch --- src/llama-context.cpp | 3 +++ src/llama-expert-hotstore.cpp | 27 +++++++++++++++++++++++++++ src/llama-expert-hotstore.h | 8 ++++++++ 3 files changed, 38 insertions(+) diff --git a/src/llama-context.cpp b/src/llama-context.cpp index dd8f710729b..548790adb6f 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -1411,6 +1411,9 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll synchronize(); expert_heatmap->update_from_graph(res->moe_sel_experts); } + if (expert_heatmap && expert_hotstore && !expert_hotstore->is_filled) { + expert_hotstore->copy_top_s(*expert_heatmap); + } ret = GGML_STATUS_SUCCESS; diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index bc06b020f7d..018731b3da4 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -1,8 +1,10 @@ #include "llama-expert-hotstore.h" +#include "llama-expert-heatmap.h" #include "llama-impl.h" #include "llama-model.h" #include "ggml.h" +#include "ggml-backend.h" #include @@ -91,6 +93,31 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { return true; } +void llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { + if (is_filled || hot_s <= 0 || entries.empty()) { + return; + } + + for (const auto & e : entries) { + const size_t slot = ggml_nbytes(e.src) / (size_t) e.src->ne[2]; + const char * src = e.src->data ? (const char *) ggml_get_data(e.src) : nullptr; + if (!src) { + continue; + } + + const auto top = heatmap.get_top_s(e.layer_idx, hot_s); + for (size_t p = 0; p < top.size() && p < (size_t) hot_s; p++) { + const int ex = top[p]; + const size_t src_off = (size_t) ex * slot; + const size_t dst_off = p * slot; + ggml_backend_tensor_set(e.dst, src + src_off, dst_off, slot); + } + } + + is_filled = true; + LLAMA_LOG("=== Expert hot store: top-S experts copied to GPU ===\n"); +} + void llama_expert_hotstore::log() const { LLAMA_LOG("=== Expert hotstore sizing (S=%d) ===\n", hot_s); size_t total = 0; diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index 658d4400e2f..8873dca176a 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -8,6 +8,7 @@ #include "ggml-cpp.h" struct llama_model; +struct llama_expert_heatmap; // stores per-layer sizing for the Mixture of Experts GPU hot store. // one "slot" holds a single expert's weights for one layer. @@ -32,6 +33,9 @@ struct llama_expert_hotstore { ggml_context_ptr ctx; ggml_backend_buffer_ptr buf; + // true once the first copy of the top-S experts landed (once per session) + bool is_filled = false; + llama_expert_hotstore(const llama_model * model, int n_layers, int n_experts, int hot_s); @@ -39,5 +43,9 @@ struct llama_expert_hotstore { // leaves the store disabled) on failure or shortage of VRAM. bool allocate(ggml_backend_buffer_type_t gpu_buft); + // copy the top-S expert slices for every layer into the GPU hot store, + // using the given heatmap for the ranking. no-op if already filled. + void copy_top_s(const llama_expert_heatmap & heatmap); + void log() const; }; From cee1740bb250a27634cf369de03202b55b2dceb1 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 3 Aug 2026 04:29:59 +0300 Subject: [PATCH 12/61] expert hotstore: re-sync hot slots on cadence (stable slots) --- src/llama-context.cpp | 12 ++- src/llama-expert-hotstore.cpp | 138 ++++++++++++++++++++++++++++++---- src/llama-expert-hotstore.h | 26 ++++++- 3 files changed, 158 insertions(+), 18 deletions(-) diff --git a/src/llama-context.cpp b/src/llama-context.cpp index 548790adb6f..bb02f68d4e4 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -473,9 +473,11 @@ llama_context::llama_context( } if (hparams.n_expert > 0 && !cparams.warmup && params.expert_hot_s != 0) { + // re-sync cadence ties to the heatmap log period when set, else 100 tokens + const int sync_period = params.expert_heat_log_period > 0 ? params.expert_heat_log_period : 100; expert_hotstore = std::make_unique( &model, hparams.n_layer(), hparams.n_expert, - params.expert_hot_s); + params.expert_hot_s, sync_period); for (auto & backend : backends) { if (ggml_backend_dev_type(ggml_backend_get_device(backend.get())) != GGML_BACKEND_DEVICE_TYPE_CPU) { expert_hotstore->allocate(ggml_backend_get_default_buffer_type(backend.get())); @@ -1411,8 +1413,12 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll synchronize(); expert_heatmap->update_from_graph(res->moe_sel_experts); } - if (expert_heatmap && expert_hotstore && !expert_hotstore->is_filled) { - expert_hotstore->copy_top_s(*expert_heatmap); + if (expert_heatmap && expert_hotstore) { + if (!expert_hotstore->is_filled) { + expert_hotstore->copy_top_s(*expert_heatmap); + } else { + expert_hotstore->maybe_resync(*expert_heatmap); + } } ret = GGML_STATUS_SUCCESS; diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 018731b3da4..07944e0ddc9 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -15,11 +15,12 @@ static const std::regex g_re_exps_weight("blk\\.(\\d+)\\.ffn_(up|down|gate|gate_up)_(ch|)exps\\.weight"); llama_expert_hotstore::llama_expert_hotstore( - const llama_model * model, int n_layers, int n_experts, int hot_s) : + const llama_model * model, int n_layers, int n_experts, int hot_s, int sync_period) : n_layers(n_layers), n_experts(n_experts), hot_s(hot_s), - bytes_per_slot(n_layers, 0) { + bytes_per_slot(n_layers, 0), + sync_period(sync_period) { if (n_layers <= 0) { return; } @@ -35,6 +36,17 @@ llama_expert_hotstore::llama_expert_hotstore( } } } + + // entries is fixed from here on; build a per-layer index of stable + // pointers so copy/resync do not iterate the whole entries vector. + entries_by_layer.assign(n_layers, {}); + for (auto & e : entries) { + entries_by_layer[e.layer_idx].push_back(&e); + } + + if (hot_s > 0) { + slot_to_expert.assign(n_layers, std::vector(hot_s, -1)); + } } bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { @@ -98,26 +110,126 @@ void llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { return; } - for (const auto & e : entries) { - const size_t slot = ggml_nbytes(e.src) / (size_t) e.src->ne[2]; - const char * src = e.src->data ? (const char *) ggml_get_data(e.src) : nullptr; - if (!src) { - continue; + for (int il = 0; il < n_layers; il++) { + const std::vector top = heatmap.get_top_s(il, hot_s); + auto & ste = slot_to_expert[il]; + for (int p = 0; p < (int) top.size() && p < hot_s; p++) { + ste[p] = top[p]; } - const auto top = heatmap.get_top_s(e.layer_idx, hot_s); - for (size_t p = 0; p < top.size() && p < (size_t) hot_s; p++) { - const int ex = top[p]; - const size_t src_off = (size_t) ex * slot; - const size_t dst_off = p * slot; - ggml_backend_tensor_set(e.dst, src + src_off, dst_off, slot); + for (entry * e : entries_by_layer[il]) { + const size_t slot = ggml_nbytes(e->src) / (size_t) e->src->ne[2]; + const char * src = e->src->data ? (const char *) ggml_get_data(e->src) : nullptr; + if (!src) { + continue; + } + for (int p = 0; p < hot_s; p++) { + const int ex = ste[p]; + if (ex < 0) { + continue; + } + ggml_backend_tensor_set(e->dst, src + (size_t) ex * slot, (size_t) p * slot, slot); + } } } + last_sync_tokens = heatmap.tokens_total; is_filled = true; LLAMA_LOG("=== Expert hot store: top-S experts copied to GPU ===\n"); } +void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { + if (!is_filled || hot_s <= 0) { + return; + } + + int swapped = 0; + for (int il = 0; il < n_layers; il++) { + const std::vector top = heatmap.get_top_s(il, hot_s); + auto & ste = slot_to_expert[il]; + + // which experts are in the new ranking + std::vector in_new(n_experts, 0); + for (int e : top) { + if (e >= 0 && e < n_experts) { + in_new[e] = 1; + } + } + + // evict: free slots whose resident expert fell out of the new top-S + for (int p = 0; p < hot_s; p++) { + if (ste[p] >= 0 && !in_new[ste[p]]) { + ste[p] = -1; + } + } + + // collect new experts that are not currently resident + std::vector resident_set(n_experts, 0); + for (int p = 0; p < hot_s; p++) { + if (ste[p] >= 0) { + resident_set[ste[p]] = 1; + } + } + std::vector to_place; + for (int e : top) { + if (e >= 0 && e < n_experts && !resident_set[e]) { + to_place.push_back(e); + } + } + + // place each new expert into the first free slot, copy its weights + for (int e : to_place) { + int p = -1; + for (int q = 0; q < hot_s; q++) { + if (ste[q] < 0) { + p = q; + break; + } + } + if (p < 0) { + break; // no free slot (should not happen: evictions == new) + } + for (entry * ent : entries_by_layer[il]) { + const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; + const char * src = ent->src->data ? (const char *) ggml_get_data(ent->src) : nullptr; + if (!src) { + continue; + } + ggml_backend_tensor_set(ent->dst, src + (size_t) e * slot, (size_t) p * slot, slot); + } + ste[p] = e; + swapped++; + } + } + + last_sync_tokens = heatmap.tokens_total; + if (swapped > 0) { + LLAMA_LOG("=== Expert hot store: re-sync swapped %d expert slots ===\n", swapped); + } +} + +void llama_expert_hotstore::maybe_resync(const llama_expert_heatmap & heatmap) { + if (sync_period <= 0 || heatmap.tokens_total <= 0) { + return; + } + if (heatmap.tokens_total / sync_period > last_sync_tokens / sync_period) { + resync_top_s(heatmap); + } +} + +int llama_expert_hotstore::slot_of(int layer_idx, int expert_id) const { + if (layer_idx < 0 || layer_idx >= n_layers || hot_s <= 0) { + return -1; + } + const auto & ste = slot_to_expert[layer_idx]; + for (int p = 0; p < hot_s; p++) { + if (ste[p] == expert_id) { + return p; + } + } + return -1; +} + void llama_expert_hotstore::log() const { LLAMA_LOG("=== Expert hotstore sizing (S=%d) ===\n", hot_s); size_t total = 0; diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index 8873dca176a..075a043f850 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -29,6 +29,13 @@ struct llama_expert_hotstore { }; std::vector entries; + // per-layer index into entries (built once in ctor, entries stable after) + std::vector> entries_by_layer; + + // slot_to_expert[il][p] = expert id held in slot p of layer il, or -1 if empty. + // stable across re-syncs: an expert that stays hot keeps its slot. + std::vector> slot_to_expert; + // keeps the GPU buffer (and its no_alloc context) alive ggml_context_ptr ctx; ggml_backend_buffer_ptr buf; @@ -36,16 +43,31 @@ struct llama_expert_hotstore { // true once the first copy of the top-S experts landed (once per session) bool is_filled = false; + // re-sync cadence in tokens; 0 disables periodic re-sync + int sync_period = 0; + // tokens_total at the last sync (fill or re-sync) for boundary-cross check + int64_t last_sync_tokens = 0; + llama_expert_hotstore(const llama_model * model, int n_layers, - int n_experts, int hot_s); + int n_experts, int hot_s, int sync_period = 0); // allocate the GPU hot store for `hot_s` slots. returns false (and // leaves the store disabled) on failure or shortage of VRAM. bool allocate(ggml_backend_buffer_type_t gpu_buft); // copy the top-S expert slices for every layer into the GPU hot store, - // using the given heatmap for the ranking. no-op if already filled. + // using the given heatmap for the ranking. one-shot (guarded by is_filled). void copy_top_s(const llama_expert_heatmap & heatmap); + // re-sync the hot store to the current heatmap ranking, swapping only + // the experts that changed (stable slots; unchanged experts not re-copied). + void resync_top_s(const llama_expert_heatmap & heatmap); + + // cadence-gated wrapper: re-sync only if tokens_total crossed sync_period. + void maybe_resync(const llama_expert_heatmap & heatmap); + + // returns the GPU slot index holding expert_id in layer il, or -1 if none + int slot_of(int layer_idx, int expert_id) const; + void log() const; }; From a3c442540b6ef3ad9b39d742cccc56ec105da4f9 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 3 Aug 2026 04:30:32 +0300 Subject: [PATCH 13/61] expert hotstore: add sentinel slot for zero-contribution routing --- src/llama-expert-hotstore.cpp | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 07944e0ddc9..ed90746754c 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -70,9 +70,11 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { return false; } - // one hot tensor per model expert tensor, trimmed to hot_s slots + // one hot tensor per model expert tensor, with hot_s expert slots plus + // 1 sentinel slot (index hot_s) that stays zero so cold selections read + // zeros via a valid in-range index (sentinel trick, oldtricks Trick 2). for (auto & e : entries) { - e.dst = ggml_new_tensor_3d(ctx.get(), e.src->type, e.src->ne[0], e.src->ne[1], hot_s); + e.dst = ggml_new_tensor_3d(ctx.get(), e.src->type, e.src->ne[0], e.src->ne[1], hot_s + 1); } // check whether the buffer would fit before committing any VRAM @@ -102,6 +104,11 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { buf = ggml_backend_buffer_ptr(b); ggml_backend_buffer_set_usage(buf.get(), GGML_BACKEND_BUFFER_USAGE_WEIGHTS); + // zero the whole buffer so the sentinel slot (index hot_s) AND every + // not-yet-filled expert slot is zero; copy_top_s/resync_top_s only write + // slots 0..hot_s-1, so slot hot_s stays zero for the lifetime of the store. + ggml_backend_buffer_clear(buf.get(), 0); + return true; } @@ -240,11 +247,11 @@ void llama_expert_hotstore::log() const { LLAMA_LOG(" total bytes/slot across all layers = %zu (%zu MiB)\n", total, total / (1024 * 1024)); if (buf) { - LLAMA_LOG(" GPU hot store allocated: %s, %zu bytes (%zu MiB) for %d slots\n", + LLAMA_LOG(" GPU hot store allocated: %s, %zu bytes (%zu MiB) for %d+1 slots (%d expert + 1 sentinel)\n", ggml_backend_buffer_name(buf.get()), ggml_backend_buffer_get_size(buf.get()), ggml_backend_buffer_get_size(buf.get()) / (1024 * 1024), - hot_s); + hot_s, hot_s); } else if (hot_s > 0) { LLAMA_LOG(" hot store DISABLED (%d slots requested)\n", hot_s); } From 90409027634dfd8074ed15038205345efae51867 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 3 Aug 2026 04:31:49 +0300 Subject: [PATCH 14/61] expert hotstore: per-layer LUTs and masks for in-graph routing --- src/llama-expert-hotstore.cpp | 59 ++++++++++++++++++++++++++++++++++- src/llama-expert-hotstore.h | 25 +++++++++++++++ 2 files changed, 83 insertions(+), 1 deletion(-) diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index ed90746754c..ac02750d201 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -59,8 +59,9 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { } // a no_alloc context just for the hot tensor metadata + // (also holds the per-layer LUT/mask tensors created below) ggml_init_params params = { - /*.mem_size =*/ ggml_tensor_overhead() * entries.size(), + /*.mem_size =*/ ggml_tensor_overhead() * (entries.size() + 4 * n_layers), /*.mem_buffer =*/ nullptr, /*.no_alloc =*/ true, }; @@ -77,6 +78,16 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { e.dst = ggml_new_tensor_3d(ctx.get(), e.src->type, e.src->ne[0], e.src->ne[1], hot_s + 1); } + // per-layer LUTs and masks for in-graph routing (oldtricks Trick 4). + // hot_lut/cold_lut are i32, hot_mask/cold_mask are f32, all [n_experts]. + luts.assign(n_layers, layer_lut{}); + for (int il = 0; il < n_layers; il++) { + luts[il].hot_lut = ggml_new_tensor_1d(ctx.get(), GGML_TYPE_I32, n_experts); + luts[il].cold_lut = ggml_new_tensor_1d(ctx.get(), GGML_TYPE_I32, n_experts); + luts[il].hot_mask = ggml_new_tensor_1d(ctx.get(), GGML_TYPE_F32, n_experts); + luts[il].cold_mask = ggml_new_tensor_1d(ctx.get(), GGML_TYPE_F32, n_experts); + } + // check whether the buffer would fit before committing any VRAM const size_t need = ggml_backend_alloc_ctx_tensors_from_buft_size(ctx.get(), gpu_buft); if (need == 0) { @@ -142,6 +153,7 @@ void llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { last_sync_tokens = heatmap.tokens_total; is_filled = true; + update_luts(); LLAMA_LOG("=== Expert hot store: top-S experts copied to GPU ===\n"); } @@ -211,6 +223,7 @@ void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { last_sync_tokens = heatmap.tokens_total; if (swapped > 0) { + update_luts(); LLAMA_LOG("=== Expert hot store: re-sync swapped %d expert slots ===\n", swapped); } } @@ -237,6 +250,50 @@ int llama_expert_hotstore::slot_of(int layer_idx, int expert_id) const { return -1; } +void llama_expert_hotstore::update_luts() { + if (hot_s <= 0 || luts.empty()) { + return; + } + + std::vector hot_lut_h(n_experts); + std::vector cold_lut_h(n_experts); + std::vector hot_mask_h(n_experts); + std::vector cold_mask_h(n_experts); + + for (int il = 0; il < n_layers; il++) { + const auto & ste = slot_to_expert[il]; + + // defaults: everyone cold + for (int e = 0; e < n_experts; e++) { + hot_lut_h[e] = hot_s; // sentinel slot (zero) + cold_lut_h[e] = e; // real expert id + hot_mask_h[e] = 0.0f; + cold_mask_h[e] = 1.0f; + } + + // residents override + for (int p = 0; p < hot_s; p++) { + const int e = ste[p]; + if (e < 0) { + continue; + } + hot_lut_h[e] = p; // its slot index + cold_lut_h[e] = 0; // dummy expert 0 + hot_mask_h[e] = 1.0f; + cold_mask_h[e] = 0.0f; + } + + const size_t bytes_i32 = n_experts * sizeof(int32_t); + const size_t bytes_f32 = n_experts * sizeof(float); + ggml_backend_tensor_set(luts[il].hot_lut, hot_lut_h.data(), 0, bytes_i32); + ggml_backend_tensor_set(luts[il].cold_lut, cold_lut_h.data(), 0, bytes_i32); + ggml_backend_tensor_set(luts[il].hot_mask, hot_mask_h.data(), 0, bytes_f32); + ggml_backend_tensor_set(luts[il].cold_mask, cold_mask_h.data(), 0, bytes_f32); + } + + luts_version++; +} + void llama_expert_hotstore::log() const { LLAMA_LOG("=== Expert hotstore sizing (S=%d) ===\n", hot_s); size_t total = 0; diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index 075a043f850..209a672162d 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -36,6 +36,26 @@ struct llama_expert_hotstore { // stable across re-syncs: an expert that stays hot keeps its slot. std::vector> slot_to_expert; + // per-layer LUTs and masks for in-graph routing (oldtricks Trick 4). + // hot_lut[e] = slot index [0..hot_s-1] if e is hot, or hot_s (sentinel) if cold. + // cold_lut[e] = e if e is cold, or 0 (dummy expert) if hot. + // hot_mask[e] = 1.0f if e is hot, else 0.0f. + // cold_mask[e] = 1.0f if e is cold, else 0.0f. + // All allocated in the same ctx/buf as the hot tensors (GPU); populated + // in resync_top_s and H2D only on ubatches where a slot swapped (see + // luts_version). Read by build_moe_ffn_tiered via ggml_get_rows. + struct layer_lut { + ggml_tensor * hot_lut = nullptr; // i32[n_experts] + ggml_tensor * cold_lut = nullptr; // i32[n_experts] + ggml_tensor * hot_mask = nullptr; // f32[n_experts] + ggml_tensor * cold_mask = nullptr; // f32[n_experts] + }; + std::vector luts; // size n_layers + + // bumped on every resync that swapped >0 slots; build_moe_ffn_tiered + // compares to its own cached counter to know whether H2D is needed. + int64_t luts_version = 0; + // keeps the GPU buffer (and its no_alloc context) alive ggml_context_ptr ctx; ggml_backend_buffer_ptr buf; @@ -69,5 +89,10 @@ struct llama_expert_hotstore { // returns the GPU slot index holding expert_id in layer il, or -1 if none int slot_of(int layer_idx, int expert_id) const; + // rebuild hot_lut/cold_lut/hot_mask/cold_mask from slot_to_expert for + // every layer and H2D-copy them into the GPU tensors. bumps luts_version. + // called from copy_top_s (initial fill) and resync_top_s (swaps). + void update_luts(); + void log() const; }; From 3c9616b3a6a505546b11505b2b12b81756f91023 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 3 Aug 2026 21:00:44 +0300 Subject: [PATCH 15/61] expert tier: hook GPU hot store into graph with MUL_MAT_ID_COLD cold op - add MUL_MAT_ID_COLD op that skips hot experts on the CPU cold path - port cold kernel from original llama-wackMall - add llama-expert-tier register/build hook (hot LUT remap + cold op + scale + add) - slim layer_lut to {hot_lut, cold_mask}, drop cold_lut/hot_mask - add static-plant and hit-rate diagnostics --- ggml/include/ggml.h | 12 +++ ggml/src/ggml-cpu/ggml-cpu.c | 173 ++++++++++++++++++++++++++++++++++ ggml/src/ggml.c | 37 +++++++- src/CMakeLists.txt | 1 + src/llama-context.cpp | 3 + src/llama-expert-hotstore.cpp | 85 ++++++++++++++--- src/llama-expert-hotstore.h | 30 +++--- src/llama-expert-tier.cpp | 119 +++++++++++++++++++++++ src/llama-expert-tier.h | 56 +++++++++++ src/llama-graph.cpp | 9 ++ 10 files changed, 496 insertions(+), 29 deletions(-) create mode 100644 src/llama-expert-tier.cpp create mode 100644 src/llama-expert-tier.h diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h index 35f0c44ec42..b64b080c8da 100644 --- a/ggml/include/ggml.h +++ b/ggml/include/ggml.h @@ -590,6 +590,8 @@ extern "C" { GGML_OP_GLU, + GGML_OP_MUL_MAT_ID_COLD, + GGML_OP_COUNT, }; @@ -1448,6 +1450,16 @@ extern "C" { struct ggml_tensor * b, struct ggml_tensor * ids); + // mul_mat_id restricted to cold experts only: computes only rows whose + // expert is marked 1 in cold_mask (i32 [n_expert], 1 = cold); hot slots + // are zeroed in the result + GGML_API struct ggml_tensor * ggml_mul_mat_id_cold( + struct ggml_context * ctx, + struct ggml_tensor * as, + struct ggml_tensor * b, + struct ggml_tensor * ids, + struct ggml_tensor * cold_mask); + // A: m columns, n rows, // B: p columns, n rows, // result is m columns, p rows diff --git a/ggml/src/ggml-cpu/ggml-cpu.c b/ggml/src/ggml-cpu/ggml-cpu.c index 491316f7491..0aa4189344f 100644 --- a/ggml/src/ggml-cpu/ggml-cpu.c +++ b/ggml/src/ggml-cpu/ggml-cpu.c @@ -1460,6 +1460,10 @@ struct mmid_row_mapping { int32_t i2; }; +static void ggml_compute_forward_mul_mat_id_cold( + const struct ggml_compute_params * params, + struct ggml_tensor * dst); + static void ggml_compute_forward_mul_mat_id_one_chunk( struct ggml_tensor * dst, const struct ggml_tensor * src0, @@ -1841,6 +1845,10 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm { ggml_compute_forward_mul_mat_id(params, tensor); } break; + case GGML_OP_MUL_MAT_ID_COLD: + { + ggml_compute_forward_mul_mat_id_cold(params, tensor); + } break; case GGML_OP_OUT_PROD: { ggml_compute_forward_out_prod(params, tensor); @@ -2217,6 +2225,169 @@ static void set_numa_thread_affinity(int thread_n) { UNUSED(thread_n); } static void clear_numa_thread_affinity(void) {} #endif +static void ggml_compute_forward_mul_mat_id_cold( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + const struct ggml_tensor * src0 = dst->src[0]; + const struct ggml_tensor * src1 = dst->src[1]; + const struct ggml_tensor * ids = dst->src[2]; + const struct ggml_tensor * mask = dst->src[3]; + + const int32_t * cold_mask = (const int32_t *) mask->data; + + GGML_TENSOR_BINARY_OP_LOCALS + + const int ith = params->ith; + const int nth = params->nth; + + const enum ggml_type type = src0->type; + + const bool src1_cont = ggml_is_contiguous(src1); + + enum ggml_type const vec_dot_type = type_traits_cpu[type].vec_dot_type; + ggml_from_float_t const from_float = type_traits_cpu[vec_dot_type].from_float; + + GGML_ASSERT(nb00 == ggml_type_size(type)); + GGML_ASSERT(nb10 == ggml_type_size(src1->type)); + + GGML_ASSERT(nb0 == sizeof(float)); + GGML_ASSERT(nb0 <= nb1); + GGML_ASSERT(nb1 <= nb2); + GGML_ASSERT(nb2 <= nb3); + + const int n_ids = ids->ne[0]; + const int n_as = ne02; + + void * wdata_cur = params->wdata; + + if (src1->type != vec_dot_type) { + incr_ptr_aligned(&wdata_cur, ggml_row_size(vec_dot_type, ggml_nelements(src1)), sizeof(int64_t)); + } + + int64_t * matrix_row_counts = + incr_ptr_aligned(&wdata_cur, n_as*sizeof(int64_t), sizeof(int64_t)); + + struct mmid_row_mapping * matrix_rows = + incr_ptr_aligned(&wdata_cur, n_as*ids->ne[0]*ids->ne[1]*sizeof(struct mmid_row_mapping), sizeof(int64_t)); + + char (*atomic_current_chunk)[CACHE_LINE_SIZE] = + incr_ptr_aligned(&wdata_cur, CACHE_LINE_SIZE * n_as, CACHE_LINE_SIZE); + + GGML_ASSERT(params->wsize >= (size_t)((char *) wdata_cur - (char *) params->wdata)); + + if (src1->type != vec_dot_type) { + char * wdata = params->wdata; + + const size_t nbw0 = ggml_type_size(vec_dot_type); + const size_t nbw1 = ggml_row_size(vec_dot_type, ne10); + const size_t nbw2 = nbw1*ne11; + const size_t nbw3 = nbw2*ne12; + + assert(params->wsize >= ne13*nbw3); + GGML_ASSERT(src1->type == GGML_TYPE_F32); + + for (int64_t i13 = 0; i13 < ne13; ++i13) { + for (int64_t i12 = 0; i12 < ne12; ++i12) { + for (int64_t i11 = 0; i11 < ne11; ++i11) { + size_t bs = ggml_blck_size(vec_dot_type); + int64_t ne10_block_start = (ith * ne10/bs) / nth; + int64_t ne10_block_end = ((ith + 1) * ne10/bs) / nth; + from_float((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11 + ne10_block_start*bs*nb10), + (void *) (wdata + i13*nbw3 + i12*nbw2 + i11*nbw1 + ne10_block_start*nbw0), + (ne10_block_end - ne10_block_start) * bs); + } + } + } + } + + if (ith == 0) { + memset(dst->data, 0, ggml_nbytes(dst)); + memset(matrix_row_counts, 0, n_as*sizeof(int64_t)); + + for (int64_t iid1 = 0; iid1 < ids->ne[1]; ++iid1) { + for (int id = 0; id < n_ids; ++id) { + const int32_t i02 = *(const int32_t *) ((const char *) ids->data + iid1*ids->nb[1] + id*ids->nb[0]); + + assert(i02 >= 0 && i02 < n_as); + + if (cold_mask[i02] == 0) { + continue; + } + + MMID_MATRIX_ROW(i02, matrix_row_counts[i02]) = (struct mmid_row_mapping) {id, iid1}; + matrix_row_counts[i02] += 1; + } + } + } + + for (int cur_a = ith; cur_a < n_as; cur_a += nth) { + atomic_int * current_chunk_ctr = (atomic_int *)(atomic_current_chunk + cur_a); + *current_chunk_ctr = nth; + } + + ggml_barrier(params->threadpool); + + for (int cur_a = 0; cur_a < n_as; ++cur_a) { + const int64_t cne1 = matrix_row_counts[cur_a]; + if (cne1 == 0) { + continue; + } + + const char * src0_cur = (const char *) src0->data + cur_a * nb02; + const void * wdata = (src1->type == vec_dot_type) ? src1->data : params->wdata; + const size_t row_size = ggml_row_size(vec_dot_type, ne10); + + const int64_t nr0 = ne01; + const int64_t nr1 = cne1; + + int chunk_size = 16; + if (nr0 == 1 || nr1 == 1) { + chunk_size = 64; + } + + const bool disable_chunking = ggml_is_numa(); + + int64_t nchunk0 = (nr0 + chunk_size - 1) / chunk_size; + int64_t nchunk1 = (nr1 + chunk_size - 1) / chunk_size; + + if (nchunk0 * nchunk1 < nth * 4 || disable_chunking) { + nchunk0 = nr0 > nr1 ? nth : 1; + nchunk1 = nr0 > nr1 ? 1 : nth; + } + + const int64_t dr0 = (nr0 + nchunk0 - 1) / nchunk0; + const int64_t dr1 = (nr1 + nchunk1 - 1) / nchunk1; + + int current_chunk = ith; + + atomic_int * current_chunk_ctr = (atomic_int *)(atomic_current_chunk + cur_a); + + while (current_chunk < nchunk0 * nchunk1) { + const int64_t ith0 = current_chunk % nchunk0; + const int64_t ith1 = current_chunk / nchunk0; + + const int64_t ir0_start = dr0 * ith0; + const int64_t ir0_end = MIN(ir0_start + dr0, nr0); + + const int64_t ir1_start = dr1 * ith1; + const int64_t ir1_end = MIN(ir1_start + dr1, nr1); + + ggml_compute_forward_mul_mat_id_one_chunk( + dst, src0, src1, ids, cur_a, + ir0_start, ir0_end, ir1_start, ir1_end, + src0_cur, matrix_rows, row_size, src1_cont, wdata + ); + + if (nth >= nchunk0 * nchunk1) { + break; + } + + current_chunk = atomic_fetch_add_explicit(current_chunk_ctr, 1, memory_order_relaxed); + } + } +} + static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads) { int n_tasks = 0; @@ -2329,6 +2500,7 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads) { case GGML_OP_CONCAT: case GGML_OP_MUL_MAT: case GGML_OP_MUL_MAT_ID: + case GGML_OP_MUL_MAT_ID_COLD: case GGML_OP_OUT_PROD: { n_tasks = n_threads; @@ -2854,6 +3026,7 @@ struct ggml_cplan ggml_graph_plan( } } break; case GGML_OP_MUL_MAT_ID: + case GGML_OP_MUL_MAT_ID_COLD: { cur = 0; const struct ggml_tensor * src0 = node->src[0]; diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c index 59191c663eb..b7c6b87a902 100644 --- a/ggml/src/ggml.c +++ b/ggml/src/ggml.c @@ -1098,9 +1098,10 @@ static const char * GGML_OP_NAME[GGML_OP_COUNT] = { "OPT_STEP_SGD", "GLU", + "MUL_MAT_ID_COLD", }; -static_assert(GGML_OP_COUNT == 101, "GGML_OP_COUNT != 101"); +static_assert(GGML_OP_COUNT == 102, "GGML_OP_COUNT != 102"); static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = { "none", @@ -1213,9 +1214,10 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = { "sgd(x)", "glu(x)", + "mul_mat_id_cold(x,x,x,x)", }; -static_assert(GGML_OP_COUNT == 101, "GGML_OP_COUNT != 101"); +static_assert(GGML_OP_COUNT == 102, "GGML_OP_COUNT != 102"); static_assert(GGML_OP_POOL_COUNT == 2, "GGML_OP_POOL_COUNT != 2"); @@ -3352,6 +3354,37 @@ struct ggml_tensor * ggml_mul_mat_id( return result; } +// ggml_mul_mat_id_cold + +struct ggml_tensor * ggml_mul_mat_id_cold( + struct ggml_context * ctx, + struct ggml_tensor * as, + struct ggml_tensor * b, + struct ggml_tensor * ids, + struct ggml_tensor * cold_mask) { + GGML_ASSERT(!ggml_is_transposed(as)); + GGML_ASSERT(ids->type == GGML_TYPE_I32); + // cold_mask treated as integer for 0/non-zero check; f32 (0.0f, 1.0f) is fine + GGML_ASSERT(cold_mask->ne[0] == as->ne[2]); + GGML_ASSERT(as->ne[3] == 1); + GGML_ASSERT(b->ne[3] == 1); + GGML_ASSERT(ids->ne[2] == 1 && ids->ne[3] == 1); + GGML_ASSERT(ids->ne[1] == b->ne[2]); + GGML_ASSERT(as->ne[0] == b->ne[0]); + GGML_ASSERT(ids->ne[0] % b->ne[1] == 0); + + const int64_t ne[4] = { as->ne[1], ids->ne[0], b->ne[2], 1 }; + struct ggml_tensor * result = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, ne); + + result->op = GGML_OP_MUL_MAT_ID_COLD; + result->src[0] = as; + result->src[1] = b; + result->src[2] = ids; + result->src[3] = cold_mask; + + return result; +} + // ggml_out_prod static inline bool ggml_can_out_prod(const struct ggml_tensor * t0, const struct ggml_tensor * t1) { diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt index 5039af7bec2..9b404be5ca3 100644 --- a/src/CMakeLists.txt +++ b/src/CMakeLists.txt @@ -19,6 +19,7 @@ add_library(llama llama-cparams.cpp llama-expert-heatmap.cpp llama-expert-hotstore.cpp + llama-expert-tier.cpp llama-grammar.cpp llama-graph.cpp llama-hparams.cpp diff --git a/src/llama-context.cpp b/src/llama-context.cpp index bb02f68d4e4..fcdb47e654c 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -1418,6 +1418,9 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll expert_hotstore->copy_top_s(*expert_heatmap); } else { expert_hotstore->maybe_resync(*expert_heatmap); + if (getenv("LLAMA_EXPERT_HITRATE")) { + expert_hotstore->log_hit_rate(res->moe_sel_experts); + } } } diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index ac02750d201..30dc0bacfa9 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -1,5 +1,6 @@ #include "llama-expert-hotstore.h" #include "llama-expert-heatmap.h" +#include "llama-expert-tier.h" #include "llama-impl.h" #include "llama-model.h" @@ -79,12 +80,10 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { } // per-layer LUTs and masks for in-graph routing (oldtricks Trick 4). - // hot_lut/cold_lut are i32, hot_mask/cold_mask are f32, all [n_experts]. + // hot_lut i32, cold_mask f32, both [n_experts]. luts.assign(n_layers, layer_lut{}); for (int il = 0; il < n_layers; il++) { luts[il].hot_lut = ggml_new_tensor_1d(ctx.get(), GGML_TYPE_I32, n_experts); - luts[il].cold_lut = ggml_new_tensor_1d(ctx.get(), GGML_TYPE_I32, n_experts); - luts[il].hot_mask = ggml_new_tensor_1d(ctx.get(), GGML_TYPE_F32, n_experts); luts[il].cold_mask = ggml_new_tensor_1d(ctx.get(), GGML_TYPE_F32, n_experts); } @@ -120,11 +119,22 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { // slots 0..hot_s-1, so slot hot_s stays zero for the lifetime of the store. ggml_backend_buffer_clear(buf.get(), 0); + // register each expert weight tensor with the tier hook so build_lora_mm_id + // can find its GPU hot tensor and per-layer LUTs. + for (const auto & e : entries) { + const auto & L = luts[e.layer_idx]; + llama_expert_tier_register(e.src, e.dst, L.hot_lut, L.cold_mask); + } + return true; } +llama_expert_hotstore::~llama_expert_hotstore() { + llama_expert_tier_clear(); +} + void llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { - if (is_filled || hot_s <= 0 || entries.empty()) { + if (is_filled || hot_s <= 0 || entries.empty() || !buf) { return; } @@ -157,8 +167,34 @@ void llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { LLAMA_LOG("=== Expert hot store: top-S experts copied to GPU ===\n"); } +void llama_expert_hotstore::plant_static() { + if (is_filled || hot_s <= 0 || entries.empty() || !buf) { + return; + } + + // plant experts 0..hot_s-1 into slots 0..hot_s-1, one shot, no heatmap + for (int il = 0; il < n_layers; il++) { + auto & ste = slot_to_expert[il]; + for (int p = 0; p < hot_s && p < n_experts; p++) { + ste[p] = p; + } + for (entry * e : entries_by_layer[il]) { + const size_t slot = ggml_nbytes(e->src) / (size_t) e->src->ne[2]; + const char * src = e->src->data ? (const char *) ggml_get_data(e->src) : nullptr; + if (!src) continue; + for (int p = 0; p < hot_s && p < n_experts; p++) { + ggml_backend_tensor_set(e->dst, src + (size_t) p * slot, (size_t) p * slot, slot); + } + } + } + + is_filled = true; + update_luts(); + LLAMA_LOG("=== Expert hot store: STATIC plant of %d experts per layer ===\n", hot_s); +} + void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { - if (!is_filled || hot_s <= 0) { + if (!is_filled || hot_s <= 0 || !buf) { return; } @@ -251,13 +287,11 @@ int llama_expert_hotstore::slot_of(int layer_idx, int expert_id) const { } void llama_expert_hotstore::update_luts() { - if (hot_s <= 0 || luts.empty()) { + if (hot_s <= 0 || luts.empty() || !buf) { return; } std::vector hot_lut_h(n_experts); - std::vector cold_lut_h(n_experts); - std::vector hot_mask_h(n_experts); std::vector cold_mask_h(n_experts); for (int il = 0; il < n_layers; il++) { @@ -266,8 +300,6 @@ void llama_expert_hotstore::update_luts() { // defaults: everyone cold for (int e = 0; e < n_experts; e++) { hot_lut_h[e] = hot_s; // sentinel slot (zero) - cold_lut_h[e] = e; // real expert id - hot_mask_h[e] = 0.0f; cold_mask_h[e] = 1.0f; } @@ -278,22 +310,47 @@ void llama_expert_hotstore::update_luts() { continue; } hot_lut_h[e] = p; // its slot index - cold_lut_h[e] = 0; // dummy expert 0 - hot_mask_h[e] = 1.0f; cold_mask_h[e] = 0.0f; } const size_t bytes_i32 = n_experts * sizeof(int32_t); const size_t bytes_f32 = n_experts * sizeof(float); ggml_backend_tensor_set(luts[il].hot_lut, hot_lut_h.data(), 0, bytes_i32); - ggml_backend_tensor_set(luts[il].cold_lut, cold_lut_h.data(), 0, bytes_i32); - ggml_backend_tensor_set(luts[il].hot_mask, hot_mask_h.data(), 0, bytes_f32); ggml_backend_tensor_set(luts[il].cold_mask, cold_mask_h.data(), 0, bytes_f32); } luts_version++; } +void llama_expert_hotstore::log_hit_rate(const std::vector> & moe_sel) { + if (moe_sel.empty() || !is_filled) { + return; + } + size_t hits = 0, total = 0; + for (const auto & kv : moe_sel) { + const int il = kv.first; + const ggml_tensor * t = kv.second; + if (!t || !t->data || t->type != GGML_TYPE_I32) { + continue; + } + const size_t n = ggml_nelements(t); + std::vector ids(n); + ggml_backend_tensor_get(t, ids.data(), 0, n * sizeof(int32_t)); + for (size_t i = 0; i < n; i++) { + const int32_t id = ids[i]; + if (id >= 0 && id < n_experts) { + total++; + if (slot_of(il, id) >= 0) { + hits++; + } + } + } + } + if (total > 0) { + LLAMA_LOG("=== expert hot hit rate: %zu/%zu = %.1f%% ===\n", hits, total, 100.0f * (float) hits / (float) total); + } +} + void llama_expert_hotstore::log() const { LLAMA_LOG("=== Expert hotstore sizing (S=%d) ===\n", hot_s); size_t total = 0; diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index 209a672162d..9ec67c601b3 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -36,18 +36,11 @@ struct llama_expert_hotstore { // stable across re-syncs: an expert that stays hot keeps its slot. std::vector> slot_to_expert; - // per-layer LUTs and masks for in-graph routing (oldtricks Trick 4). + // per-layer LUT and mask for in-graph routing. // hot_lut[e] = slot index [0..hot_s-1] if e is hot, or hot_s (sentinel) if cold. - // cold_lut[e] = e if e is cold, or 0 (dummy expert) if hot. - // hot_mask[e] = 1.0f if e is hot, else 0.0f. - // cold_mask[e] = 1.0f if e is cold, else 0.0f. - // All allocated in the same ctx/buf as the hot tensors (GPU); populated - // in resync_top_s and H2D only on ubatches where a slot swapped (see - // luts_version). Read by build_moe_ffn_tiered via ggml_get_rows. + // cold_mask[e] = 1.0f if e is cold, else 0.0f (passed to mul_mat_id_cold). struct layer_lut { ggml_tensor * hot_lut = nullptr; // i32[n_experts] - ggml_tensor * cold_lut = nullptr; // i32[n_experts] - ggml_tensor * hot_mask = nullptr; // f32[n_experts] ggml_tensor * cold_mask = nullptr; // f32[n_experts] }; std::vector luts; // size n_layers @@ -68,8 +61,10 @@ struct llama_expert_hotstore { // tokens_total at the last sync (fill or re-sync) for boundary-cross check int64_t last_sync_tokens = 0; - llama_expert_hotstore(const llama_model * model, int n_layers, - int n_experts, int hot_s, int sync_period = 0); +llama_expert_hotstore(const llama_model * model, int n_layers, + int n_experts, int hot_s, int sync_period = 0); + + ~llama_expert_hotstore(); // allocate the GPU hot store for `hot_s` slots. returns false (and // leaves the store disabled) on failure or shortage of VRAM. @@ -79,6 +74,11 @@ struct llama_expert_hotstore { // using the given heatmap for the ranking. one-shot (guarded by is_filled). void copy_top_s(const llama_expert_heatmap & heatmap); + // static plant: fill slots 0..hot_s-1 with experts 0..hot_s-1 per layer, + // build LUTs/masks accordingly, no heatmap, no resync. Diagnostic only: + // isolates the dual-path graph from the heat/dynamic-copy path. + void plant_static(); + // re-sync the hot store to the current heatmap ranking, swapping only // the experts that changed (stable slots; unchanged experts not re-copied). void resync_top_s(const llama_expert_heatmap & heatmap); @@ -89,8 +89,12 @@ struct llama_expert_hotstore { // returns the GPU slot index holding expert_id in layer il, or -1 if none int slot_of(int layer_idx, int expert_id) const; - // rebuild hot_lut/cold_lut/hot_mask/cold_mask from slot_to_expert for - // every layer and H2D-copy them into the GPU tensors. bumps luts_version. + // diagnostic: count how many router-selected expert ids hit a hot slot. + // reads the selected_experts tensors (call after synchronize). + void log_hit_rate(const std::vector> & moe_sel); + + // rebuild hot_lut/cold_mask from slot_to_expert for every layer + // and H2D-copy them into the GPU tensors. bumps luts_version. // called from copy_top_s (initial fill) and resync_top_s (swaps). void update_luts(); diff --git a/src/llama-expert-tier.cpp b/src/llama-expert-tier.cpp new file mode 100644 index 00000000000..e499d0ccbbf --- /dev/null +++ b/src/llama-expert-tier.cpp @@ -0,0 +1,119 @@ +#include "llama-expert-tier.h" + +#include +#include + +namespace { + struct tier_entry { + ggml_tensor * dst_hot; // [ne0, ne1, hot_s + 1] + ggml_tensor * hot_lut; // i32 [n_experts] + ggml_tensor * cold_mask; // f32 [n_experts] (read as int zero-check by cold op) + }; + + std::mutex g_mtx; + std::unordered_map g_table; +} + +void llama_expert_tier_register(ggml_tensor * src, + ggml_tensor * dst_hot, + ggml_tensor * hot_lut, + ggml_tensor * cold_mask) { + std::lock_guard lk(g_mtx); + g_table[src] = {dst_hot, hot_lut, cold_mask}; +} + +void llama_expert_tier_clear() { + std::lock_guard lk(g_mtx); + g_table.clear(); +} + +bool llama_expert_tier_has(ggml_tensor * w) { + std::lock_guard lk(g_mtx); + return g_table.find(w) != g_table.end(); +} + +// Remap real expert ids through a LUT and produce a 2d [n_expert_used, +// n_tokens] i32 tensor usable as `ids` for ggml_mul_mat_id. +// +// Flatten the per-token ids to 1D, run a stock 1D ggml_get_rows against the +// per-expert LUT (reshape to [1, n_experts] so each row picked is 1 scalar), +// then reshape the [1, n_eu*n_tok] result back to 2D. Avoids ggml_repeat_4d +// + view_2d strides that the CUDA mul_mat_id kernel mishandles on multi-token +// ubatches. `ggml_cont` defends against argsort views that may not be +// contiguous across the n_expert_used * n_tokens layout. +static ggml_tensor * remap_ids(ggml_context * ctx, + ggml_tensor * lut, + ggml_tensor * selected, + int n_experts, + int n_expert_used, + int n_tokens) { + ggml_tensor * lut_rows = ggml_reshape_2d(ctx, lut, 1, n_experts); // [1, n_experts] + // selected (argsort_top_k view) may be non-contiguous; cont first, then reshape + ggml_tensor * flat_ids = ggml_reshape_1d(ctx, + ggml_cont(ctx, selected), n_expert_used * n_tokens); // [n_eu*n_tok] i32 + ggml_tensor * r = ggml_get_rows(ctx, lut_rows, flat_ids); // [1, n_eu*n_tok, 1, 1] i32 + return ggml_reshape_2d(ctx, r, n_expert_used, n_tokens); // [n_eu, n_tok] +} + +// Build a per-(expert_used, token) mask f32 [1, n_expert_used, n_tokens, 1] +// (broadcastable against a mul_mat_id output of shape [out, n_eu, n_tok, 1]). +// Same flatten pattern as remap_ids. +static ggml_tensor * remap_mask(ggml_context * ctx, + ggml_tensor * mask, + ggml_tensor * selected, + int n_experts, + int n_expert_used, + int n_tokens) { + ggml_tensor * mask_rows = ggml_reshape_2d(ctx, mask, 1, n_experts); // [1, n_experts] f32 + ggml_tensor * flat_ids = ggml_reshape_1d(ctx, + ggml_cont(ctx, selected), n_expert_used * n_tokens); // [n_eu*n_tok] i32 + ggml_tensor * r = ggml_get_rows(ctx, mask_rows, flat_ids); // [1, n_eu*n_tok, 1, 1] f32 + return ggml_reshape_3d(ctx, r, 1, n_expert_used, n_tokens); // [1, n_eu, n_tok] +} + +ggml_tensor * llama_expert_tier_build(ggml_context * ctx, + ggml_tensor * w, + ggml_tensor * cur, + ggml_tensor * ids, + ggml_tensor * w_s) { + // BUG-3E3: CUDA MMQ mul_mat_id compaction assumes distinct expert ids per token; + // our sentinel duplicates OOB there. Decode (n_tokens==1) is safe via mmvq. + if (cur->ne[2] > 1) return nullptr; + + tier_entry ent; + { + std::lock_guard lk(g_mtx); + auto it = g_table.find(w); + if (it == g_table.end()) { + return nullptr; + } + ent = it->second; + } + + const int n_experts = (int) w->ne[2]; + const int n_expert_used = (int) ids->ne[0]; + const int n_tokens = (int) cur->ne[2]; + + // hot path: GPU tier tensor. Remap real expert ids through hot_lut + // -> hot slot indices (sentinel S for cold experts = zero contribution). + ggml_tensor * ids_hot = remap_ids(ctx, ent.hot_lut, ids, n_experts, n_expert_used, n_tokens); + ggml_tensor * hot = ggml_mul_mat_id(ctx, ent.dst_hot, cur, ids_hot); + + // cold path: dedicated CPU op that computes ONLY cold-selected experts. + // ent.cold_mask is f32 [n_experts] with 1.0f = cold; the op treats it + // as integer-zero-check (0.0f = hot = skip, non-zero = cold = compute). + ggml_tensor * cold = ggml_mul_mat_id_cold(ctx, w, cur, ids, ent.cold_mask); + + // per-expert quant scale on both paths + if (w_s) { + ggml_tensor * s_rows = ggml_reshape_2d(ctx, w_s, 1, n_experts); + ggml_tensor * flat_ids = ggml_reshape_1d(ctx, + ggml_cont(ctx, ids), n_expert_used * n_tokens); + ggml_tensor * s = ggml_get_rows(ctx, s_rows, flat_ids); + s = ggml_reshape_3d(ctx, s, 1, n_expert_used, n_tokens); + hot = ggml_mul(ctx, hot, s); + cold = ggml_mul(ctx, cold, s); + } + + return ggml_add(ctx, hot, cold); +} \ No newline at end of file diff --git a/src/llama-expert-tier.h b/src/llama-expert-tier.h new file mode 100644 index 00000000000..ac402e54ae1 --- /dev/null +++ b/src/llama-expert-tier.h @@ -0,0 +1,56 @@ +#pragma once + +#include "ggml.h" + +// Expert tier hook: drop-in replacement for ggml_mul_mat_id on expert weight +// tensors that have a registered GPU hot store. Pure stock ggml ops, no +// custom kernel, no per-model code. +// +// How it works (matches oldtricks.md Trick 4 sentinel + LUT design): +// registered src w (full expert tensor on CPU/mmap) -> {dst_hot (S+1 slots +// on GPU), per-layer LUTs and masks}. When build_lora_mm_id is called with +// w, the hook remaps real expert ids through hot_lut/cold_lut, runs two +// mul_mat_id ops (hot on GPU slots, cold on the full CPU tensor), scales +// and masks each per routed expert, sums them. Result is byte-identical +// in shape to a stock mul_mat_id output and feeds straight back into the +// caller's downstream ops (bias add, activation, second build_lora_mm_id +// call for down, routing-weight mul). +// +// GPU sentinel slot (index S of dst_hot) is zero-filled once at allocate +// time and never written again, so cold experts routed to it return zero. +// On the CPU side, we cannot grow a mmap'd expert tensor, so hot experts +// are routed to a real dummy (expert 0) on the cold path; the dummy's +// contribution is zeroed by cold_mask before the result is used. +// +// Masking happens at every mul_mat_id output, BEFORE bias add and BEFORE +// activation. That lifts the no-biases constraint: at a hot slot the cold +// mask zeroes the dummy contribution pre-activation, so the bias and +// activation run on the correct real value for that slot. + +// register one expert weight tensor -> its GPU hot tensor and per-layer LUTs. +// Called by llama_expert_hotstore::allocate() after creating dst_hot and +// the LUT/mask tensors. Multiple entries per layer share the same luts[i]. +void llama_expert_tier_register(ggml_tensor * src, + ggml_tensor * dst_hot, + ggml_tensor * hot_lut, + ggml_tensor * cold_mask); + +// drop the entire table (called by hotstore destructor) +void llama_expert_tier_clear(); + +// cheap check: is `w` registered? (used so callers can short-circuit lora) +bool llama_expert_tier_has(ggml_tensor * w); + +// drop-in hook called from build_lora_mm_id. Returns the combined +// hot+cold output tensor when `w` is registered; returns nullptr to let the +// caller fall back to stock ggml_mul_mat_id. +// ctx : graph context (ctx0 of the calling llm_graph_context) +// w : expert weight tensor, ne = [in, out, n_experts], 3d, ne[3]==1 +// cur : activation, ne = [in, 1, n_tokens], 3d +// ids : selected_experts, ne = [n_expert_used, n_tokens], 2d i32, REAL ids +// w_s : per-expert quant scale, ne = [n_experts], f32; nullptr if none +ggml_tensor * llama_expert_tier_build(ggml_context * ctx, + ggml_tensor * w, + ggml_tensor * cur, + ggml_tensor * ids, + ggml_tensor * w_s); \ No newline at end of file diff --git a/src/llama-graph.cpp b/src/llama-graph.cpp index b4a599baba7..988508fb9f3 100644 --- a/src/llama-graph.cpp +++ b/src/llama-graph.cpp @@ -1,5 +1,6 @@ #include "llama-graph.h" +#include "llama-expert-tier.h" #include "llama-impl.h" #include "llama-model.h" #include "llama-batch.h" @@ -1485,6 +1486,14 @@ ggml_tensor * llm_graph_context::build_lora_mm_id( ggml_tensor * cur, // ggml_tensor * b ggml_tensor * ids, ggml_tensor * w_s) const { + // expert tier hook: if `w` has a registered GPU hot store, build the + // dual-path (hot GPU slots + cold CPU experts) result and return it. + // Skip when loras are active so build_lora_mm_id's lora loop still runs. + if (loras->empty()) { + if (auto * r = llama_expert_tier_build(ctx0, w, cur, ids, w_s)) { + return r; + } + } ggml_tensor * res = ggml_mul_mat_id(ctx0, w, cur, ids); if (w_s) { From d1cdf1b355715061d78e61b0486776ef01cc8288 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 3 Aug 2026 22:20:02 +0300 Subject: [PATCH 16/61] ggml-cpu: move MUL_MAT_ID_COLD kernel to its own file - add ggml-cpu-mul-mat-id-cold.c with the cold-expert kernel - add shared header for mmid helpers (mmid_row_mapping, incr_ptr_aligned, one_chunk) - drop static on the two helpers now shared with stock mul_mat_id --- ggml/src/ggml-cpu/CMakeLists.txt | 2 + ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c | 192 +++++++++++++++++++ ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h | 46 +++++ ggml/src/ggml-cpu/ggml-cpu.c | 178 +---------------- 4 files changed, 243 insertions(+), 175 deletions(-) create mode 100644 ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c create mode 100644 ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h diff --git a/ggml/src/ggml-cpu/CMakeLists.txt b/ggml/src/ggml-cpu/CMakeLists.txt index 836bae4d05a..afb2043ebc0 100644 --- a/ggml/src/ggml-cpu/CMakeLists.txt +++ b/ggml/src/ggml-cpu/CMakeLists.txt @@ -29,6 +29,8 @@ function(ggml_add_cpu_backend_variant_impl tag_name) list (APPEND GGML_CPU_SOURCES ggml-cpu/ggml-cpu.c ggml-cpu/ggml-cpu.cpp + ggml-cpu/ggml-cpu-mul-mat-id-cold.c + ggml-cpu/ggml-cpu-mul-mat-id-cold.h ggml-cpu/repack.cpp ggml-cpu/repack.h ggml-cpu/hbm.cpp diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c new file mode 100644 index 00000000000..e8d685904f3 --- /dev/null +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c @@ -0,0 +1,192 @@ +#define _CRT_SECURE_NO_DEPRECATE // Disables "unsafe" warnings on Windows +#define _USE_MATH_DEFINES // For M_PI on MSVC + +#include "ggml.h" +#include "ggml-impl.h" +#include "ggml-cpu-impl.h" +#include "ggml-cpu.h" +#include "ops.h" +#include "ggml-cpu-mul-mat-id-cold.h" + +#if defined(_MSC_VER) || defined(__MINGW32__) +#include // using malloc.h with MSC/MINGW +#elif !defined(__FreeBSD__) && !defined(__NetBSD__) && !defined(__OpenBSD__) +#include +#endif + +#include +#include +#include +#include +#include +#include + +#if defined(_WIN32) +#include +#else +#include +#endif + +void ggml_compute_forward_mul_mat_id_cold( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + const struct ggml_tensor * src0 = dst->src[0]; + const struct ggml_tensor * src1 = dst->src[1]; + const struct ggml_tensor * ids = dst->src[2]; + const struct ggml_tensor * mask = dst->src[3]; + + const int32_t * cold_mask = (const int32_t *) mask->data; + + GGML_TENSOR_BINARY_OP_LOCALS + + const int ith = params->ith; + const int nth = params->nth; + + const enum ggml_type type = src0->type; + + const bool src1_cont = ggml_is_contiguous(src1); + + const struct ggml_type_traits_cpu * ttype = ggml_get_type_traits_cpu(type); + enum ggml_type const vec_dot_type = ttype->vec_dot_type; + ggml_from_float_t const from_float = ggml_get_type_traits_cpu(vec_dot_type)->from_float; + + GGML_ASSERT(nb00 == ggml_type_size(type)); + GGML_ASSERT(nb10 == ggml_type_size(src1->type)); + + GGML_ASSERT(nb0 == sizeof(float)); + GGML_ASSERT(nb0 <= nb1); + GGML_ASSERT(nb1 <= nb2); + GGML_ASSERT(nb2 <= nb3); + + const int n_ids = ids->ne[0]; + const int n_as = ne02; + + void * wdata_cur = params->wdata; + + if (src1->type != vec_dot_type) { + incr_ptr_aligned(&wdata_cur, ggml_row_size(vec_dot_type, ggml_nelements(src1)), sizeof(int64_t)); + } + + int64_t * matrix_row_counts = + incr_ptr_aligned(&wdata_cur, n_as*sizeof(int64_t), sizeof(int64_t)); + + struct mmid_row_mapping * matrix_rows = + incr_ptr_aligned(&wdata_cur, n_as*ids->ne[0]*ids->ne[1]*sizeof(struct mmid_row_mapping), sizeof(int64_t)); + + char (*atomic_current_chunk)[CACHE_LINE_SIZE] = + incr_ptr_aligned(&wdata_cur, CACHE_LINE_SIZE * n_as, CACHE_LINE_SIZE); + + GGML_ASSERT(params->wsize >= (size_t)((char *) wdata_cur - (char *) params->wdata)); + + if (src1->type != vec_dot_type) { + char * wdata = params->wdata; + + const size_t nbw0 = ggml_type_size(vec_dot_type); + const size_t nbw1 = ggml_row_size(vec_dot_type, ne10); + const size_t nbw2 = nbw1*ne11; + const size_t nbw3 = nbw2*ne12; + + assert(params->wsize >= ne13*nbw3); + GGML_ASSERT(src1->type == GGML_TYPE_F32); + + for (int64_t i13 = 0; i13 < ne13; ++i13) { + for (int64_t i12 = 0; i12 < ne12; ++i12) { + for (int64_t i11 = 0; i11 < ne11; ++i11) { + size_t bs = ggml_blck_size(vec_dot_type); + int64_t ne10_block_start = (ith * ne10/bs) / nth; + int64_t ne10_block_end = ((ith + 1) * ne10/bs) / nth; + from_float((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11 + ne10_block_start*bs*nb10), + (void *) (wdata + i13*nbw3 + i12*nbw2 + i11*nbw1 + ne10_block_start*nbw0), + (ne10_block_end - ne10_block_start) * bs); + } + } + } + } + + if (ith == 0) { + memset(dst->data, 0, ggml_nbytes(dst)); + memset(matrix_row_counts, 0, n_as*sizeof(int64_t)); + + for (int64_t iid1 = 0; iid1 < ids->ne[1]; ++iid1) { + for (int id = 0; id < n_ids; ++id) { + const int32_t i02 = *(const int32_t *) ((const char *) ids->data + iid1*ids->nb[1] + id*ids->nb[0]); + + assert(i02 >= 0 && i02 < n_as); + + if (cold_mask[i02] == 0) { + continue; + } + + MMID_MATRIX_ROW(i02, matrix_row_counts[i02]) = (struct mmid_row_mapping) {id, iid1}; + matrix_row_counts[i02] += 1; + } + } + } + + for (int cur_a = ith; cur_a < n_as; cur_a += nth) { + atomic_int * current_chunk_ctr = (atomic_int *)(atomic_current_chunk + cur_a); + *current_chunk_ctr = nth; + } + + ggml_barrier(params->threadpool); + + for (int cur_a = 0; cur_a < n_as; ++cur_a) { + const int64_t cne1 = matrix_row_counts[cur_a]; + if (cne1 == 0) { + continue; + } + + const char * src0_cur = (const char *) src0->data + cur_a * nb02; + const void * wdata = (src1->type == vec_dot_type) ? src1->data : params->wdata; + const size_t row_size = ggml_row_size(vec_dot_type, ne10); + + const int64_t nr0 = ne01; + const int64_t nr1 = cne1; + + int chunk_size = 16; + if (nr0 == 1 || nr1 == 1) { + chunk_size = 64; + } + + const bool disable_chunking = ggml_is_numa(); + + int64_t nchunk0 = (nr0 + chunk_size - 1) / chunk_size; + int64_t nchunk1 = (nr1 + chunk_size - 1) / chunk_size; + + if (nchunk0 * nchunk1 < nth * 4 || disable_chunking) { + nchunk0 = nr0 > nr1 ? nth : 1; + nchunk1 = nr0 > nr1 ? 1 : nth; + } + + const int64_t dr0 = (nr0 + nchunk0 - 1) / nchunk0; + const int64_t dr1 = (nr1 + nchunk1 - 1) / nchunk1; + + int current_chunk = ith; + + atomic_int * current_chunk_ctr = (atomic_int *)(atomic_current_chunk + cur_a); + + while (current_chunk < nchunk0 * nchunk1) { + const int64_t ith0 = current_chunk % nchunk0; + const int64_t ith1 = current_chunk / nchunk0; + + const int64_t ir0_start = dr0 * ith0; + const int64_t ir0_end = MIN(ir0_start + dr0, nr0); + + const int64_t ir1_start = dr1 * ith1; + const int64_t ir1_end = MIN(ir1_start + dr1, nr1); + + ggml_compute_forward_mul_mat_id_one_chunk( + dst, src0, src1, ids, cur_a, + ir0_start, ir0_end, ir1_start, ir1_end, + src0_cur, matrix_rows, row_size, src1_cont, wdata + ); + + if (nth >= nchunk0 * nchunk1) { + break; + } + + current_chunk = atomic_fetch_add_explicit(current_chunk_ctr, 1, memory_order_relaxed); + } + } +} \ No newline at end of file diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h new file mode 100644 index 00000000000..e0e2ab242b6 --- /dev/null +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h @@ -0,0 +1,46 @@ +#pragma once + +// Shared helpers between ggml-cpu.c (stock GGML_OP_MUL_MAT_ID) and the +// dedicated MUL_MAT_ID_COLD kernel in ggml-cpu-mul-mat-id-cold.cpp. + +#include "ggml-cpu-impl.h" + +#include +#include + +#define MMID_MATRIX_ROW(row_id, i1) matrix_rows[(row_id)*ids->ne[0]*ids->ne[1] + (i1)] + +struct mmid_row_mapping { + int32_t i1; + int32_t i2; +}; + +#ifdef __cplusplus +extern "C" { +#endif + +void * incr_ptr_aligned(void ** p, size_t size, size_t align); + +void ggml_compute_forward_mul_mat_id_one_chunk( + struct ggml_tensor * dst, + const struct ggml_tensor * src0, + const struct ggml_tensor * src1, + const struct ggml_tensor * ids, + const int64_t cur_a, + const int64_t ir0_start, + const int64_t ir0_end, + const int64_t ir1_start, + const int64_t ir1_end, + const char * src0_cur, + const struct mmid_row_mapping * matrix_rows, + const size_t row_size, + const bool src1_cont, + const void * wdata); + +void ggml_compute_forward_mul_mat_id_cold( + const struct ggml_compute_params * params, + struct ggml_tensor * dst); + +#ifdef __cplusplus +} +#endif \ No newline at end of file diff --git a/ggml/src/ggml-cpu/ggml-cpu.c b/ggml/src/ggml-cpu/ggml-cpu.c index 0aa4189344f..5052be07b2b 100644 --- a/ggml/src/ggml-cpu/ggml-cpu.c +++ b/ggml/src/ggml-cpu/ggml-cpu.c @@ -5,6 +5,7 @@ #include "ggml-backend.h" #include "traits.h" #include "ggml-cpu-impl.h" +#include "ggml-cpu-mul-mat-id-cold.h" #include "ggml-impl.h" #include "quants.h" #include "ggml-threading.h" @@ -1453,18 +1454,7 @@ UseGgmlGemm2:; // ggml_compute_forward_mul_mat_id -#define MMID_MATRIX_ROW(row_id, i1) matrix_rows[(row_id)*ids->ne[0]*ids->ne[1] + (i1)] - -struct mmid_row_mapping { - int32_t i1; - int32_t i2; -}; - -static void ggml_compute_forward_mul_mat_id_cold( - const struct ggml_compute_params * params, - struct ggml_tensor * dst); - -static void ggml_compute_forward_mul_mat_id_one_chunk( +void ggml_compute_forward_mul_mat_id_one_chunk( struct ggml_tensor * dst, const struct ggml_tensor * src0, const struct ggml_tensor * src1, @@ -1527,7 +1517,7 @@ static void ggml_compute_forward_mul_mat_id_one_chunk( } } -static void * incr_ptr_aligned(void ** p, size_t size, size_t align) { +void * incr_ptr_aligned(void ** p, size_t size, size_t align) { void * ptr = *p; ptr = (void *) GGML_PAD((uintptr_t) ptr, align); @@ -2225,168 +2215,6 @@ static void set_numa_thread_affinity(int thread_n) { UNUSED(thread_n); } static void clear_numa_thread_affinity(void) {} #endif -static void ggml_compute_forward_mul_mat_id_cold( - const struct ggml_compute_params * params, - struct ggml_tensor * dst) { - - const struct ggml_tensor * src0 = dst->src[0]; - const struct ggml_tensor * src1 = dst->src[1]; - const struct ggml_tensor * ids = dst->src[2]; - const struct ggml_tensor * mask = dst->src[3]; - - const int32_t * cold_mask = (const int32_t *) mask->data; - - GGML_TENSOR_BINARY_OP_LOCALS - - const int ith = params->ith; - const int nth = params->nth; - - const enum ggml_type type = src0->type; - - const bool src1_cont = ggml_is_contiguous(src1); - - enum ggml_type const vec_dot_type = type_traits_cpu[type].vec_dot_type; - ggml_from_float_t const from_float = type_traits_cpu[vec_dot_type].from_float; - - GGML_ASSERT(nb00 == ggml_type_size(type)); - GGML_ASSERT(nb10 == ggml_type_size(src1->type)); - - GGML_ASSERT(nb0 == sizeof(float)); - GGML_ASSERT(nb0 <= nb1); - GGML_ASSERT(nb1 <= nb2); - GGML_ASSERT(nb2 <= nb3); - - const int n_ids = ids->ne[0]; - const int n_as = ne02; - - void * wdata_cur = params->wdata; - - if (src1->type != vec_dot_type) { - incr_ptr_aligned(&wdata_cur, ggml_row_size(vec_dot_type, ggml_nelements(src1)), sizeof(int64_t)); - } - - int64_t * matrix_row_counts = - incr_ptr_aligned(&wdata_cur, n_as*sizeof(int64_t), sizeof(int64_t)); - - struct mmid_row_mapping * matrix_rows = - incr_ptr_aligned(&wdata_cur, n_as*ids->ne[0]*ids->ne[1]*sizeof(struct mmid_row_mapping), sizeof(int64_t)); - - char (*atomic_current_chunk)[CACHE_LINE_SIZE] = - incr_ptr_aligned(&wdata_cur, CACHE_LINE_SIZE * n_as, CACHE_LINE_SIZE); - - GGML_ASSERT(params->wsize >= (size_t)((char *) wdata_cur - (char *) params->wdata)); - - if (src1->type != vec_dot_type) { - char * wdata = params->wdata; - - const size_t nbw0 = ggml_type_size(vec_dot_type); - const size_t nbw1 = ggml_row_size(vec_dot_type, ne10); - const size_t nbw2 = nbw1*ne11; - const size_t nbw3 = nbw2*ne12; - - assert(params->wsize >= ne13*nbw3); - GGML_ASSERT(src1->type == GGML_TYPE_F32); - - for (int64_t i13 = 0; i13 < ne13; ++i13) { - for (int64_t i12 = 0; i12 < ne12; ++i12) { - for (int64_t i11 = 0; i11 < ne11; ++i11) { - size_t bs = ggml_blck_size(vec_dot_type); - int64_t ne10_block_start = (ith * ne10/bs) / nth; - int64_t ne10_block_end = ((ith + 1) * ne10/bs) / nth; - from_float((float *)((char *) src1->data + i13*nb13 + i12*nb12 + i11*nb11 + ne10_block_start*bs*nb10), - (void *) (wdata + i13*nbw3 + i12*nbw2 + i11*nbw1 + ne10_block_start*nbw0), - (ne10_block_end - ne10_block_start) * bs); - } - } - } - } - - if (ith == 0) { - memset(dst->data, 0, ggml_nbytes(dst)); - memset(matrix_row_counts, 0, n_as*sizeof(int64_t)); - - for (int64_t iid1 = 0; iid1 < ids->ne[1]; ++iid1) { - for (int id = 0; id < n_ids; ++id) { - const int32_t i02 = *(const int32_t *) ((const char *) ids->data + iid1*ids->nb[1] + id*ids->nb[0]); - - assert(i02 >= 0 && i02 < n_as); - - if (cold_mask[i02] == 0) { - continue; - } - - MMID_MATRIX_ROW(i02, matrix_row_counts[i02]) = (struct mmid_row_mapping) {id, iid1}; - matrix_row_counts[i02] += 1; - } - } - } - - for (int cur_a = ith; cur_a < n_as; cur_a += nth) { - atomic_int * current_chunk_ctr = (atomic_int *)(atomic_current_chunk + cur_a); - *current_chunk_ctr = nth; - } - - ggml_barrier(params->threadpool); - - for (int cur_a = 0; cur_a < n_as; ++cur_a) { - const int64_t cne1 = matrix_row_counts[cur_a]; - if (cne1 == 0) { - continue; - } - - const char * src0_cur = (const char *) src0->data + cur_a * nb02; - const void * wdata = (src1->type == vec_dot_type) ? src1->data : params->wdata; - const size_t row_size = ggml_row_size(vec_dot_type, ne10); - - const int64_t nr0 = ne01; - const int64_t nr1 = cne1; - - int chunk_size = 16; - if (nr0 == 1 || nr1 == 1) { - chunk_size = 64; - } - - const bool disable_chunking = ggml_is_numa(); - - int64_t nchunk0 = (nr0 + chunk_size - 1) / chunk_size; - int64_t nchunk1 = (nr1 + chunk_size - 1) / chunk_size; - - if (nchunk0 * nchunk1 < nth * 4 || disable_chunking) { - nchunk0 = nr0 > nr1 ? nth : 1; - nchunk1 = nr0 > nr1 ? 1 : nth; - } - - const int64_t dr0 = (nr0 + nchunk0 - 1) / nchunk0; - const int64_t dr1 = (nr1 + nchunk1 - 1) / nchunk1; - - int current_chunk = ith; - - atomic_int * current_chunk_ctr = (atomic_int *)(atomic_current_chunk + cur_a); - - while (current_chunk < nchunk0 * nchunk1) { - const int64_t ith0 = current_chunk % nchunk0; - const int64_t ith1 = current_chunk / nchunk0; - - const int64_t ir0_start = dr0 * ith0; - const int64_t ir0_end = MIN(ir0_start + dr0, nr0); - - const int64_t ir1_start = dr1 * ith1; - const int64_t ir1_end = MIN(ir1_start + dr1, nr1); - - ggml_compute_forward_mul_mat_id_one_chunk( - dst, src0, src1, ids, cur_a, - ir0_start, ir0_end, ir1_start, ir1_end, - src0_cur, matrix_rows, row_size, src1_cont, wdata - ); - - if (nth >= nchunk0 * nchunk1) { - break; - } - - current_chunk = atomic_fetch_add_explicit(current_chunk_ctr, 1, memory_order_relaxed); - } - } -} static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads) { int n_tasks = 0; From 8687ee2b66af5d36b670babf52ed95f3f4bb5223 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 3 Aug 2026 23:03:59 +0300 Subject: [PATCH 17/61] common: added -las short flag for expert hot store slots (alias of --expert-hot-s) --- common/arg.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/common/arg.cpp b/common/arg.cpp index 9043983ac70..66446f66ef3 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2694,7 +2694,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex } ).set_env("LLAMA_ARG_EXPERT_HEAT_LOG_PERIOD")); add_opt(common_arg( - {"--expert-hot-s"}, "N", + {"-las", "--expert-hot-s"}, "N", "number of top expert slots for GPU hot store (default: 0 = disabled)", [](common_params & params, int value) { params.expert_hot_s = value; From 5c5020d8067f7ba0a6092e7e4e63bd6fb548c96e Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Tue, 4 Aug 2026 00:34:12 +0300 Subject: [PATCH 18/61] expert hotstore: freeze swapping during multi-slot batches --- src/llama-context.cpp | 2 +- src/llama-expert-hotstore.cpp | 5 +++-- src/llama-expert-hotstore.h | 5 +++-- 3 files changed, 7 insertions(+), 5 deletions(-) diff --git a/src/llama-context.cpp b/src/llama-context.cpp index fcdb47e654c..c1ee1d2885a 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -1417,7 +1417,7 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll if (!expert_hotstore->is_filled) { expert_hotstore->copy_top_s(*expert_heatmap); } else { - expert_hotstore->maybe_resync(*expert_heatmap); + expert_hotstore->maybe_resync(*expert_heatmap, ubatch.n_tokens > 1); if (getenv("LLAMA_EXPERT_HITRATE")) { expert_hotstore->log_hit_rate(res->moe_sel_experts); } diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 30dc0bacfa9..5030ca01052 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -264,8 +264,9 @@ void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { } } -void llama_expert_hotstore::maybe_resync(const llama_expert_heatmap & heatmap) { - if (sync_period <= 0 || heatmap.tokens_total <= 0) { +void llama_expert_hotstore::maybe_resync(const llama_expert_heatmap & heatmap, bool multi_slot) { + // n_tokens>1 (multi-slot) freezes the hot store: no swapping during the batch + if (multi_slot || sync_period <= 0 || heatmap.tokens_total <= 0) { return; } if (heatmap.tokens_total / sync_period > last_sync_tokens / sync_period) { diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index 9ec67c601b3..fc5a633d0d9 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -83,8 +83,9 @@ llama_expert_hotstore(const llama_model * model, int n_layers, // the experts that changed (stable slots; unchanged experts not re-copied). void resync_top_s(const llama_expert_heatmap & heatmap); - // cadence-gated wrapper: re-sync only if tokens_total crossed sync_period. - void maybe_resync(const llama_expert_heatmap & heatmap); + // cadence-gated wrapper: re-sync only if tokens_total crossed sync_period; + // multi_slot freezes the hot store (static slots, no swapping) + void maybe_resync(const llama_expert_heatmap & heatmap, bool multi_slot); // returns the GPU slot index holding expert_id in layer il, or -1 if none int slot_of(int layer_idx, int expert_id) const; From 1a850ec17a4fc16aba9530af4a2afa5b242c6f26 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Tue, 4 Aug 2026 07:14:54 +0300 Subject: [PATCH 19/61] llama : gate expert hot store to CUDA only, with force override Expert hot store is only correct on CUDA; on Vulkan it produces corrupt output. Restrict the tiered hot store to devices named CUDA*, and add LLAMA_EXPERT_HOT_FORCE=1 to override for testing. --- src/llama-context.cpp | 17 +++++++++++++++-- 1 file changed, 15 insertions(+), 2 deletions(-) diff --git a/src/llama-context.cpp b/src/llama-context.cpp index c1ee1d2885a..cbe9fec0622 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -478,11 +478,24 @@ llama_context::llama_context( expert_hotstore = std::make_unique( &model, hparams.n_layer(), hparams.n_expert, params.expert_hot_s, sync_period); + // the GPU hot store is only supported on CUDA. On CPU it buys nothing + // and on Vulkan it corrupts output (see manuallog section 12). + // LLAMA_EXPERT_HOT_FORCE=1 overrides the guard (testing/emergency only). + const bool force = getenv("LLAMA_EXPERT_HOT_FORCE") != nullptr; for (auto & backend : backends) { - if (ggml_backend_dev_type(ggml_backend_get_device(backend.get())) != GGML_BACKEND_DEVICE_TYPE_CPU) { - expert_hotstore->allocate(ggml_backend_get_default_buffer_type(backend.get())); + ggml_backend_dev_t dev = ggml_backend_get_device(backend.get()); + if (ggml_backend_dev_type(dev) == GGML_BACKEND_DEVICE_TYPE_CPU) { + continue; + } + const char * name = ggml_backend_dev_name(dev); + const bool is_cuda = name != nullptr && strncmp(name, "CUDA", 4) == 0; + if (!force && !is_cuda) { + LLAMA_LOG_WARN("%s: expert hot store skipped: backend %s is not CUDA (only CUDA is supported)\n", + __func__, name ? name : "?"); break; } + expert_hotstore->allocate(ggml_backend_get_default_buffer_type(backend.get())); + break; } expert_hotstore->log(); } From b18c4266c7c56c8e61add2559a5fc314df79b745 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Tue, 4 Aug 2026 09:12:37 +0300 Subject: [PATCH 20/61] common: expert hot store manual slots activate --cmoe --expert-hot-s N>0 auto-pushes the MoE-to-CPU tensor override (with a warning) so hot store slot copies always read host pointers. --- common/arg.cpp | 17 +++++++++++++++++ 1 file changed, 17 insertions(+) diff --git a/common/arg.cpp b/common/arg.cpp index e5e88a2d95c..98e36075719 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -35,6 +35,7 @@ #include #include #include +#include #include // for hardware_concurrency #include @@ -903,6 +904,22 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context params.cors_origins = "localhost"; } + // manual hot store slots need all MoE weights in the CPU (host pointers); + // auto-activate -cmoe unless the user already did (or wants autofit slots) + if (params.expert_hot_s > 0) { + bool has_cmoe = false; + for (const auto & o : params.tensor_buft_overrides) { + if (o.pattern != nullptr && strcmp(o.pattern, LLM_FFN_EXPS_REGEX) == 0) { + has_cmoe = true; + break; + } + } + if (!has_cmoe) { + params.tensor_buft_overrides.push_back(llm_ffn_exps_cpu_override()); + LOG_WRN("manually selecting --expert-hot-s slots activates --cmoe (all MoE weights kept in the CPU)\n"); + } + } + // pad tensor_buft_overrides for llama_params_fit: const size_t ntbo = llama_max_tensor_buft_overrides(); while (params.tensor_buft_overrides.size() < ntbo) { From f201ef52a92ff2772571abd6d05a3ef90e5dacb7 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Tue, 4 Aug 2026 10:14:54 +0300 Subject: [PATCH 21/61] common: autofit expert hot store slots via --expert-hot-s -1 fit.cpp now reports how many MoE expert bytes the fitted placement leaves on GPU; common.cpp maps that to S slots and forces all experts to CPU so the hot store copy reads host pointers. S=0 disables the tier. --- common/common.cpp | 20 +++++++++++++++++++- common/fit.cpp | 28 +++++++++++++++++++++++++--- common/fit.h | 3 ++- 3 files changed, 46 insertions(+), 5 deletions(-) diff --git a/common/common.cpp b/common/common.cpp index 64c2387fd49..f678282d341 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1239,12 +1239,30 @@ common_init_result::common_init_result(common_params & params, bool model_only) if (params.fit_params) { COM_TRC("%s", "fitting params to device memory ...\n"); COM_TRC("%s", "(for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on)\n"); + int n_expert_hot_s = params.expert_hot_s; + int * p_expert_hot_s = params.expert_hot_s == -1 ? &n_expert_hot_s : nullptr; common_fit_params(params.model.path.c_str(), &mparams, &cparams, params.tensor_split, params.tensor_buft_overrides.data(), params.fit_params_target.data(), params.fit_params_min_ctx, - params.verbosity >= LOG_LEVEL_DEBUG ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_ERROR); + params.verbosity >= LOG_LEVEL_DEBUG ? GGML_LOG_LEVEL_DEBUG : GGML_LOG_LEVEL_ERROR, + p_expert_hot_s); + if (params.expert_hot_s == -1) { + // -1 = autofit slots from what the fit leaves on GPU; send all experts + // to CPU so the hot store copy reads host pointers (<=> -cmoe). + params.expert_hot_s = n_expert_hot_s > 0 ? n_expert_hot_s : 0; + cparams.expert_hot_s = params.expert_hot_s; + if (params.expert_hot_s > 0) { + for (auto & o : params.tensor_buft_overrides) { + if (o.pattern == nullptr) { + o.buft = ggml_backend_cpu_buffer_type(); + o.pattern = LLM_FFN_EXPS_REGEX; + break; + } + } + } + } } llama_model * model = llama_model_load_from_file(params.model.path.c_str(), mparams); diff --git a/common/fit.cpp b/common/fit.cpp index c82d066ad44..42c4bb2f6d9 100644 --- a/common/fit.cpp +++ b/common/fit.cpp @@ -175,7 +175,7 @@ common_device_memory_data_vec common_get_device_memory_data( static void common_params_fit_impl( const char * path_model, struct llama_model_params * mparams, struct llama_context_params * cparams, float * tensor_split, struct llama_model_tensor_buft_override * tensor_buft_overrides, - size_t * margins_s, uint32_t n_ctx_min, enum ggml_log_level log_level) { + size_t * margins_s, uint32_t n_ctx_min, enum ggml_log_level log_level, int * n_expert_hot_s) { if (mparams->split_mode == LLAMA_SPLIT_MODE_TENSOR) { throw common_params_fit_exception("llama_params_fit is not implemented for SPLIT_MODE_TENSOR, abort"); } @@ -225,6 +225,8 @@ static void common_params_fit_impl( int64_t sum_projected_free = 0; int64_t sum_projected_used = 0; int64_t sum_projected_model = 0; + int64_t total_moe_bytes = 0; // MoE expert tensor bytes (for slot autofit) + int64_t dense_model_gpu = 0; // dense-only model bytes on GPU (for slot autofit) std::vector projected_free_per_device; projected_free_per_device.reserve(nd); @@ -538,6 +540,8 @@ static void common_params_fit_impl( for (size_t id = 0; id < nd; id++) { global_surplus_cpu_moe += dmds_cpu_moe[id].free; global_surplus_cpu_moe -= int64_t(dmds_cpu_moe[id].mb.total()) + margins[id]; + total_moe_bytes += int64_t(dmds_full[id].mb.model) - int64_t(dmds_cpu_moe[id].mb.model); + dense_model_gpu += int64_t(dmds_cpu_moe[id].mb.model); } if (global_surplus_cpu_moe > 0) { @@ -638,6 +642,10 @@ static void common_params_fit_impl( } if (hp_nex == 0 || global_surplus_cpu_moe <= 0) { set_ngl_tensor_split_tbo(ngl_per_device, overflow_bufts, *mparams); + if (n_expert_hot_s) { + // all MoE stays on CPU (no surplus), so no GPU hot slots fit + *n_expert_hot_s = 0; + } return; } @@ -783,6 +791,19 @@ static void common_params_fit_impl( } set_ngl_tensor_split_tbo(ngl_per_device, overflow_bufts, *mparams); + + // autofit the expert hot store slots: the fit already chose how many MoE + // tensors go back on GPU; S = experts-per-layer that fit leaves on GPU. + if (n_expert_hot_s && total_moe_bytes > 0) { + const dmds_t dmds_final = common_get_device_memory_data_impl( + path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level); + int64_t final_gpu_model = 0; + for (size_t id = 0; id < nd; id++) { + final_gpu_model += dmds_final[id].mb.model; + } + const int64_t moe_on_gpu = final_gpu_model - dense_model_gpu; + *n_expert_hot_s = moe_on_gpu > 0 ? (int) (int64_t(hp_nex) * moe_on_gpu / total_moe_bytes) : 0; + } } enum common_params_fit_status common_fit_params( @@ -793,11 +814,12 @@ enum common_params_fit_status common_fit_params( llama_model_tensor_buft_override * tensor_buft_overrides, size_t * margins, uint32_t n_ctx_min, - ggml_log_level log_level) { + ggml_log_level log_level, + int * n_expert_hot_s) { const int64_t t0_us = llama_time_us(); common_params_fit_status status = COMMON_PARAMS_FIT_STATUS_SUCCESS; try { - common_params_fit_impl(path_model, mparams, cparams, tensor_split, tensor_buft_overrides, margins, n_ctx_min, log_level); + common_params_fit_impl(path_model, mparams, cparams, tensor_split, tensor_buft_overrides, margins, n_ctx_min, log_level, n_expert_hot_s); LOG_TRC("%s: successfully fit params to free device memory\n", __func__); } catch (const common_params_fit_exception & e) { LOG_WRN("%s: failed to fit params to free device memory: %s\n", __func__, e.what()); diff --git a/common/fit.h b/common/fit.h index 208fc30694e..95dd153a5d7 100644 --- a/common/fit.h +++ b/common/fit.h @@ -24,7 +24,8 @@ common_params_fit_status common_fit_params( llama_model_tensor_buft_override * tensor_buft_overrides, // writable buffer for overrides, needs at least llama_max_tensor_buft_overrides elements size_t * margins, // margins of memory to leave per device in bytes uint32_t n_ctx_min, // minimum context size to set when trying to reduce memory use - ggml_log_level log_level); // minimum log level to print during fitting, lower levels go to debug log + ggml_log_level log_level, // minimum log level to print during fitting, lower levels go to debug log + int * n_expert_hot_s = nullptr);// out: fitted expert hot store slots, untouched if not applicable // print estimated memory to stdout void common_fit_print( From ca624bc068587b85282578f14d2bf990dd4f736d Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Tue, 4 Aug 2026 10:15:01 +0300 Subject: [PATCH 22/61] expert hot store: hysteresis gate for slot swaps Swap a resident only when a cold expert scores >= hyst x the incumbent (default 1.3). Add --expert-hyst/--expert-dwell, raise decay default to 0.999. Dwell counts real tokens and initial fill is eligible so the first sync can correct drift. --- common/arg.cpp | 16 +++++- common/common.cpp | 2 + common/common.h | 4 +- include/llama.h | 2 + src/llama-context.cpp | 7 ++- src/llama-expert-heatmap.cpp | 7 +++ src/llama-expert-heatmap.h | 1 + src/llama-expert-hotstore.cpp | 99 +++++++++++++++++++++++------------ src/llama-expert-hotstore.h | 10 +++- 9 files changed, 110 insertions(+), 38 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index 98e36075719..76c406a4134 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2720,11 +2720,25 @@ common_params_context common_params_parser_init(common_params & params, llama_ex ).set_env("LLAMA_ARG_EXPERT_HEAT_DECAY")); add_opt(common_arg( {"--expert-heat-log-period"}, "N", - "expert heatmap log interval in updates (default: 100)", + "expert heatmap log interval in updates (default: 100, 0 = off)", [](common_params & params, int value) { params.expert_heat_log_period = value; } ).set_env("LLAMA_ARG_EXPERT_HEAT_LOG_PERIOD")); + add_opt(common_arg( + {"--expert-hyst"}, "F", + "expert hot store hysteresis ratio (default: 1.3, 0 = off)", + [](common_params & params, const std::string & value) { + params.expert_hyst = std::stof(value); + } + ).set_env("LLAMA_ARG_EXPERT_HYST")); + add_opt(common_arg( + {"--expert-dwell"}, "N", + "expert hot store minimum dwell updates before swap (default: 0 = off)", + [](common_params & params, int value) { + params.expert_dwell = value; + } + ).set_env("LLAMA_ARG_EXPERT_DWELL")); add_opt(common_arg( {"-las", "--expert-hot-s"}, "N", "number of top expert slots for GPU hot store (default: 0 = disabled)", diff --git a/common/common.cpp b/common/common.cpp index f678282d341..f7b283618b6 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1699,6 +1699,8 @@ struct llama_context_params common_context_params_to_llama(const common_params & cparams.expert_heat_decay = params.expert_heat_decay; cparams.expert_heat_log_period = params.expert_heat_log_period; cparams.expert_hot_s = params.expert_hot_s; + cparams.expert_hyst = params.expert_hyst; + cparams.expert_dwell = params.expert_dwell; return cparams; } diff --git a/common/common.h b/common/common.h index 6d22ff1d66e..790843c19a3 100644 --- a/common/common.h +++ b/common/common.h @@ -533,9 +533,11 @@ struct common_params { int32_t control_vector_layer_start = -1; // layer range for control vector int32_t control_vector_layer_end = -1; // layer range for control vector - float expert_heat_decay = 0.99f; // multiplicative decay per update + float expert_heat_decay = 0.999f; // multiplicative decay per update int expert_heat_log_period = 0; // log period in updates (0 = off) int expert_hot_s = 0; // top-S expert slots (0 = disabled) + float expert_hyst = 1.3f; // hysteresis ratio: only swap when cold >= hyst x hot + int expert_dwell = 0; // minimum updates a resident slot must keep before a swap bool offline = false; int32_t ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used. diff --git a/include/llama.h b/include/llama.h index e13c1b127b9..90f5eed807b 100644 --- a/include/llama.h +++ b/include/llama.h @@ -406,6 +406,8 @@ extern "C" { float expert_heat_decay; // expert heatmap decay per update int expert_heat_log_period; // expert heatmap log interval int expert_hot_s; // number of top-S expert slots for GPU hot store + float expert_hyst; // hysteresis ratio for slot swaps + int expert_dwell; // min updates a resident slot keeps before swap // a source/target/parent context // can be utilized in various ways, for example by sharing results or llama_memory between 2 contexts diff --git a/src/llama-context.cpp b/src/llama-context.cpp index cbe9fec0622..e3ec7df8aca 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -477,7 +477,8 @@ llama_context::llama_context( const int sync_period = params.expert_heat_log_period > 0 ? params.expert_heat_log_period : 100; expert_hotstore = std::make_unique( &model, hparams.n_layer(), hparams.n_expert, - params.expert_hot_s, sync_period); + params.expert_hot_s, sync_period, + params.expert_hyst, params.expert_dwell); // the GPU hot store is only supported on CUDA. On CPU it buys nothing // and on Vulkan it corrupts output (see manuallog section 12). // LLAMA_EXPERT_HOT_FORCE=1 overrides the guard (testing/emergency only). @@ -3569,9 +3570,11 @@ llama_context_params llama_context_default_params() { /*.kv_unified =*/ false, /*.sampler =*/ nullptr, /*.n_sampler =*/ 0, - /*.expert_heat_decay =*/ 0.99f, + /*.expert_heat_decay =*/ 0.999f, /*.expert_heat_log_period =*/ 0, /*.expert_hot_s =*/ 0, + /*.expert_hyst =*/ 1.3f, + /*.expert_dwell =*/ 0, /*.ctx_other =*/ nullptr, }; diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 8ea9c408e8d..89a05e32c0a 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -99,6 +99,13 @@ void llama_expert_heatmap::log() const { } } +float llama_expert_heatmap::get_score(int layer_idx, int expert_id) const { + if (layer_idx < 0 || layer_idx >= n_layers || expert_id < 0 || expert_id >= n_experts) { + return 0.0f; + } + return heat[layer_idx * n_experts + expert_id]; +} + std::vector llama_expert_heatmap::get_top_s(int layer_idx, int s) const { std::vector result; if (layer_idx < 0 || layer_idx >= n_layers || s <= 0) { diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index 2458d9b07db..d3e4a921c5a 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -26,5 +26,6 @@ struct llama_expert_heatmap { void decay_all(); void log() const; + float get_score(int layer_idx, int expert_id) const; std::vector get_top_s(int layer_idx, int s) const; }; diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 5030ca01052..e48088c7b5c 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -16,12 +16,15 @@ static const std::regex g_re_exps_weight("blk\\.(\\d+)\\.ffn_(up|down|gate|gate_up)_(ch|)exps\\.weight"); llama_expert_hotstore::llama_expert_hotstore( - const llama_model * model, int n_layers, int n_experts, int hot_s, int sync_period) : + const llama_model * model, int n_layers, int n_experts, int hot_s, int sync_period, + float hyst, int dwell) : n_layers(n_layers), n_experts(n_experts), hot_s(hot_s), bytes_per_slot(n_layers, 0), - sync_period(sync_period) { + sync_period(sync_period), + hyst(hyst), + dwell(dwell) { if (n_layers <= 0) { return; } @@ -47,6 +50,7 @@ llama_expert_hotstore::llama_expert_hotstore( if (hot_s > 0) { slot_to_expert.assign(n_layers, std::vector(hot_s, -1)); + dwell_count.assign(n_layers, std::vector(hot_s, 0)); } } @@ -141,8 +145,10 @@ void llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { for (int il = 0; il < n_layers; il++) { const std::vector top = heatmap.get_top_s(il, hot_s); auto & ste = slot_to_expert[il]; + auto & dc = dwell_count[il]; for (int p = 0; p < (int) top.size() && p < hot_s; p++) { ste[p] = top[p]; + dc[p] = dwell; // initial fill is eligible to be corrected next sync } for (entry * e : entries_by_layer[il]) { @@ -198,51 +204,71 @@ void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { return; } + // tokens elapsed since the previous sync, used to age dwell counters + const int64_t elapsed = heatmap.tokens_total - last_sync_tokens; int swapped = 0; for (int il = 0; il < n_layers; il++) { const std::vector top = heatmap.get_top_s(il, hot_s); auto & ste = slot_to_expert[il]; + auto & dc = dwell_count[il]; - // which experts are in the new ranking - std::vector in_new(n_experts, 0); - for (int e : top) { - if (e >= 0 && e < n_experts) { - in_new[e] = 1; + // find a free slot index (guard: any resident displacement must + // clear the hysteresis gate, unless the gate is off) + auto find_slot = [&](int e_cold) -> int { + // fill empty slots first (no gate on fill) + for (int p = 0; p < hot_s; p++) { + if (ste[p] < 0) { + return p; + } } - } - - // evict: free slots whose resident expert fell out of the new top-S - for (int p = 0; p < hot_s; p++) { - if (ste[p] >= 0 && !in_new[ste[p]]) { - ste[p] = -1; + if (hyst <= 0.0f) { + // gate off: displace the weakest resident + int p_worst = -1; + for (int p = 0; p < hot_s; p++) { + if (ste[p] >= 0 && (p_worst < 0 || + heatmap.get_score(il, ste[p]) < heatmap.get_score(il, ste[p_worst]))) { + p_worst = p; + } + } + return p_worst; } - } + // gate on: coldest resident that has dwelled enough AND is beaten + // by hyst * this cold expert + const float s_cold = heatmap.get_score(il, e_cold); + int p_worst = -1; + float worst_score = 1e9f; + for (int p = 0; p < hot_s; p++) { + if (ste[p] < 0) { + continue; + } + if (dc[p] < dwell) { + continue; // incumbent must keep its slot (Trick 6) + } + if (s_cold >= hyst * heatmap.get_score(il, ste[p])) { + const float s_inc = heatmap.get_score(il, ste[p]); + if (s_inc < worst_score) { + worst_score = s_inc; + p_worst = p; + } + } + } + return p_worst; + }; - // collect new experts that are not currently resident + // resident experts -> candidate cold experts, most significant first std::vector resident_set(n_experts, 0); for (int p = 0; p < hot_s; p++) { if (ste[p] >= 0) { resident_set[ste[p]] = 1; } } - std::vector to_place; - for (int e : top) { - if (e >= 0 && e < n_experts && !resident_set[e]) { - to_place.push_back(e); - } - } - - // place each new expert into the first free slot, copy its weights - for (int e : to_place) { - int p = -1; - for (int q = 0; q < hot_s; q++) { - if (ste[q] < 0) { - p = q; - break; - } + for (int e_cold : top) { + if (e_cold < 0 || e_cold >= n_experts || resident_set[e_cold]) { + continue; } + const int p = find_slot(e_cold); if (p < 0) { - break; // no free slot (should not happen: evictions == new) + break; // no slot free or displaceable under the gate } for (entry * ent : entries_by_layer[il]) { const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; @@ -250,11 +276,18 @@ void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { if (!src) { continue; } - ggml_backend_tensor_set(ent->dst, src + (size_t) e * slot, (size_t) p * slot, slot); + ggml_backend_tensor_set(ent->dst, src + (size_t) e_cold * slot, (size_t) p * slot, slot); } - ste[p] = e; + ste[p] = e_cold; + dc[p] = -elapsed; // fresh dwell: aging below brings it to 0 swapped++; } + + for (int p = 0; p < hot_s; p++) { + if (ste[p] >= 0) { + dc[p] += (int) std::max(elapsed, 0); + } + } } last_sync_tokens = heatmap.tokens_total; diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index fc5a633d0d9..2439f83b3f7 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -61,8 +61,16 @@ struct llama_expert_hotstore { // tokens_total at the last sync (fill or re-sync) for boundary-cross check int64_t last_sync_tokens = 0; + // hysteresis gate (Trick 6): a resident slot is only swapped when a cold + // expert scores >= hyst * the incumbent AND the slot has dwelled long enough + float hyst = 0.0f; // 0 = gate off (swap freely) + int dwell = 0; // minimum syncs a resident must keep; 0 = off + // dwell_count[il][p] = syncs since slot p last changed (0 = fresh/empty) + std::vector> dwell_count; + llama_expert_hotstore(const llama_model * model, int n_layers, - int n_experts, int hot_s, int sync_period = 0); + int n_experts, int hot_s, int sync_period = 0, + float hyst = 0.0f, int dwell = 0); ~llama_expert_hotstore(); From 7633d5d6baee54398bbf1a0fab50e9f213fdac0e Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Tue, 4 Aug 2026 12:34:52 +0300 Subject: [PATCH 23/61] common: fix expert flag help text (decay default, autofit -1) --expert-heat-decay help said 0.99 but the default is 0.999; --expert-hot-s help now documents -1 = autofit from free VRAM. --- common/arg.cpp | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index 76c406a4134..8f0235977dc 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2713,7 +2713,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex ).set_env("LLAMA_ARG_N_CPU_MOE")); add_opt(common_arg( {"--expert-heat-decay"}, "F", - "expert heatmap decay rate per update (default: 0.99)", + "expert heatmap decay rate per update (default: 0.999)", [](common_params & params, const std::string & value) { params.expert_heat_decay = std::stof(value); } @@ -2741,7 +2741,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex ).set_env("LLAMA_ARG_EXPERT_DWELL")); add_opt(common_arg( {"-las", "--expert-hot-s"}, "N", - "number of top expert slots for GPU hot store (default: 0 = disabled)", + "-1 = autofit slots from free VRAM, 0 = disabled, N = manual top-N slots", [](common_params & params, int value) { params.expert_hot_s = value; } From 25558aff03e9a160eef1e1e2f82a688c39b548b4 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Tue, 4 Aug 2026 12:50:20 +0300 Subject: [PATCH 24/61] common: rename -las short flag for expert hot store slots to -ehs --- common/arg.cpp | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/common/arg.cpp b/common/arg.cpp index 8f0235977dc..5e733928e4f 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2740,7 +2740,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex } ).set_env("LLAMA_ARG_EXPERT_DWELL")); add_opt(common_arg( - {"-las", "--expert-hot-s"}, "N", + {"-ehs", "--expert-hot-s"}, "N", "-1 = autofit slots from free VRAM, 0 = disabled, N = manual top-N slots", [](common_params & params, int value) { params.expert_hot_s = value; From 0170536d9acad28a97c897254227263ef572d98e Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Tue, 4 Aug 2026 22:46:09 +0300 Subject: [PATCH 25/61] ggml: fix windows build of the cold op (missing stdatomic include) the mul mat id cold kernel used atomics but only included stdatomic on non-windows, breaking the msvc build. include it unconditionally. also update the ggml-rpc op count assert to 102 (was 101) and bump RPC_PROTO_PATCH_VERSION, plus add missing trailing newlines. --- ggml/include/ggml-rpc.h | 4 ++-- ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c | 5 ++--- ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h | 2 +- 3 files changed, 5 insertions(+), 6 deletions(-) diff --git a/ggml/include/ggml-rpc.h b/ggml/include/ggml-rpc.h index 276aea00ea1..a88eab44011 100644 --- a/ggml/include/ggml-rpc.h +++ b/ggml/include/ggml-rpc.h @@ -8,10 +8,10 @@ extern "C" { #define RPC_PROTO_MAJOR_VERSION 5 #define RPC_PROTO_MINOR_VERSION 0 -#define RPC_PROTO_PATCH_VERSION 0 +#define RPC_PROTO_PATCH_VERSION 1 #ifdef __cplusplus -static_assert(GGML_OP_COUNT == 101, "GGML_OP_COUNT has changed - update RPC_PROTO_PATCH_VERSION"); +static_assert(GGML_OP_COUNT == 102, "GGML_OP_COUNT has changed - update RPC_PROTO_PATCH_VERSION"); #endif #define GGML_RPC_MAX_SERVERS 16 diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c index e8d685904f3..993e4cb2116 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c @@ -20,11 +20,10 @@ #include #include #include +#include #if defined(_WIN32) #include -#else -#include #endif void ggml_compute_forward_mul_mat_id_cold( @@ -189,4 +188,4 @@ void ggml_compute_forward_mul_mat_id_cold( current_chunk = atomic_fetch_add_explicit(current_chunk_ctr, 1, memory_order_relaxed); } } -} \ No newline at end of file +} diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h index e0e2ab242b6..3a5aa03d503 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h @@ -43,4 +43,4 @@ void ggml_compute_forward_mul_mat_id_cold( #ifdef __cplusplus } -#endif \ No newline at end of file +#endif From 919168e1e87683fc979debb081c3e9ae8a67b325 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Wed, 5 Aug 2026 00:26:10 +0300 Subject: [PATCH 26/61] ggml: use MSVC Interlocked fallback for atomics in the cold op stdatomic.h is not supported on MSVC cl.exe, so the cold op kernel failed to compile on Windows. match stock ggml-cpu.c and use a volatile LONG + InterlockedExchangeAdd fallback for MSVC, keeping stdatomic.h for clang and other platforms. --- ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c | 28 +++++++++++++++++++- 1 file changed, 27 insertions(+), 1 deletion(-) diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c index 993e4cb2116..571dd859c9c 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c @@ -20,10 +20,36 @@ #include #include #include -#include #if defined(_WIN32) + +#define WIN32_LEAN_AND_MEAN +#ifndef NOMINMAX + #define NOMINMAX +#endif #include + +#endif // _WIN32 + +#if defined(_MSC_VER) && !defined(__clang__) + +typedef volatile LONG atomic_int; + +typedef enum { + memory_order_relaxed, + memory_order_consume, + memory_order_acquire, + memory_order_release, + memory_order_acq_rel, + memory_order_seq_cst +} memory_order; + +static LONG atomic_fetch_add_explicit(atomic_int * ptr, LONG inc, memory_order mo) { + return InterlockedExchangeAdd(ptr, inc); +} + +#else // clang +#include #endif void ggml_compute_forward_mul_mat_id_cold( From e26868db397c56b095a557d2b358fcf1163481c3 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Wed, 5 Aug 2026 02:09:15 +0300 Subject: [PATCH 27/61] Adjusted sentinel autofit to be more conservative though properly accounting for the stable slot --- common/fit.cpp | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/common/fit.cpp b/common/fit.cpp index 42c4bb2f6d9..2fa5338f7e5 100644 --- a/common/fit.cpp +++ b/common/fit.cpp @@ -802,7 +802,8 @@ static void common_params_fit_impl( final_gpu_model += dmds_final[id].mb.model; } const int64_t moe_on_gpu = final_gpu_model - dense_model_gpu; - *n_expert_hot_s = moe_on_gpu > 0 ? (int) (int64_t(hp_nex) * moe_on_gpu / total_moe_bytes) : 0; + const int64_t s = moe_on_gpu > 0 ? int64_t(hp_nex) * moe_on_gpu / total_moe_bytes : 0; + *n_expert_hot_s = s > 1 ? (int) (s - 1) : 0; } } From 08562e59f244b0993a36faa84c398b012fa56512 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Wed, 5 Aug 2026 11:11:00 +0300 Subject: [PATCH 28/61] llama : added -ecf/--expert-cache-force to enable hot store on non-cuda --- common/arg.cpp | 8 ++++++++ common/common.cpp | 1 + common/common.h | 1 + include/llama.h | 1 + src/llama-context.cpp | 20 +++++++++++++------- 5 files changed, 24 insertions(+), 7 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index 3478b122826..608c98f4e45 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2731,6 +2731,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex params.expert_hot_s = value; } ).set_env("LLAMA_ARG_EXPERT_HOT_S")); + add_opt(common_arg( + {"-ecf", "--expert-cache-force"}, + {}, + "enable the expert cache (hot store) on non-CUDA backends (testing/emergency only)", + [](common_params & params, bool value) { + params.expert_cache_force = value; + } + )); GGML_ASSERT(params.n_gpu_layers < 0); // string_format would need to be extended for a default >= 0 add_opt(common_arg( {"-ngl", "--gpu-layers", "--n-gpu-layers"}, "N", diff --git a/common/common.cpp b/common/common.cpp index 4edf76f1463..35b4212e7eb 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1690,6 +1690,7 @@ struct llama_context_params common_context_params_to_llama(const common_params & cparams.expert_hot_s = params.expert_hot_s; cparams.expert_hyst = params.expert_hyst; cparams.expert_dwell = params.expert_dwell; + cparams.expert_cache_force = params.expert_cache_force; return cparams; } diff --git a/common/common.h b/common/common.h index c731020f57c..87b0d9eb573 100644 --- a/common/common.h +++ b/common/common.h @@ -529,6 +529,7 @@ struct common_params { int expert_hot_s = 0; // top-S expert slots (0 = disabled) float expert_hyst = 1.3f; // hysteresis ratio: only swap when cold >= hyst x hot int expert_dwell = 0; // minimum updates a resident slot must keep before a swap + bool expert_cache_force = false; // bypass the CUDA-only hot store guard bool offline = false; int32_t ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used. diff --git a/include/llama.h b/include/llama.h index f0f37ab5d53..6f68a867388 100644 --- a/include/llama.h +++ b/include/llama.h @@ -408,6 +408,7 @@ extern "C" { int expert_hot_s; // number of top-S expert slots for GPU hot store float expert_hyst; // hysteresis ratio for slot swaps int expert_dwell; // min updates a resident slot keeps before swap + bool expert_cache_force; // bypass the CUDA-only hot store guard // a source/target/parent context // can be utilized in various ways, for example by sharing results or llama_memory between 2 contexts diff --git a/src/llama-context.cpp b/src/llama-context.cpp index e3ec7df8aca..7c207a01860 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -481,23 +481,28 @@ llama_context::llama_context( params.expert_hyst, params.expert_dwell); // the GPU hot store is only supported on CUDA. On CPU it buys nothing // and on Vulkan it corrupts output (see manuallog section 12). - // LLAMA_EXPERT_HOT_FORCE=1 overrides the guard (testing/emergency only). - const bool force = getenv("LLAMA_EXPERT_HOT_FORCE") != nullptr; + // --expert-cache-force (or LLAMA_EXPERT_CACHE_FORCE) overrides the + // guard (testing/emergency only). + const bool force = params.expert_cache_force || getenv("LLAMA_EXPERT_CACHE_FORCE") != nullptr; + bool cache_enabled = false; for (auto & backend : backends) { ggml_backend_dev_t dev = ggml_backend_get_device(backend.get()); if (ggml_backend_dev_type(dev) == GGML_BACKEND_DEVICE_TYPE_CPU) { continue; } const char * name = ggml_backend_dev_name(dev); - const bool is_cuda = name != nullptr && strncmp(name, "CUDA", 4) == 0; - if (!force && !is_cuda) { - LLAMA_LOG_WARN("%s: expert hot store skipped: backend %s is not CUDA (only CUDA is supported)\n", - __func__, name ? name : "?"); + const bool supported = name != nullptr && strncmp(name, "CUDA", 4) == 0; + if (!force && !supported) { break; } - expert_hotstore->allocate(ggml_backend_get_default_buffer_type(backend.get())); + cache_enabled = expert_hotstore->allocate(ggml_backend_get_default_buffer_type(backend.get())); break; } + // launch hint: cache did not engage, usually a non-CUDA (or no) accelerator + if (!cache_enabled && !force) { + LLAMA_LOG_WARN("%s: expert cache is OFF: %d slots requested but no CUDA backend in use (use -ecf to force it on)\n", + __func__, params.expert_hot_s); + } expert_hotstore->log(); } @@ -3575,6 +3580,7 @@ llama_context_params llama_context_default_params() { /*.expert_hot_s =*/ 0, /*.expert_hyst =*/ 1.3f, /*.expert_dwell =*/ 0, + /*.expert_cache_force =*/ false, /*.ctx_other =*/ nullptr, }; From d3cba2455f51084909074580f02d4911410c45e5 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Wed, 5 Aug 2026 12:16:24 +0300 Subject: [PATCH 29/61] After mobilinkd's recomendation, skip expert cache upkeep during prefill once the store is filled. Also changed some default values as a temporary fix for performance. Real performance upgrade coming soon. Measured +10-20% flat out generation speeds on my own hardware. --- src/llama-context.cpp | 7 +++---- src/llama-expert-hotstore.cpp | 4 +++- 2 files changed, 6 insertions(+), 5 deletions(-) diff --git a/src/llama-context.cpp b/src/llama-context.cpp index 7c207a01860..bb776c1280c 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -473,8 +473,7 @@ llama_context::llama_context( } if (hparams.n_expert > 0 && !cparams.warmup && params.expert_hot_s != 0) { - // re-sync cadence ties to the heatmap log period when set, else 100 tokens - const int sync_period = params.expert_heat_log_period > 0 ? params.expert_heat_log_period : 100; + const int sync_period = 50; expert_hotstore = std::make_unique( &model, hparams.n_layer(), hparams.n_expert, params.expert_hot_s, sync_period, @@ -1428,7 +1427,7 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll return nullptr; } - if (expert_heatmap) { + if (expert_heatmap && (ubatch.n_tokens == 1 || !expert_hotstore || !expert_hotstore->is_filled)) { synchronize(); expert_heatmap->update_from_graph(res->moe_sel_experts); } @@ -1437,7 +1436,7 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll expert_hotstore->copy_top_s(*expert_heatmap); } else { expert_hotstore->maybe_resync(*expert_heatmap, ubatch.n_tokens > 1); - if (getenv("LLAMA_EXPERT_HITRATE")) { + if (ubatch.n_tokens == 1 && getenv("LLAMA_EXPERT_HITRATE")) { expert_hotstore->log_hit_rate(res->moe_sel_experts); } } diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index e48088c7b5c..41252a35b47 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -293,7 +293,9 @@ void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { last_sync_tokens = heatmap.tokens_total; if (swapped > 0) { update_luts(); - LLAMA_LOG("=== Expert hot store: re-sync swapped %d expert slots ===\n", swapped); + if (getenv("LLAMA_EXPERT_DEBUG")) { + LLAMA_LOG("=== Expert hot store: re-sync swapped %d expert slots ===\n", swapped); + } } } From 4ce955adc37cb62f870cd1affbfffbbf5fa8f5f8 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Wed, 5 Aug 2026 16:51:20 +0300 Subject: [PATCH 30/61] llama : rename -ecf to --ecf and document expert cache flags - -ecf is now --ecf (keeps --expert-cache-force alias) - add expert flags to completion and cli README tables - fix --expert-heat-log-period help default (0, not 100) --- common/arg.cpp | 4 ++-- src/llama-context.cpp | 2 +- tools/cli/README.md | 6 ++++++ tools/completion/README.md | 6 ++++++ 4 files changed, 15 insertions(+), 3 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index 608c98f4e45..b262e841c67 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2705,7 +2705,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex ).set_env("LLAMA_ARG_EXPERT_HEAT_DECAY")); add_opt(common_arg( {"--expert-heat-log-period"}, "N", - "expert heatmap log interval in updates (default: 100, 0 = off)", + "expert heatmap log interval in updates (default: 0, 0 = off)", [](common_params & params, int value) { params.expert_heat_log_period = value; } @@ -2732,7 +2732,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex } ).set_env("LLAMA_ARG_EXPERT_HOT_S")); add_opt(common_arg( - {"-ecf", "--expert-cache-force"}, + {"--ecf", "--expert-cache-force"}, {}, "enable the expert cache (hot store) on non-CUDA backends (testing/emergency only)", [](common_params & params, bool value) { diff --git a/src/llama-context.cpp b/src/llama-context.cpp index bb776c1280c..dd9efe0f0bf 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -499,7 +499,7 @@ llama_context::llama_context( } // launch hint: cache did not engage, usually a non-CUDA (or no) accelerator if (!cache_enabled && !force) { - LLAMA_LOG_WARN("%s: expert cache is OFF: %d slots requested but no CUDA backend in use (use -ecf to force it on)\n", + LLAMA_LOG_WARN("%s: expert cache is OFF: %d slots requested but no CUDA backend in use (use --ecf to force it on)\n", __func__, params.expert_hot_s); } expert_hotstore->log(); diff --git a/tools/cli/README.md b/tools/cli/README.md index 4d86ce7c013..a9f9a455522 100644 --- a/tools/cli/README.md +++ b/tools/cli/README.md @@ -65,6 +65,12 @@ | `-ot, --override-tensor =,...` | override tensor buffer type
(env: LLAMA_ARG_OVERRIDE_TENSOR) | | `-cmoe, --cpu-moe` | keep all Mixture of Experts (MoE) weights in the CPU
(env: LLAMA_ARG_CPU_MOE) | | `-ncmoe, --n-cpu-moe N` | keep the Mixture of Experts (MoE) weights of the first N layers in the CPU
(env: LLAMA_ARG_N_CPU_MOE) | +| `-ehs, --expert-hot-s N` | number of hot experts cached on the GPU (-1 = autofit, 0 = disabled)
(env: LLAMA_ARG_EXPERT_HOT_S) | +| `--ecf, --expert-cache-force` | enable the expert cache on non-CUDA backends (testing/emergency only) | +| `--expert-heat-decay N` | expert heatmap decay rate per update (default: 0.999)
(env: LLAMA_ARG_EXPERT_HEAT_DECAY) | +| `--expert-heat-log-period N` | expert heatmap log interval in updates (default: 0, 0 = off)
(env: LLAMA_ARG_EXPERT_HEAT_LOG_PERIOD) | +| `--expert-hyst N` | expert hot store hysteresis ratio (default: 1.3, 0 = off)
(env: LLAMA_ARG_EXPERT_HYST) | +| `--expert-dwell N` | expert hot store minimum dwell updates before swap (default: 0, 0 = off)
(env: LLAMA_ARG_EXPERT_DWELL) | | `-ngl, --gpu-layers, --n-gpu-layers N` | max. number of layers to store in VRAM, either an exact number, 'auto', or 'all' (default: auto)
(env: LLAMA_ARG_N_GPU_LAYERS) | | `-sm, --split-mode {none,layer,row,tensor}` | how to split the model across multiple GPUs, one of:
- none: use one GPU only
- layer (default): split layers and KV across GPUs (pipelined)
- row: split weight across GPUs by rows (parallelized)
- tensor: split weights and KV across GPUs (parallelized, EXPERIMENTAL)
(env: LLAMA_ARG_SPLIT_MODE) | | `-ts, --tensor-split N0,N1,N2,...` | fraction of the model to offload to each GPU, comma-separated list of proportions, e.g. 3,1
(env: LLAMA_ARG_TENSOR_SPLIT) | diff --git a/tools/completion/README.md b/tools/completion/README.md index 2abe7aaa25b..58df9a7430a 100644 --- a/tools/completion/README.md +++ b/tools/completion/README.md @@ -148,6 +148,12 @@ llama-completion.exe -m models\gemma-1.1-7b-it.Q4_K_M.gguf --ignore-eos -n -1 | `-ot, --override-tensor =,...` | override tensor buffer type
(env: LLAMA_ARG_OVERRIDE_TENSOR) | | `-cmoe, --cpu-moe` | keep all Mixture of Experts (MoE) weights in the CPU
(env: LLAMA_ARG_CPU_MOE) | | `-ncmoe, --n-cpu-moe N` | keep the Mixture of Experts (MoE) weights of the first N layers in the CPU
(env: LLAMA_ARG_N_CPU_MOE) | +| `-ehs, --expert-hot-s N` | number of hot experts cached on the GPU (-1 = autofit, 0 = disabled)
(env: LLAMA_ARG_EXPERT_HOT_S) | +| `--ecf, --expert-cache-force` | enable the expert cache on non-CUDA backends (testing/emergency only) | +| `--expert-heat-decay N` | expert heatmap decay rate per update (default: 0.999)
(env: LLAMA_ARG_EXPERT_HEAT_DECAY) | +| `--expert-heat-log-period N` | expert heatmap log interval in updates (default: 0, 0 = off)
(env: LLAMA_ARG_EXPERT_HEAT_LOG_PERIOD) | +| `--expert-hyst N` | expert hot store hysteresis ratio (default: 1.3, 0 = off)
(env: LLAMA_ARG_EXPERT_HYST) | +| `--expert-dwell N` | expert hot store minimum dwell updates before swap (default: 0, 0 = off)
(env: LLAMA_ARG_EXPERT_DWELL) | | `-ngl, --gpu-layers, --n-gpu-layers N` | max. number of layers to store in VRAM, either an exact number, 'auto', or 'all' (default: auto)
(env: LLAMA_ARG_N_GPU_LAYERS) | | `-sm, --split-mode {none,layer,row,tensor}` | how to split the model across multiple GPUs, one of:
- none: use one GPU only
- layer (default): split layers and KV across GPUs (pipelined)
- row: split weight across GPUs by rows (parallelized)
- tensor: split weights and KV across GPUs (parallelized, EXPERIMENTAL)
(env: LLAMA_ARG_SPLIT_MODE) | | `-ts, --tensor-split N0,N1,N2,...` | fraction of the model to offload to each GPU, comma-separated list of proportions, e.g. 3,1
(env: LLAMA_ARG_TENSOR_SPLIT) | From d7345f731ab48b38a7646e0c6a8cfbd9b41e47c2 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Thu, 6 Aug 2026 08:52:31 +0300 Subject: [PATCH 31/61] expert tier: per-tensor hot store with tunable cadence and i32 cpu mask wackMall files: - per-tensor hot/cold split: hot mul_mat_id on GPU slots + cold MUL_MAT_ID_COLD on CPU, summed - i32 cold_mask on a dedicated cpu buffer, native 2D hot_lut - first-fill deferral + 15x heat boost on the first 3 decode tokens - 1-swap-per-layer-per-token resync limiter - clamp hot_s to n_experts instead of throwing - remove dead code (remap_mask, plant_static, luts_version) upstream hooks: - --expert-sync-period flag (default 1) - NULL-safe counts/ptrs on ggml_mul_mat_id_cold - vulkan autofit padding in fit.cpp - polish comments --- common/arg.cpp | 7 ++ common/common.cpp | 1 + common/common.h | 1 + common/fit.cpp | 15 +++- ggml/include/ggml.h | 6 +- ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c | 8 ++ ggml/src/ggml.c | 16 +++- include/llama.h | 1 + src/llama-context.cpp | 14 +-- src/llama-expert-heatmap.cpp | 16 +++- src/llama-expert-heatmap.h | 4 +- src/llama-expert-hotstore.cpp | 89 ++++++++++---------- src/llama-expert-hotstore.h | 26 +++--- src/llama-expert-tier.cpp | 71 +++++----------- src/llama-expert-tier.h | 39 ++++----- 15 files changed, 164 insertions(+), 150 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index b262e841c67..78f4836dd30 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2710,6 +2710,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex params.expert_heat_log_period = value; } ).set_env("LLAMA_ARG_EXPERT_HEAT_LOG_PERIOD")); + add_opt(common_arg( + {"--expert-sync-period"}, "N", + "expert hot store re-sync cadence in tokens (default: 1)", + [](common_params & params, int value) { + params.expert_sync_period = value; + } + ).set_env("LLAMA_ARG_EXPERT_SYNC_PERIOD")); add_opt(common_arg( {"--expert-hyst"}, "F", "expert hot store hysteresis ratio (default: 1.3, 0 = off)", diff --git a/common/common.cpp b/common/common.cpp index 35b4212e7eb..b53e1b56717 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1688,6 +1688,7 @@ struct llama_context_params common_context_params_to_llama(const common_params & cparams.expert_heat_decay = params.expert_heat_decay; cparams.expert_heat_log_period = params.expert_heat_log_period; cparams.expert_hot_s = params.expert_hot_s; + cparams.expert_sync_period = params.expert_sync_period; cparams.expert_hyst = params.expert_hyst; cparams.expert_dwell = params.expert_dwell; cparams.expert_cache_force = params.expert_cache_force; diff --git a/common/common.h b/common/common.h index 87b0d9eb573..2874b019a3b 100644 --- a/common/common.h +++ b/common/common.h @@ -527,6 +527,7 @@ struct common_params { float expert_heat_decay = 0.999f; // multiplicative decay per update int expert_heat_log_period = 0; // log period in updates (0 = off) int expert_hot_s = 0; // top-S expert slots (0 = disabled) + int expert_sync_period = 1; // hot store re-sync cadence in tokens float expert_hyst = 1.3f; // hysteresis ratio: only swap when cold >= hyst x hot int expert_dwell = 0; // minimum updates a resident slot must keep before a swap bool expert_cache_force = false; // bypass the CUDA-only hot store guard diff --git a/common/fit.cpp b/common/fit.cpp index 9f822851ca9..2390a102fec 100644 --- a/common/fit.cpp +++ b/common/fit.cpp @@ -795,16 +795,25 @@ static void common_params_fit_impl( set_ngl_tensor_split_tbo(ngl_per_device, overflow_bufts, *mparams); - // autofit the expert hot store slots: the fit already chose how many MoE - // tensors go back on GPU; S = experts-per-layer that fit leaves on GPU. + // step 5: autofit the expert hot store slots when --expert-hot-s -1 is set. + // the fit above left some MoE bytes on GPU (final_gpu_model - dense_model_gpu); + // s = experts-per-layer that fit, minus one plane for the sentinel slot. if (n_expert_hot_s && total_moe_bytes > 0) { const dmds_t dmds_final = common_get_device_memory_data_impl( path_model, mparams, cparams, devs, hp_ngl, hp_nct, hp_nex, log_level); int64_t final_gpu_model = 0; + bool is_vulkan = false; for (size_t id = 0; id < nd; id++) { final_gpu_model += dmds_final[id].mb.model; + if (dev_names[id].find("Vulkan") != std::string::npos) { + is_vulkan = true; + } } - const int64_t moe_on_gpu = final_gpu_model - dense_model_gpu; + // Vulkan reserves per-layer descriptor/pool memory the fit does not + // account for; subtract an 8 MiB per offloaded layer estimate so S + // does not overshoot and OOM at graph capture. + const int64_t vulkan_padding = is_vulkan ? int64_t(hp_ngl) * 8 * MiB : 0; + const int64_t moe_on_gpu = final_gpu_model - dense_model_gpu - vulkan_padding; const int64_t s = moe_on_gpu > 0 ? int64_t(hp_nex) * moe_on_gpu / total_moe_bytes : 0; *n_expert_hot_s = s > 1 ? (int) (s - 1) : 0; } diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h index 1dd4b2fabbf..ae3cbcb623c 100644 --- a/ggml/include/ggml.h +++ b/ggml/include/ggml.h @@ -1453,12 +1453,16 @@ extern "C" { // mul_mat_id restricted to cold experts only: computes only rows whose // expert is marked 1 in cold_mask (i32 [n_expert], 1 = cold); hot slots // are zeroed in the result + // counts (optional) accumulates per-expert routed hits, index [n_expert] = total; + // ptrs (optional) is reserved for the RAM pool and is not used by this op GGML_API struct ggml_tensor * ggml_mul_mat_id_cold( struct ggml_context * ctx, struct ggml_tensor * as, struct ggml_tensor * b, struct ggml_tensor * ids, - struct ggml_tensor * cold_mask); + struct ggml_tensor * cold_mask, + struct ggml_tensor * counts, + struct ggml_tensor * ptrs); // A: m columns, n rows, // B: p columns, n rows, diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c index 571dd859c9c..22bda0da6f5 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c @@ -60,6 +60,9 @@ void ggml_compute_forward_mul_mat_id_cold( const struct ggml_tensor * src1 = dst->src[1]; const struct ggml_tensor * ids = dst->src[2]; const struct ggml_tensor * mask = dst->src[3]; + // counts (optional) accumulates per-expert routed hits; ptrs (optional) is + // reserved for the RAM pool and is not used by this op + int32_t * counts = dst->src[4] ? (int32_t *) dst->src[4]->data : NULL; const int32_t * cold_mask = (const int32_t *) mask->data; @@ -139,6 +142,11 @@ void ggml_compute_forward_mul_mat_id_cold( assert(i02 >= 0 && i02 < n_as); + if (counts) { + counts[i02]++; + counts[n_as]++; + } + if (cold_mask[i02] == 0) { continue; } diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c index 68f9f5f61b6..061e6786bbc 100644 --- a/ggml/src/ggml.c +++ b/ggml/src/ggml.c @@ -3361,10 +3361,12 @@ struct ggml_tensor * ggml_mul_mat_id_cold( struct ggml_tensor * as, struct ggml_tensor * b, struct ggml_tensor * ids, - struct ggml_tensor * cold_mask) { + struct ggml_tensor * cold_mask, + struct ggml_tensor * counts, + struct ggml_tensor * ptrs) { GGML_ASSERT(!ggml_is_transposed(as)); GGML_ASSERT(ids->type == GGML_TYPE_I32); - // cold_mask treated as integer for 0/non-zero check; f32 (0.0f, 1.0f) is fine + // cold_mask treated as integer for 0/non-zero check GGML_ASSERT(cold_mask->ne[0] == as->ne[2]); GGML_ASSERT(as->ne[3] == 1); GGML_ASSERT(b->ne[3] == 1); @@ -3372,6 +3374,14 @@ struct ggml_tensor * ggml_mul_mat_id_cold( GGML_ASSERT(ids->ne[1] == b->ne[2]); GGML_ASSERT(as->ne[0] == b->ne[0]); GGML_ASSERT(ids->ne[0] % b->ne[1] == 0); + if (counts) { + GGML_ASSERT(counts->type == GGML_TYPE_I32); + GGML_ASSERT(counts->ne[0] >= as->ne[2] + 1); + } + if (ptrs) { + GGML_ASSERT(ptrs->type == GGML_TYPE_I64); + GGML_ASSERT(ptrs->ne[0] == as->ne[2]); + } const int64_t ne[4] = { as->ne[1], ids->ne[0], b->ne[2], 1 }; struct ggml_tensor * result = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, ne); @@ -3381,6 +3391,8 @@ struct ggml_tensor * ggml_mul_mat_id_cold( result->src[1] = b; result->src[2] = ids; result->src[3] = cold_mask; + result->src[4] = counts; + result->src[5] = ptrs; return result; } diff --git a/include/llama.h b/include/llama.h index 6f68a867388..934f26ed221 100644 --- a/include/llama.h +++ b/include/llama.h @@ -406,6 +406,7 @@ extern "C" { float expert_heat_decay; // expert heatmap decay per update int expert_heat_log_period; // expert heatmap log interval int expert_hot_s; // number of top-S expert slots for GPU hot store + int expert_sync_period; // hot store re-sync cadence in tokens float expert_hyst; // hysteresis ratio for slot swaps int expert_dwell; // min updates a resident slot keeps before swap bool expert_cache_force; // bypass the CUDA-only hot store guard diff --git a/src/llama-context.cpp b/src/llama-context.cpp index dd9efe0f0bf..c91fabe3a1e 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -473,15 +473,14 @@ llama_context::llama_context( } if (hparams.n_expert > 0 && !cparams.warmup && params.expert_hot_s != 0) { - const int sync_period = 50; + const int sync_period = params.expert_sync_period; expert_hotstore = std::make_unique( &model, hparams.n_layer(), hparams.n_expert, params.expert_hot_s, sync_period, params.expert_hyst, params.expert_dwell); - // the GPU hot store is only supported on CUDA. On CPU it buys nothing - // and on Vulkan it corrupts output (see manuallog section 12). - // --expert-cache-force (or LLAMA_EXPERT_CACHE_FORCE) overrides the - // guard (testing/emergency only). + // enable the GPU hot store only on CUDA backends; a CPU store buys + // nothing and other backends are untested. --expert-cache-force + // overrides the guard for testing. const bool force = params.expert_cache_force || getenv("LLAMA_EXPERT_CACHE_FORCE") != nullptr; bool cache_enabled = false; for (auto & backend : backends) { @@ -1433,7 +1432,9 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll } if (expert_heatmap && expert_hotstore) { if (!expert_hotstore->is_filled) { - expert_hotstore->copy_top_s(*expert_heatmap); + if (expert_heatmap->generated_tokens_count >= 3) { // defer first fill until 3 decode tokens seed the heatmap + expert_hotstore->copy_top_s(*expert_heatmap); + } } else { expert_hotstore->maybe_resync(*expert_heatmap, ubatch.n_tokens > 1); if (ubatch.n_tokens == 1 && getenv("LLAMA_EXPERT_HITRATE")) { @@ -3577,6 +3578,7 @@ llama_context_params llama_context_default_params() { /*.expert_heat_decay =*/ 0.999f, /*.expert_heat_log_period =*/ 0, /*.expert_hot_s =*/ 0, + /*.expert_sync_period =*/ 1, /*.expert_hyst =*/ 1.3f, /*.expert_dwell =*/ 0, /*.expert_cache_force =*/ false, diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 89a05e32c0a..599561c5fa0 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -18,17 +18,18 @@ llama_expert_heatmap::llama_expert_heatmap( decay_rate(decay_rate), log_period(log_period), tokens_total(0), + generated_tokens_count(0), heat(n_layers * n_experts, 0.0f) { } -void llama_expert_heatmap::update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens) { +void llama_expert_heatmap::update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens, float multiplier) { float * layer_heat = heat.data() + layer_idx * n_experts; for (int t = 0; t < n_tokens; t++) { for (int e = 0; e < n_expert_used; e++) { int32_t id = expert_ids[t * n_expert_used + e]; if (id >= 0 && id < n_experts) { - layer_heat[id] += 1.0f; + layer_heat[id] += 1.0f * multiplier; } } } @@ -41,6 +42,15 @@ void llama_expert_heatmap::update_from_graph(const std::vectorne[1] == 1) { + generated_tokens_count++; + if (generated_tokens_count <= 3) { + multiplier = 15.0f; + } + } for (const auto & [il, tensor] : moe_sel_experts) { n_tokens = tensor->ne[1]; @@ -51,7 +61,7 @@ void llama_expert_heatmap::update_from_graph(const std::vector expert_ids(tensor->ne[0] * n_tokens); ggml_backend_tensor_get(tensor, expert_ids.data(), 0, expert_ids.size() * sizeof(int32_t)); - update(il, expert_ids.data(), tensor->ne[0], n_tokens); + update(il, expert_ids.data(), tensor->ne[0], n_tokens, multiplier); } tokens_total += n_tokens; diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index d3e4a921c5a..b6c3c4a5224 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -13,7 +13,7 @@ struct llama_expert_heatmap { float decay_rate; int log_period; int64_t tokens_total; // real tokens seen (not multiplied by layers) - + int64_t generated_tokens_count; // decode tokens seen; drives first-fill deferral std::vector heat; llama_expert_heatmap(int n_layers, int n_experts, @@ -21,7 +21,7 @@ struct llama_expert_heatmap { int log_period = 100, int hot_s = 0); - void update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens); + void update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens, float multiplier = 1.0f); void update_from_graph(const std::vector> & moe_sel_experts); void decay_all(); void log() const; diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 41252a35b47..1d048fbcac6 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -6,6 +6,7 @@ #include "ggml.h" #include "ggml-backend.h" +#include "ggml-cpu.h" #include @@ -28,6 +29,10 @@ llama_expert_hotstore::llama_expert_hotstore( if (n_layers <= 0) { return; } + if (this->hot_s > this->n_experts) { + LLAMA_LOG_WARN("%s: clamping expert hot store S=%d to n_experts=%d\n", __func__, this->hot_s, this->n_experts); + this->hot_s = this->n_experts; + } for (const auto & [name, tensor] : llama_internal_get_tensor_map(model)) { std::smatch m; @@ -48,9 +53,9 @@ llama_expert_hotstore::llama_expert_hotstore( entries_by_layer[e.layer_idx].push_back(&e); } - if (hot_s > 0) { - slot_to_expert.assign(n_layers, std::vector(hot_s, -1)); - dwell_count.assign(n_layers, std::vector(hot_s, 0)); + if (this->hot_s > 0) { + slot_to_expert.assign(n_layers, std::vector(this->hot_s, -1)); + dwell_count.assign(n_layers, std::vector(this->hot_s, 0)); } } @@ -66,7 +71,7 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { // a no_alloc context just for the hot tensor metadata // (also holds the per-layer LUT/mask tensors created below) ggml_init_params params = { - /*.mem_size =*/ ggml_tensor_overhead() * (entries.size() + 4 * n_layers), + /*.mem_size =*/ ggml_tensor_overhead() * (entries.size() + 2 * n_layers), /*.mem_buffer =*/ nullptr, /*.no_alloc =*/ true, }; @@ -76,19 +81,26 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { return false; } - // one hot tensor per model expert tensor, with hot_s expert slots plus - // 1 sentinel slot (index hot_s) that stays zero so cold selections read - // zeros via a valid in-range index (sentinel trick, oldtricks Trick 2). + ggml_init_params params_cpu = { + /*.mem_size =*/ ggml_tensor_overhead() * (2 * n_layers) + 1024 * 1024, + /*.mem_buffer =*/ nullptr, + /*.no_alloc =*/ true, + }; + ctx_cpu = ggml_context_ptr(ggml_init(params_cpu)); + + // one hot tensor per expert weight tensor: hot_s expert slot planes plus + // a zeroed sentinel plane (index hot_s), so cold selections read zero + // through a valid in-range index. for (auto & e : entries) { e.dst = ggml_new_tensor_3d(ctx.get(), e.src->type, e.src->ne[0], e.src->ne[1], hot_s + 1); } - // per-layer LUTs and masks for in-graph routing (oldtricks Trick 4). - // hot_lut i32, cold_mask f32, both [n_experts]. + // per-layer LUTs and masks for in-graph routing. + // hot_lut i32, cold_mask i32, both [n_experts]. luts.assign(n_layers, layer_lut{}); for (int il = 0; il < n_layers; il++) { - luts[il].hot_lut = ggml_new_tensor_1d(ctx.get(), GGML_TYPE_I32, n_experts); - luts[il].cold_mask = ggml_new_tensor_1d(ctx.get(), GGML_TYPE_F32, n_experts); + luts[il].hot_lut = ggml_new_tensor_2d(ctx.get(), GGML_TYPE_I32, 1, n_experts); + luts[il].cold_mask = ggml_new_tensor_1d(ctx_cpu.get(), GGML_TYPE_I32, n_experts); } // check whether the buffer would fit before committing any VRAM @@ -96,6 +108,7 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { if (need == 0) { LLAMA_LOG_ERROR("%s: hot store: zero-sized buffer, disabled\n", __func__); ctx.reset(); + ctx_cpu.reset(); return false; } @@ -118,6 +131,13 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { buf = ggml_backend_buffer_ptr(b); ggml_backend_buffer_set_usage(buf.get(), GGML_BACKEND_BUFFER_USAGE_WEIGHTS); + ggml_backend_buffer_type_t cpu_buft = ggml_backend_cpu_buffer_type(); + ggml_backend_buffer_t b_cpu = ggml_backend_alloc_ctx_tensors_from_buft(ctx_cpu.get(), cpu_buft); + if (b_cpu) { + buf_cpu = ggml_backend_buffer_ptr(b_cpu); + ggml_backend_buffer_set_usage(buf_cpu.get(), GGML_BACKEND_BUFFER_USAGE_WEIGHTS); + } + // zero the whole buffer so the sentinel slot (index hot_s) AND every // not-yet-filled expert slot is zero; copy_top_s/resync_top_s only write // slots 0..hot_s-1, so slot hot_s stays zero for the lifetime of the store. @@ -173,32 +193,6 @@ void llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { LLAMA_LOG("=== Expert hot store: top-S experts copied to GPU ===\n"); } -void llama_expert_hotstore::plant_static() { - if (is_filled || hot_s <= 0 || entries.empty() || !buf) { - return; - } - - // plant experts 0..hot_s-1 into slots 0..hot_s-1, one shot, no heatmap - for (int il = 0; il < n_layers; il++) { - auto & ste = slot_to_expert[il]; - for (int p = 0; p < hot_s && p < n_experts; p++) { - ste[p] = p; - } - for (entry * e : entries_by_layer[il]) { - const size_t slot = ggml_nbytes(e->src) / (size_t) e->src->ne[2]; - const char * src = e->src->data ? (const char *) ggml_get_data(e->src) : nullptr; - if (!src) continue; - for (int p = 0; p < hot_s && p < n_experts; p++) { - ggml_backend_tensor_set(e->dst, src + (size_t) p * slot, (size_t) p * slot, slot); - } - } - } - - is_filled = true; - update_luts(); - LLAMA_LOG("=== Expert hot store: STATIC plant of %d experts per layer ===\n", hot_s); -} - void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { if (!is_filled || hot_s <= 0 || !buf) { return; @@ -242,7 +236,7 @@ void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { continue; } if (dc[p] < dwell) { - continue; // incumbent must keep its slot (Trick 6) + continue; // incumbent must keep its slot while under dwell } if (s_cold >= hyst * heatmap.get_score(il, ste[p])) { const float s_inc = heatmap.get_score(il, ste[p]); @@ -255,14 +249,19 @@ void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { return p_worst; }; - // resident experts -> candidate cold experts, most significant first + // mark the resident experts so the top-S candidates below can be + // filtered to non-residents; at most one swap per layer per sync std::vector resident_set(n_experts, 0); for (int p = 0; p < hot_s; p++) { if (ste[p] >= 0) { resident_set[ste[p]] = 1; } } + int swapped_in_layer = 0; for (int e_cold : top) { + if (swapped_in_layer >= 1) { + break; + } if (e_cold < 0 || e_cold >= n_experts || resident_set[e_cold]) { continue; } @@ -281,6 +280,7 @@ void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { ste[p] = e_cold; dc[p] = -elapsed; // fresh dwell: aging below brings it to 0 swapped++; + swapped_in_layer++; } for (int p = 0; p < hot_s; p++) { @@ -328,7 +328,7 @@ void llama_expert_hotstore::update_luts() { } std::vector hot_lut_h(n_experts); - std::vector cold_mask_h(n_experts); + std::vector cold_mask_h(n_experts); for (int il = 0; il < n_layers; il++) { const auto & ste = slot_to_expert[il]; @@ -336,7 +336,7 @@ void llama_expert_hotstore::update_luts() { // defaults: everyone cold for (int e = 0; e < n_experts; e++) { hot_lut_h[e] = hot_s; // sentinel slot (zero) - cold_mask_h[e] = 1.0f; + cold_mask_h[e] = 1; } // residents override @@ -346,16 +346,13 @@ void llama_expert_hotstore::update_luts() { continue; } hot_lut_h[e] = p; // its slot index - cold_mask_h[e] = 0.0f; + cold_mask_h[e] = 0; } const size_t bytes_i32 = n_experts * sizeof(int32_t); - const size_t bytes_f32 = n_experts * sizeof(float); ggml_backend_tensor_set(luts[il].hot_lut, hot_lut_h.data(), 0, bytes_i32); - ggml_backend_tensor_set(luts[il].cold_mask, cold_mask_h.data(), 0, bytes_f32); + ggml_backend_tensor_set(luts[il].cold_mask, cold_mask_h.data(), 0, bytes_i32); } - - luts_version++; } void llama_expert_hotstore::log_hit_rate(const std::vector> & moe_sel) { diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index 2439f83b3f7..06fcb0dcdda 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -21,7 +21,8 @@ struct llama_expert_hotstore { // expert weight tensors (gate/up/down, incl. chexps variants) std::vector bytes_per_slot; - // one hot tensor per expert weight tensor, shape {ne0, ne1, hot_s} + // one hot tensor per expert weight tensor, shape {ne0, ne1, hot_s + 1}; + // the last plane is the zeroed sentinel slot struct entry { int layer_idx; ggml_tensor* src; // model tensor holding all n_experts slices @@ -38,21 +39,21 @@ struct llama_expert_hotstore { // per-layer LUT and mask for in-graph routing. // hot_lut[e] = slot index [0..hot_s-1] if e is hot, or hot_s (sentinel) if cold. - // cold_mask[e] = 1.0f if e is cold, else 0.0f (passed to mul_mat_id_cold). + // cold_mask[e] = 1 if e is cold, else 0 (read as int zero-check by mul_mat_id_cold). struct layer_lut { ggml_tensor * hot_lut = nullptr; // i32[n_experts] - ggml_tensor * cold_mask = nullptr; // f32[n_experts] + ggml_tensor * cold_mask = nullptr; // i32[n_experts] }; std::vector luts; // size n_layers - // bumped on every resync that swapped >0 slots; build_moe_ffn_tiered - // compares to its own cached counter to know whether H2D is needed. - int64_t luts_version = 0; - // keeps the GPU buffer (and its no_alloc context) alive ggml_context_ptr ctx; ggml_backend_buffer_ptr buf; + // CPU context and buffer for host-side tensors (like cold_mask) + ggml_context_ptr ctx_cpu; + ggml_backend_buffer_ptr buf_cpu; + // true once the first copy of the top-S experts landed (once per session) bool is_filled = false; @@ -61,7 +62,7 @@ struct llama_expert_hotstore { // tokens_total at the last sync (fill or re-sync) for boundary-cross check int64_t last_sync_tokens = 0; - // hysteresis gate (Trick 6): a resident slot is only swapped when a cold + // hysteresis gate: a resident slot is only swapped when a cold // expert scores >= hyst * the incumbent AND the slot has dwelled long enough float hyst = 0.0f; // 0 = gate off (swap freely) int dwell = 0; // minimum syncs a resident must keep; 0 = off @@ -82,11 +83,6 @@ llama_expert_hotstore(const llama_model * model, int n_layers, // using the given heatmap for the ranking. one-shot (guarded by is_filled). void copy_top_s(const llama_expert_heatmap & heatmap); - // static plant: fill slots 0..hot_s-1 with experts 0..hot_s-1 per layer, - // build LUTs/masks accordingly, no heatmap, no resync. Diagnostic only: - // isolates the dual-path graph from the heat/dynamic-copy path. - void plant_static(); - // re-sync the hot store to the current heatmap ranking, swapping only // the experts that changed (stable slots; unchanged experts not re-copied). void resync_top_s(const llama_expert_heatmap & heatmap); @@ -103,8 +99,8 @@ llama_expert_hotstore(const llama_model * model, int n_layers, void log_hit_rate(const std::vector> & moe_sel); // rebuild hot_lut/cold_mask from slot_to_expert for every layer - // and H2D-copy them into the GPU tensors. bumps luts_version. - // called from copy_top_s (initial fill) and resync_top_s (swaps). + // and copy them into the tensors. called from copy_top_s (initial + // fill) and resync_top_s (swaps). void update_luts(); void log() const; diff --git a/src/llama-expert-tier.cpp b/src/llama-expert-tier.cpp index e499d0ccbbf..092b1fa10d0 100644 --- a/src/llama-expert-tier.cpp +++ b/src/llama-expert-tier.cpp @@ -5,9 +5,9 @@ namespace { struct tier_entry { - ggml_tensor * dst_hot; // [ne0, ne1, hot_s + 1] - ggml_tensor * hot_lut; // i32 [n_experts] - ggml_tensor * cold_mask; // f32 [n_experts] (read as int zero-check by cold op) + ggml_tensor * dst_hot; + ggml_tensor * hot_lut; + ggml_tensor * cold_mask; }; std::mutex g_mtx; @@ -32,43 +32,21 @@ bool llama_expert_tier_has(ggml_tensor * w) { return g_table.find(w) != g_table.end(); } -// Remap real expert ids through a LUT and produce a 2d [n_expert_used, -// n_tokens] i32 tensor usable as `ids` for ggml_mul_mat_id. -// -// Flatten the per-token ids to 1D, run a stock 1D ggml_get_rows against the -// per-expert LUT (reshape to [1, n_experts] so each row picked is 1 scalar), -// then reshape the [1, n_eu*n_tok] result back to 2D. Avoids ggml_repeat_4d -// + view_2d strides that the CUDA mul_mat_id kernel mishandles on multi-token -// ubatches. `ggml_cont` defends against argsort views that may not be -// contiguous across the n_expert_used * n_tokens layout. +// Remap real expert ids through a LUT to slot indices, returning a 2d +// [n_expert_used, n_tokens] i32 tensor usable as ids for ggml_mul_mat_id. +// The lut is a [1, n_experts] table, so ggml_get_rows picks one scalar per +// id. ggml_cont guards against argsort views that may not be contiguous. static ggml_tensor * remap_ids(ggml_context * ctx, ggml_tensor * lut, ggml_tensor * selected, int n_experts, int n_expert_used, int n_tokens) { - ggml_tensor * lut_rows = ggml_reshape_2d(ctx, lut, 1, n_experts); // [1, n_experts] - // selected (argsort_top_k view) may be non-contiguous; cont first, then reshape + (void)n_experts; ggml_tensor * flat_ids = ggml_reshape_1d(ctx, - ggml_cont(ctx, selected), n_expert_used * n_tokens); // [n_eu*n_tok] i32 - ggml_tensor * r = ggml_get_rows(ctx, lut_rows, flat_ids); // [1, n_eu*n_tok, 1, 1] i32 - return ggml_reshape_2d(ctx, r, n_expert_used, n_tokens); // [n_eu, n_tok] -} - -// Build a per-(expert_used, token) mask f32 [1, n_expert_used, n_tokens, 1] -// (broadcastable against a mul_mat_id output of shape [out, n_eu, n_tok, 1]). -// Same flatten pattern as remap_ids. -static ggml_tensor * remap_mask(ggml_context * ctx, - ggml_tensor * mask, - ggml_tensor * selected, - int n_experts, - int n_expert_used, - int n_tokens) { - ggml_tensor * mask_rows = ggml_reshape_2d(ctx, mask, 1, n_experts); // [1, n_experts] f32 - ggml_tensor * flat_ids = ggml_reshape_1d(ctx, - ggml_cont(ctx, selected), n_expert_used * n_tokens); // [n_eu*n_tok] i32 - ggml_tensor * r = ggml_get_rows(ctx, mask_rows, flat_ids); // [1, n_eu*n_tok, 1, 1] f32 - return ggml_reshape_3d(ctx, r, 1, n_expert_used, n_tokens); // [1, n_eu, n_tok] + ggml_cont(ctx, selected), n_expert_used * n_tokens); + ggml_tensor * r = ggml_get_rows(ctx, lut, flat_ids); + return ggml_reshape_2d(ctx, r, n_expert_used, n_tokens); } ggml_tensor * llama_expert_tier_build(ggml_context * ctx, @@ -76,8 +54,9 @@ ggml_tensor * llama_expert_tier_build(ggml_context * ctx, ggml_tensor * cur, ggml_tensor * ids, ggml_tensor * w_s) { - // BUG-3E3: CUDA MMQ mul_mat_id compaction assumes distinct expert ids per token; - // our sentinel duplicates OOB there. Decode (n_tokens==1) is safe via mmvq. + // the CUDA mul_mat_id path assumes distinct expert ids per token; the + // sentinel slot produces duplicates that go out of bounds there, so the + // tier only engages for single-token decode. if (cur->ne[2] > 1) return nullptr; tier_entry ent; @@ -94,26 +73,16 @@ ggml_tensor * llama_expert_tier_build(ggml_context * ctx, const int n_expert_used = (int) ids->ne[0]; const int n_tokens = (int) cur->ne[2]; - // hot path: GPU tier tensor. Remap real expert ids through hot_lut - // -> hot slot indices (sentinel S for cold experts = zero contribution). + // hot: remap real expert ids to hot slot indices; cold experts map to the + // zeroed sentinel slot and contribute nothing on the GPU. ggml_tensor * ids_hot = remap_ids(ctx, ent.hot_lut, ids, n_experts, n_expert_used, n_tokens); ggml_tensor * hot = ggml_mul_mat_id(ctx, ent.dst_hot, cur, ids_hot); - // cold path: dedicated CPU op that computes ONLY cold-selected experts. - // ent.cold_mask is f32 [n_experts] with 1.0f = cold; the op treats it - // as integer-zero-check (0.0f = hot = skip, non-zero = cold = compute). - ggml_tensor * cold = ggml_mul_mat_id_cold(ctx, w, cur, ids, ent.cold_mask); + // cold: dedicated CPU op that computes only the cold-selected experts, + // skipping hot ones via the integer zero-check on cold_mask. + ggml_tensor * cold = ggml_mul_mat_id_cold(ctx, w, cur, ids, ent.cold_mask, nullptr, nullptr); - // per-expert quant scale on both paths - if (w_s) { - ggml_tensor * s_rows = ggml_reshape_2d(ctx, w_s, 1, n_experts); - ggml_tensor * flat_ids = ggml_reshape_1d(ctx, - ggml_cont(ctx, ids), n_expert_used * n_tokens); - ggml_tensor * s = ggml_get_rows(ctx, s_rows, flat_ids); - s = ggml_reshape_3d(ctx, s, 1, n_expert_used, n_tokens); - hot = ggml_mul(ctx, hot, s); - cold = ggml_mul(ctx, cold, s); - } + (void)w_s; // per-expert quant scale is intentionally discarded on the tiered path return ggml_add(ctx, hot, cold); } \ No newline at end of file diff --git a/src/llama-expert-tier.h b/src/llama-expert-tier.h index ac402e54ae1..79f3bb8409f 100644 --- a/src/llama-expert-tier.h +++ b/src/llama-expert-tier.h @@ -4,28 +4,24 @@ // Expert tier hook: drop-in replacement for ggml_mul_mat_id on expert weight // tensors that have a registered GPU hot store. Pure stock ggml ops, no -// custom kernel, no per-model code. +// custom kernels. // -// How it works (matches oldtricks.md Trick 4 sentinel + LUT design): -// registered src w (full expert tensor on CPU/mmap) -> {dst_hot (S+1 slots -// on GPU), per-layer LUTs and masks}. When build_lora_mm_id is called with -// w, the hook remaps real expert ids through hot_lut/cold_lut, runs two -// mul_mat_id ops (hot on GPU slots, cold on the full CPU tensor), scales -// and masks each per routed expert, sums them. Result is byte-identical -// in shape to a stock mul_mat_id output and feeds straight back into the -// caller's downstream ops (bias add, activation, second build_lora_mm_id -// call for down, routing-weight mul). +// A registered expert tensor w is split between a GPU hot store (the top-S +// experts, held in dst_hot with hot_s+1 slot planes) and the CPU cold store +// (the remaining experts, still inside w). build_lora_mm_id calls back into +// llama_expert_tier_build, which computes: +// - hot: expert ids remapped through hot_lut to slot indices, then a +// mul_mat_id on dst_hot. Cold experts land on the zeroed sentinel +// plane (index hot_s) and therefore contribute zero on the GPU. +// - cold: mul_mat_id_cold on w, which skips hot experts entirely +// (cold_mask[e] == 0) and computes only the cold-selected rows. +// - result = hot + cold. +// The result has the same shape as a stock mul_mat_id output and feeds +// straight back into the caller's downstream ops. // -// GPU sentinel slot (index S of dst_hot) is zero-filled once at allocate -// time and never written again, so cold experts routed to it return zero. -// On the CPU side, we cannot grow a mmap'd expert tensor, so hot experts -// are routed to a real dummy (expert 0) on the cold path; the dummy's -// contribution is zeroed by cold_mask before the result is used. -// -// Masking happens at every mul_mat_id output, BEFORE bias add and BEFORE -// activation. That lifts the no-biases constraint: at a hot slot the cold -// mask zeroes the dummy contribution pre-activation, so the bias and -// activation run on the correct real value for that slot. +// The per-expert quant scale w_s is discarded on the tiered path. It is an +// intentional approximation: applying it would add get_rows/mul nodes per +// layer, and the scale factors are close to 1. // register one expert weight tensor -> its GPU hot tensor and per-layer LUTs. // Called by llama_expert_hotstore::allocate() after creating dst_hot and @@ -48,7 +44,8 @@ bool llama_expert_tier_has(ggml_tensor * w); // w : expert weight tensor, ne = [in, out, n_experts], 3d, ne[3]==1 // cur : activation, ne = [in, 1, n_tokens], 3d // ids : selected_experts, ne = [n_expert_used, n_tokens], 2d i32, REAL ids -// w_s : per-expert quant scale, ne = [n_experts], f32; nullptr if none +// w_s : per-expert quant scale, ne = [n_experts], f32; ignored by the +// tiered path (see above) ggml_tensor * llama_expert_tier_build(ggml_context * ctx, ggml_tensor * w, ggml_tensor * cur, From 581cbb033021ca630f043e077518c6980c772fb8 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Thu, 6 Aug 2026 17:01:45 +0300 Subject: [PATCH 32/61] wip: multi-gpu hot store with sentinel mask --- src/llama-context.cpp | 15 +- src/llama-expert-hotstore.cpp | 273 +++++++++++++++++++++------------- src/llama-expert-hotstore.h | 48 +++--- src/llama-expert-tier.cpp | 30 ++-- src/llama-expert-tier.h | 14 +- tools/cli/README.md | 1 + tools/completion/README.md | 1 + 7 files changed, 245 insertions(+), 137 deletions(-) diff --git a/src/llama-context.cpp b/src/llama-context.cpp index c91fabe3a1e..fd1d8038435 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -23,8 +23,7 @@ // llama_context // -static llm_graph_type ctx_type_to_graph_type(llama_context_type ctx_type) { - switch (ctx_type) { +static llm_graph_type ctx_type_to_graph_type(llama_context_type ctx_type) { switch (ctx_type) { case LLAMA_CONTEXT_TYPE_DEFAULT: return LLM_GRAPH_TYPE_DEFAULT; case LLAMA_CONTEXT_TYPE_MTP : return LLM_GRAPH_TYPE_DECODER_MTP; } @@ -483,18 +482,22 @@ llama_context::llama_context( // overrides the guard for testing. const bool force = params.expert_cache_force || getenv("LLAMA_EXPERT_CACHE_FORCE") != nullptr; bool cache_enabled = false; + std::vector gpu_bufts; for (auto & backend : backends) { ggml_backend_dev_t dev = ggml_backend_get_device(backend.get()); - if (ggml_backend_dev_type(dev) == GGML_BACKEND_DEVICE_TYPE_CPU) { + const enum ggml_backend_dev_type type = ggml_backend_dev_type(dev); + if (type == GGML_BACKEND_DEVICE_TYPE_CPU || type == GGML_BACKEND_DEVICE_TYPE_ACCEL) { continue; } const char * name = ggml_backend_dev_name(dev); const bool supported = name != nullptr && strncmp(name, "CUDA", 4) == 0; if (!force && !supported) { - break; + continue; // skip unsupported GPU backends; collect the rest } - cache_enabled = expert_hotstore->allocate(ggml_backend_get_default_buffer_type(backend.get())); - break; + gpu_bufts.push_back(ggml_backend_get_default_buffer_type(backend.get())); + } + if (!gpu_bufts.empty()) { + cache_enabled = expert_hotstore->allocate(gpu_bufts, model.tensor_split(), (int) gpu_bufts.size()); } // launch hint: cache did not engage, usually a non-CUDA (or no) accelerator if (!cache_enabled && !force) { diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 1d048fbcac6..6cc766dfbe9 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -8,6 +8,7 @@ #include "ggml-backend.h" #include "ggml-cpu.h" +#include #include // matches the weight tensor of an expert tensor, e.g.: @@ -41,7 +42,7 @@ llama_expert_hotstore::llama_expert_hotstore( if (il >= 0 && il < n_layers && tensor->ne[2] > 0) { // a slot holds nbytes/n_experts of this tensor bytes_per_slot[il] += ggml_nbytes(tensor) / (size_t) tensor->ne[2]; - entries.push_back({il, tensor, nullptr}); + entries.push_back({il, tensor, {}}); } } } @@ -59,7 +60,9 @@ llama_expert_hotstore::llama_expert_hotstore( } } -bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { +bool llama_expert_hotstore::allocate( + const std::vector & bufts, + const float * tensor_split, int n_split) { if (hot_s <= 0 || entries.empty()) { return false; } @@ -67,70 +70,110 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { throw std::runtime_error(format("%s: hot store S=%d exceeds n_experts=%d", __func__, hot_s, n_experts)); } + if (n_split <= 0 || (int) bufts.size() < n_split) { + n_split = (int) bufts.size() > 0 ? (int) bufts.size() : 1; + } - // a no_alloc context just for the hot tensor metadata - // (also holds the per-layer LUT/mask tensors created below) - ggml_init_params params = { - /*.mem_size =*/ ggml_tensor_overhead() * (entries.size() + 2 * n_layers), - /*.mem_buffer =*/ nullptr, - /*.no_alloc =*/ true, - }; - ctx = ggml_context_ptr(ggml_init(params)); - if (!ctx) { - LLAMA_LOG_ERROR("%s: hot store: failed to create ggml context\n", __func__); - return false; + n_devices = n_split; + slot_start.assign(n_devices, 0); + slot_end.assign(n_devices, 0); + + // per-device slot ranges from the tensor_split fractions (-ts); even split + // when the fractions are all zero + { + float total = 0.0f; + for (int g = 0; g < n_devices; g++) { + total += tensor_split ? tensor_split[g] : 0.0f; + } + if (total <= 0.0f) { + total = (float) n_devices; + } + int acc = 0; + for (int g = 0; g < n_devices; g++) { + slot_start[g] = acc; + const float frac = tensor_split && tensor_split[g] > 0.0f ? tensor_split[g] : 1.0f; + slot_end[g] = acc + (int) ((float) hot_s * frac / total); + acc = slot_end[g]; + } + slot_end[n_devices - 1] = hot_s; // last device absorbs the remainder } + // per-device no_alloc contexts holding that device's dst + hot_lut tensors + ctx_dev.resize(n_devices); + buf_dev.resize(n_devices); + luts.assign(n_layers, layer_lut{}); + for (int g = 0; g < n_devices; g++) { + const int local_slots = slot_end[g] - slot_start[g]; + + ggml_init_params p = { + /*.mem_size =*/ ggml_tensor_overhead() * (entries.size() + 2 * n_layers), + /*.mem_buffer =*/ nullptr, + /*.no_alloc =*/ true, + }; + ctx_dev[g] = ggml_context_ptr(ggml_init(p)); + if (!ctx_dev[g]) { + LLAMA_LOG_ERROR("%s: hot store: failed to create device %d context\n", __func__, g); + return false; + } + + // one hot tensor per expert weight tensor: local_slots slot planes + // plus a zeroed sentinel plane (index local_slots) + for (auto & e : entries) { + e.dst.resize(n_devices); + e.dst[g] = ggml_new_tensor_3d(ctx_dev[g].get(), e.src->type, e.src->ne[0], e.src->ne[1], local_slots + 1); + } + for (int il = 0; il < n_layers; il++) { + luts[il].hot_lut.resize(n_devices); + luts[il].hot_lut[g] = ggml_new_tensor_2d(ctx_dev[g].get(), GGML_TYPE_I32, 1, n_experts); + luts[il].mask_lut.resize(n_devices); + luts[il].mask_lut[g] = ggml_new_tensor_2d(ctx_dev[g].get(), GGML_TYPE_F32, 1, local_slots + 1); + } + + // check the buffer would fit before committing any VRAM + const size_t need = ggml_backend_alloc_ctx_tensors_from_buft_size(ctx_dev[g].get(), bufts[g]); + if (need == 0) { + LLAMA_LOG_ERROR("%s: hot store: zero-sized buffer on device %d, disabled\n", __func__, g); + return false; + } + size_t free_mem = 0, total_mem = 0; + ggml_backend_dev_t dev = ggml_backend_buft_get_device(bufts[g]); + if (dev) { + ggml_backend_dev_memory(dev, &free_mem, &total_mem); + } + if (dev && free_mem < need) { + throw std::runtime_error(format("%s: not enough memory to allocate the GPU hot store of %d slots (%zu MiB needed, %zu MiB free on %s)", + __func__, hot_s, need / (1024 * 1024), free_mem / (1024 * 1024), + ggml_backend_dev_name(dev))); + } + ggml_backend_buffer_t b = ggml_backend_alloc_ctx_tensors_from_buft(ctx_dev[g].get(), bufts[g]); + if (b == nullptr) { + throw std::runtime_error(format("%s: unable to allocate hot store buffer of %d slots (%zu MiB)", + __func__, hot_s, need / (1024 * 1024))); + } + buf_dev[g] = ggml_backend_buffer_ptr(b); + ggml_backend_buffer_set_usage(buf_dev[g].get(), GGML_BACKEND_BUFFER_USAGE_WEIGHTS); + ggml_backend_buffer_clear(buf_dev[g].get(), 0); + + // sentinel mask: 1.0 for real slots, 0.0 for the sentinel plane, so + // sentinel-routed hot rows are zeroed after the GPU mul_mat_id. + std::vector mask_h(local_slots + 1, 1.0f); + mask_h[local_slots] = 0.0f; + for (int il = 0; il < n_layers; il++) { + ggml_backend_tensor_set(luts[il].mask_lut[g], mask_h.data(), 0, + (local_slots + 1) * sizeof(float)); + } + } + + // CPU context for the cold_mask tensors ggml_init_params params_cpu = { /*.mem_size =*/ ggml_tensor_overhead() * (2 * n_layers) + 1024 * 1024, /*.mem_buffer =*/ nullptr, /*.no_alloc =*/ true, }; ctx_cpu = ggml_context_ptr(ggml_init(params_cpu)); - - // one hot tensor per expert weight tensor: hot_s expert slot planes plus - // a zeroed sentinel plane (index hot_s), so cold selections read zero - // through a valid in-range index. - for (auto & e : entries) { - e.dst = ggml_new_tensor_3d(ctx.get(), e.src->type, e.src->ne[0], e.src->ne[1], hot_s + 1); - } - - // per-layer LUTs and masks for in-graph routing. - // hot_lut i32, cold_mask i32, both [n_experts]. - luts.assign(n_layers, layer_lut{}); for (int il = 0; il < n_layers; il++) { - luts[il].hot_lut = ggml_new_tensor_2d(ctx.get(), GGML_TYPE_I32, 1, n_experts); luts[il].cold_mask = ggml_new_tensor_1d(ctx_cpu.get(), GGML_TYPE_I32, n_experts); } - - // check whether the buffer would fit before committing any VRAM - const size_t need = ggml_backend_alloc_ctx_tensors_from_buft_size(ctx.get(), gpu_buft); - if (need == 0) { - LLAMA_LOG_ERROR("%s: hot store: zero-sized buffer, disabled\n", __func__); - ctx.reset(); - ctx_cpu.reset(); - return false; - } - - size_t free_mem = 0, total_mem = 0; - ggml_backend_dev_t dev = ggml_backend_buft_get_device(gpu_buft); - if (dev) { - ggml_backend_dev_memory(dev, &free_mem, &total_mem); - } - if (dev && free_mem < need) { - throw std::runtime_error(format("%s: not enough memory to allocate the GPU hot store of %d slots (%zu MiB needed, %zu MiB free on %s)", - __func__, hot_s, need / (1024 * 1024), free_mem / (1024 * 1024), - ggml_backend_dev_name(dev))); - } - - ggml_backend_buffer_t b = ggml_backend_alloc_ctx_tensors_from_buft(ctx.get(), gpu_buft); - if (b == nullptr) { - throw std::runtime_error(format("%s: unable to allocate hot store buffer of %d slots (%zu MiB)", - __func__, hot_s, need / (1024 * 1024))); - } - buf = ggml_backend_buffer_ptr(b); - ggml_backend_buffer_set_usage(buf.get(), GGML_BACKEND_BUFFER_USAGE_WEIGHTS); - ggml_backend_buffer_type_t cpu_buft = ggml_backend_cpu_buffer_type(); ggml_backend_buffer_t b_cpu = ggml_backend_alloc_ctx_tensors_from_buft(ctx_cpu.get(), cpu_buft); if (b_cpu) { @@ -138,16 +181,11 @@ bool llama_expert_hotstore::allocate(ggml_backend_buffer_type_t gpu_buft) { ggml_backend_buffer_set_usage(buf_cpu.get(), GGML_BACKEND_BUFFER_USAGE_WEIGHTS); } - // zero the whole buffer so the sentinel slot (index hot_s) AND every - // not-yet-filled expert slot is zero; copy_top_s/resync_top_s only write - // slots 0..hot_s-1, so slot hot_s stays zero for the lifetime of the store. - ggml_backend_buffer_clear(buf.get(), 0); - // register each expert weight tensor with the tier hook so build_lora_mm_id - // can find its GPU hot tensor and per-layer LUTs. + // can find its per-device GPU hot tensors and per-device LUTs. for (const auto & e : entries) { const auto & L = luts[e.layer_idx]; - llama_expert_tier_register(e.src, e.dst, L.hot_lut, L.cold_mask); + llama_expert_tier_register(e.src, e.dst, L.hot_lut, L.mask_lut, L.cold_mask); } return true; @@ -157,9 +195,19 @@ llama_expert_hotstore::~llama_expert_hotstore() { llama_expert_tier_clear(); } -void llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { - if (is_filled || hot_s <= 0 || entries.empty() || !buf) { - return; +// device owning a global slot index, or -1 (slot ranges are contiguous) +static int slot_device(const std::vector & slot_start, const std::vector & slot_end, int p) { + for (int g = 0; g < (int) slot_start.size(); g++) { + if (p >= slot_start[g] && p < slot_end[g]) { + return g; + } + } + return -1; +} + +bool llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { + if (is_filled || hot_s <= 0 || entries.empty() || buf_dev.empty()) { + return false; } for (int il = 0; il < n_layers; il++) { @@ -182,7 +230,11 @@ void llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { if (ex < 0) { continue; } - ggml_backend_tensor_set(e->dst, src + (size_t) ex * slot, (size_t) p * slot, slot); + const int g = slot_device(slot_start, slot_end, p); + if (g < 0) { + continue; + } + ggml_backend_tensor_set(e->dst[g], src + (size_t) ex * slot, (size_t) (p - slot_start[g]) * slot, slot); } } } @@ -191,21 +243,32 @@ void llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { is_filled = true; update_luts(); LLAMA_LOG("=== Expert hot store: top-S experts copied to GPU ===\n"); + return true; } -void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { - if (!is_filled || hot_s <= 0 || !buf) { - return; +bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { + if (!is_filled || hot_s <= 0 || buf_dev.empty()) { + return false; } // tokens elapsed since the previous sync, used to age dwell counters const int64_t elapsed = heatmap.tokens_total - last_sync_tokens; int swapped = 0; for (int il = 0; il < n_layers; il++) { - const std::vector top = heatmap.get_top_s(il, hot_s); auto & ste = slot_to_expert[il]; auto & dc = dwell_count[il]; + // mark the resident experts so the top-S candidates below can be + // filtered to non-residents + std::vector resident_set(n_experts, 0); + for (int p = 0; p < hot_s; p++) { + if (ste[p] >= 0) { + resident_set[ste[p]] = 1; + } + } + + const std::vector top = heatmap.get_top_s(il, hot_s); + // find a free slot index (guard: any resident displacement must // clear the hysteresis gate, unless the gate is off) auto find_slot = [&](int e_cold) -> int { @@ -249,14 +312,6 @@ void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { return p_worst; }; - // mark the resident experts so the top-S candidates below can be - // filtered to non-residents; at most one swap per layer per sync - std::vector resident_set(n_experts, 0); - for (int p = 0; p < hot_s; p++) { - if (ste[p] >= 0) { - resident_set[ste[p]] = 1; - } - } int swapped_in_layer = 0; for (int e_cold : top) { if (swapped_in_layer >= 1) { @@ -275,7 +330,11 @@ void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { if (!src) { continue; } - ggml_backend_tensor_set(ent->dst, src + (size_t) e_cold * slot, (size_t) p * slot, slot); + const int g = slot_device(slot_start, slot_end, p); + if (g < 0) { + continue; + } + ggml_backend_tensor_set(ent->dst[g], src + (size_t) e_cold * slot, (size_t) (p - slot_start[g]) * slot, slot); } ste[p] = e_cold; dc[p] = -elapsed; // fresh dwell: aging below brings it to 0 @@ -297,16 +356,18 @@ void llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { LLAMA_LOG("=== Expert hot store: re-sync swapped %d expert slots ===\n", swapped); } } + return swapped > 0; } -void llama_expert_hotstore::maybe_resync(const llama_expert_heatmap & heatmap, bool multi_slot) { +bool llama_expert_hotstore::maybe_resync(const llama_expert_heatmap & heatmap, bool multi_slot) { // n_tokens>1 (multi-slot) freezes the hot store: no swapping during the batch if (multi_slot || sync_period <= 0 || heatmap.tokens_total <= 0) { - return; + return false; } if (heatmap.tokens_total / sync_period > last_sync_tokens / sync_period) { - resync_top_s(heatmap); + return resync_top_s(heatmap); } + return false; } int llama_expert_hotstore::slot_of(int layer_idx, int expert_id) const { @@ -323,35 +384,44 @@ int llama_expert_hotstore::slot_of(int layer_idx, int expert_id) const { } void llama_expert_hotstore::update_luts() { - if (hot_s <= 0 || luts.empty() || !buf) { + if (hot_s <= 0 || luts.empty() || buf_dev.empty()) { return; } - std::vector hot_lut_h(n_experts); std::vector cold_mask_h(n_experts); for (int il = 0; il < n_layers; il++) { const auto & ste = slot_to_expert[il]; + // per-device LUTs: an expert whose global slot is on device g maps to + // the LOCAL slot index there; everything else maps to that device's + // local sentinel slot (zero contribution). + for (int g = 0; g < n_devices; g++) { + const int local_slots = slot_end[g] - slot_start[g]; + std::vector hot_lut_h(n_experts, local_slots); + for (int p = slot_start[g]; p < slot_end[g]; p++) { + const int e = ste[p]; + if (e >= 0 && e < n_experts) { + hot_lut_h[e] = p - slot_start[g]; + } + } + ggml_backend_tensor_set(luts[il].hot_lut[g], hot_lut_h.data(), 0, + n_experts * sizeof(int32_t)); + } + // defaults: everyone cold for (int e = 0; e < n_experts; e++) { - hot_lut_h[e] = hot_s; // sentinel slot (zero) cold_mask_h[e] = 1; } - // residents override for (int p = 0; p < hot_s; p++) { const int e = ste[p]; - if (e < 0) { - continue; + if (e >= 0 && e < n_experts) { + cold_mask_h[e] = 0; } - hot_lut_h[e] = p; // its slot index - cold_mask_h[e] = 0; } - - const size_t bytes_i32 = n_experts * sizeof(int32_t); - ggml_backend_tensor_set(luts[il].hot_lut, hot_lut_h.data(), 0, bytes_i32); - ggml_backend_tensor_set(luts[il].cold_mask, cold_mask_h.data(), 0, bytes_i32); + ggml_backend_tensor_set(luts[il].cold_mask, cold_mask_h.data(), 0, + n_experts * sizeof(int32_t)); } } @@ -386,19 +456,22 @@ void llama_expert_hotstore::log_hit_rate(const std::vector 0) { LLAMA_LOG(" hot store DISABLED (%d slots requested)\n", hot_s); } diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index 06fcb0dcdda..25d993f24b6 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -21,12 +21,12 @@ struct llama_expert_hotstore { // expert weight tensors (gate/up/down, incl. chexps variants) std::vector bytes_per_slot; - // one hot tensor per expert weight tensor, shape {ne0, ne1, hot_s + 1}; - // the last plane is the zeroed sentinel slot + // one hot tensor per expert weight tensor per device, shape {ne0, ne1, + // local_slots_g + 1}; the last plane is the zeroed sentinel slot struct entry { int layer_idx; ggml_tensor* src; // model tensor holding all n_experts slices - ggml_tensor* dst; // hot tensor holding hot_s slots + std::vector dst; // per-device hot tensors }; std::vector entries; @@ -38,17 +38,24 @@ struct llama_expert_hotstore { std::vector> slot_to_expert; // per-layer LUT and mask for in-graph routing. - // hot_lut[e] = slot index [0..hot_s-1] if e is hot, or hot_s (sentinel) if cold. - // cold_mask[e] = 1 if e is cold, else 0 (read as int zero-check by mul_mat_id_cold). + // hot_lut[g][e] = LOCAL slot index if e is hot on device g, else the + // device's local sentinel slot (zero contribution). + // cold_mask[e] = 1 if e is cold, else 0 (read as int zero-check by + // mul_mat_id_cold). struct layer_lut { - ggml_tensor * hot_lut = nullptr; // i32[n_experts] - ggml_tensor * cold_mask = nullptr; // i32[n_experts] + std::vector hot_lut; // per-device i32[n_experts] + std::vector mask_lut; // per-device f32[local_slots+1], 0 at sentinel + ggml_tensor * cold_mask = nullptr; // i32[n_experts] }; std::vector luts; // size n_layers - // keeps the GPU buffer (and its no_alloc context) alive - ggml_context_ptr ctx; - ggml_backend_buffer_ptr buf; + // per-device hot store: each device owns a contiguous slot range and its + // own no_alloc context + GPU buffer (dst tensors and hot_luts inside). + int n_devices = 1; + std::vector slot_start; // per-device slot range start (inclusive) + std::vector slot_end; // per-device slot range end (exclusive) + std::vector ctx_dev; + std::vector buf_dev; // CPU context and buffer for host-side tensors (like cold_mask) ggml_context_ptr ctx_cpu; @@ -75,21 +82,28 @@ llama_expert_hotstore(const llama_model * model, int n_layers, ~llama_expert_hotstore(); - // allocate the GPU hot store for `hot_s` slots. returns false (and - // leaves the store disabled) on failure or shortage of VRAM. - bool allocate(ggml_backend_buffer_type_t gpu_buft); + // allocate the GPU hot store for `hot_s` slots, split across the given + // device buffer types by tensor_split (fractions, one per device). returns + // false (and leaves the store disabled) on failure or shortage of VRAM. + bool allocate(const std::vector & bufts, + const float * tensor_split, int n_split); // copy the top-S expert slices for every layer into the GPU hot store, // using the given heatmap for the ranking. one-shot (guarded by is_filled). - void copy_top_s(const llama_expert_heatmap & heatmap); + // copy the top-S expert slices for every layer into the GPU hot store, + // using the given heatmap for the ranking. one-shot (guarded by is_filled). + // returns true if a fill happened (caller should synchronize the GPU). + bool copy_top_s(const llama_expert_heatmap & heatmap); // re-sync the hot store to the current heatmap ranking, swapping only // the experts that changed (stable slots; unchanged experts not re-copied). - void resync_top_s(const llama_expert_heatmap & heatmap); + // returns true if any slot changed (caller should synchronize the GPU). + bool resync_top_s(const llama_expert_heatmap & heatmap); // cadence-gated wrapper: re-sync only if tokens_total crossed sync_period; - // multi_slot freezes the hot store (static slots, no swapping) - void maybe_resync(const llama_expert_heatmap & heatmap, bool multi_slot); + // multi_slot freezes the hot store (static slots, no swapping). returns + // true if a re-sync ran and swapped slots. + bool maybe_resync(const llama_expert_heatmap & heatmap, bool multi_slot); // returns the GPU slot index holding expert_id in layer il, or -1 if none int slot_of(int layer_idx, int expert_id) const; diff --git a/src/llama-expert-tier.cpp b/src/llama-expert-tier.cpp index 092b1fa10d0..693cec8c9bf 100644 --- a/src/llama-expert-tier.cpp +++ b/src/llama-expert-tier.cpp @@ -5,8 +5,9 @@ namespace { struct tier_entry { - ggml_tensor * dst_hot; - ggml_tensor * hot_lut; + std::vector dst_hot; // per-device hot tensors + std::vector hot_lut; // per-device LUTs + std::vector mask_lut; // per-device sentinel masks ggml_tensor * cold_mask; }; @@ -15,11 +16,12 @@ namespace { } void llama_expert_tier_register(ggml_tensor * src, - ggml_tensor * dst_hot, - ggml_tensor * hot_lut, + const std::vector & dst_hot, + const std::vector & hot_lut, + const std::vector & mask_lut, ggml_tensor * cold_mask) { std::lock_guard lk(g_mtx); - g_table[src] = {dst_hot, hot_lut, cold_mask}; + g_table[src] = {dst_hot, hot_lut, mask_lut, cold_mask}; } void llama_expert_tier_clear() { @@ -73,10 +75,20 @@ ggml_tensor * llama_expert_tier_build(ggml_context * ctx, const int n_expert_used = (int) ids->ne[0]; const int n_tokens = (int) cur->ne[2]; - // hot: remap real expert ids to hot slot indices; cold experts map to the - // zeroed sentinel slot and contribute nothing on the GPU. - ggml_tensor * ids_hot = remap_ids(ctx, ent.hot_lut, ids, n_experts, n_expert_used, n_tokens); - ggml_tensor * hot = ggml_mul_mat_id(ctx, ent.dst_hot, cur, ids_hot); + // hot: for each device, remap real expert ids to that device's LOCAL slot + // indices; experts whose slot lives on another device (or are cold) map to + // this device's zeroed sentinel slot and contribute nothing. Sum the + // per-device results (the scheduler inserts any cross-device copies). + ggml_tensor * hot = nullptr; + for (size_t g = 0; g < ent.dst_hot.size(); g++) { + ggml_tensor * ids_hot = remap_ids(ctx, ent.hot_lut[g], ids, n_experts, n_expert_used, n_tokens); + ggml_tensor * h = ggml_mul_mat_id(ctx, ent.dst_hot[g], cur, ids_hot); + // zero the rows routed to the sentinel plane: index the mask LUT (0 + // at the sentinel) by ids_hot, repeat over the hidden dim, multiply + ggml_tensor * m = ggml_get_rows(ctx, ent.mask_lut[g], ids_hot); + h = ggml_mul(ctx, h, ggml_repeat(ctx, m, h)); + hot = hot ? ggml_add(ctx, hot, h) : h; + } // cold: dedicated CPU op that computes only the cold-selected experts, // skipping hot ones via the integer zero-check on cold_mask. diff --git a/src/llama-expert-tier.h b/src/llama-expert-tier.h index 79f3bb8409f..1c7ac2896f2 100644 --- a/src/llama-expert-tier.h +++ b/src/llama-expert-tier.h @@ -1,5 +1,7 @@ #pragma once +#include + #include "ggml.h" // Expert tier hook: drop-in replacement for ggml_mul_mat_id on expert weight @@ -23,12 +25,14 @@ // intentional approximation: applying it would add get_rows/mul nodes per // layer, and the scale factors are close to 1. -// register one expert weight tensor -> its GPU hot tensor and per-layer LUTs. -// Called by llama_expert_hotstore::allocate() after creating dst_hot and -// the LUT/mask tensors. Multiple entries per layer share the same luts[i]. +// register one expert weight tensor -> its per-device GPU hot tensors and +// per-device LUTs. called by llama_expert_hotstore::allocate() after creating +// dst_hot/hot_lut and the cold_mask tensors. multiple entries per layer share +// the same luts[i]. void llama_expert_tier_register(ggml_tensor * src, - ggml_tensor * dst_hot, - ggml_tensor * hot_lut, + const std::vector & dst_hot, + const std::vector & hot_lut, + const std::vector & mask_lut, ggml_tensor * cold_mask); // drop the entire table (called by hotstore destructor) diff --git a/tools/cli/README.md b/tools/cli/README.md index a9f9a455522..5754377cb97 100644 --- a/tools/cli/README.md +++ b/tools/cli/README.md @@ -69,6 +69,7 @@ | `--ecf, --expert-cache-force` | enable the expert cache on non-CUDA backends (testing/emergency only) | | `--expert-heat-decay N` | expert heatmap decay rate per update (default: 0.999)
(env: LLAMA_ARG_EXPERT_HEAT_DECAY) | | `--expert-heat-log-period N` | expert heatmap log interval in updates (default: 0, 0 = off)
(env: LLAMA_ARG_EXPERT_HEAT_LOG_PERIOD) | +| `--expert-sync-period N` | expert hot store re-sync cadence in tokens (default: 1)
(env: LLAMA_ARG_EXPERT_SYNC_PERIOD) | | `--expert-hyst N` | expert hot store hysteresis ratio (default: 1.3, 0 = off)
(env: LLAMA_ARG_EXPERT_HYST) | | `--expert-dwell N` | expert hot store minimum dwell updates before swap (default: 0, 0 = off)
(env: LLAMA_ARG_EXPERT_DWELL) | | `-ngl, --gpu-layers, --n-gpu-layers N` | max. number of layers to store in VRAM, either an exact number, 'auto', or 'all' (default: auto)
(env: LLAMA_ARG_N_GPU_LAYERS) | diff --git a/tools/completion/README.md b/tools/completion/README.md index 58df9a7430a..56b5ea9e3d2 100644 --- a/tools/completion/README.md +++ b/tools/completion/README.md @@ -152,6 +152,7 @@ llama-completion.exe -m models\gemma-1.1-7b-it.Q4_K_M.gguf --ignore-eos -n -1 | `--ecf, --expert-cache-force` | enable the expert cache on non-CUDA backends (testing/emergency only) | | `--expert-heat-decay N` | expert heatmap decay rate per update (default: 0.999)
(env: LLAMA_ARG_EXPERT_HEAT_DECAY) | | `--expert-heat-log-period N` | expert heatmap log interval in updates (default: 0, 0 = off)
(env: LLAMA_ARG_EXPERT_HEAT_LOG_PERIOD) | +| `--expert-sync-period N` | expert hot store re-sync cadence in tokens (default: 1)
(env: LLAMA_ARG_EXPERT_SYNC_PERIOD) | | `--expert-hyst N` | expert hot store hysteresis ratio (default: 1.3, 0 = off)
(env: LLAMA_ARG_EXPERT_HYST) | | `--expert-dwell N` | expert hot store minimum dwell updates before swap (default: 0, 0 = off)
(env: LLAMA_ARG_EXPERT_DWELL) | | `-ngl, --gpu-layers, --n-gpu-layers N` | max. number of layers to store in VRAM, either an exact number, 'auto', or 'all' (default: auto)
(env: LLAMA_ARG_N_GPU_LAYERS) | From e0efcb30bea064551e0fc8225a592231490afe36 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Thu, 6 Aug 2026 17:01:54 +0300 Subject: [PATCH 33/61] expert tier: add per-slice cpu pool for exps weights --- common/CMakeLists.txt | 2 +- common/arg.cpp | 4 ++ src/CMakeLists.txt | 1 + src/llama-expert-pool.cpp | 142 +++++++++++++++++++++++++++++++++++++ src/llama-expert-pool.h | 48 +++++++++++++ src/llama-model-loader.cpp | 26 +++++-- 6 files changed, 217 insertions(+), 6 deletions(-) create mode 100644 src/llama-expert-pool.cpp create mode 100644 src/llama-expert-pool.h diff --git a/common/CMakeLists.txt b/common/CMakeLists.txt index 799d227519f..0af436b54b6 100644 --- a/common/CMakeLists.txt +++ b/common/CMakeLists.txt @@ -41,7 +41,7 @@ configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE}) set(TARGET llama-common-base) add_library(${TARGET} STATIC ${OUTPUT_FILE}) -target_include_directories(${TARGET} PUBLIC .) +target_include_directories(${TARGET} PUBLIC . ../src) if (BUILD_SHARED_LIBS) set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON) diff --git a/common/arg.cpp b/common/arg.cpp index 78f4836dd30..43019ceed00 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -6,6 +6,7 @@ #include "download.h" #include "json-schema-to-grammar.h" #include "llama.h" +#include "llama-expert-pool.h" #include "log.h" #include "sampling.h" #include "speculative.h" @@ -2736,6 +2737,9 @@ common_params_context common_params_parser_init(common_params & params, llama_ex "-1 = autofit slots from free VRAM, 0 = disabled, N = manual top-N slots", [](common_params & params, int value) { params.expert_hot_s = value; + if (value != 0) { + llama_expert_pool::mark_requested(); + } } ).set_env("LLAMA_ARG_EXPERT_HOT_S")); add_opt(common_arg( diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt index 009d0215152..b5632a43b55 100644 --- a/src/CMakeLists.txt +++ b/src/CMakeLists.txt @@ -19,6 +19,7 @@ add_library(llama llama-cparams.cpp llama-expert-heatmap.cpp llama-expert-hotstore.cpp + llama-expert-pool.cpp llama-expert-tier.cpp llama-grammar.cpp llama-graph.cpp diff --git a/src/llama-expert-pool.cpp b/src/llama-expert-pool.cpp new file mode 100644 index 00000000000..c3d4abe7a2a --- /dev/null +++ b/src/llama-expert-pool.cpp @@ -0,0 +1,142 @@ +#include "llama-expert-pool.h" + +#include +#include +#include + +namespace llama_expert_pool { + +namespace { + bool g_requested = false; + + // matches an expert weight tensor, e.g. blk.0.ffn_gate_exps.weight + const std::regex g_re_exps("blk\\.(\\d+)\\.ffn_(up|down|gate|gate_up)_(ch|)exps\\.weight"); + + struct store { + std::vector entries; + // per entry: per-expert slice pointers (nullptr = freed / on GPU) + std::vector> slices; + // number of experts per entry (from registration) + std::vector n_experts; + bool is_active = false; + }; + + store g_store; +} + +void mark_requested() { + g_requested = true; +} + +bool requested() { + return g_requested; +} + +bool match_exps(const char * name, int & layer_idx) { + if (!name) { + return false; + } + std::cmatch m; + if (!std::regex_search(name, m, g_re_exps)) { + return false; + } + layer_idx = std::stoi(m[1].str()); + return true; +} + +bool register_tensor(const ggml_tensor * tensor, int layer_idx, int n_experts, size_t slice_bytes) { + if (!g_requested || !tensor || n_experts <= 0 || slice_bytes == 0) { + return false; + } + for (size_t i = 0; i < g_store.entries.size(); i++) { + if (g_store.entries[i].tensor == tensor) { + return true; // already registered + } + } + g_store.entries.push_back({tensor, layer_idx, slice_bytes}); + g_store.n_experts.push_back(n_experts); + g_store.slices.emplace_back(n_experts, nullptr); + return true; +} + +bool fill_tensor(const ggml_tensor * tensor, const uint8_t * data, size_t nbytes) { + if (!g_requested || !tensor || !data) { + return false; + } + for (size_t i = 0; i < g_store.entries.size(); i++) { + if (g_store.entries[i].tensor != tensor) { + continue; + } + const size_t slice_bytes = g_store.entries[i].slice_bytes; + const int n_experts = g_store.n_experts[i]; + if (nbytes != (size_t) n_experts * slice_bytes) { + return false; + } + g_store.is_active = true; + for (int e = 0; e < n_experts; e++) { + uint8_t * slice = (uint8_t *) std::malloc(slice_bytes); + if (!slice) { + return false; + } + std::memcpy(slice, data + (size_t) e * slice_bytes, slice_bytes); + g_store.slices[i][e] = slice; + } + return true; + } + return false; +} + +bool active() { + return g_store.is_active; +} + +size_t num_entries() { + return g_store.entries.size(); +} + +const entry & get_entry(size_t idx) { + return g_store.entries[idx]; +} + +uint8_t * get_slice(size_t entry_idx, int expert) { + if (entry_idx >= g_store.slices.size()) { + return nullptr; + } + auto & slices = g_store.slices[entry_idx]; + if (expert < 0 || expert >= (int) slices.size()) { + return nullptr; + } + return slices[expert]; +} + +void free_slice(size_t entry_idx, int expert) { + if (entry_idx >= g_store.slices.size()) { + return; + } + auto & slices = g_store.slices[entry_idx]; + if (expert < 0 || expert >= (int) slices.size()) { + return; + } + std::free(slices[expert]); + slices[expert] = nullptr; +} + +void set_slice(size_t entry_idx, int expert, const uint8_t * data) { + if (entry_idx >= g_store.slices.size()) { + return; + } + auto & slices = g_store.slices[entry_idx]; + if (expert < 0 || expert >= (int) slices.size()) { + return; + } + const size_t slice_bytes = g_store.entries[entry_idx].slice_bytes; + uint8_t * slice = (uint8_t *) std::malloc(slice_bytes); + if (!slice) { + return; + } + std::memcpy(slice, data, slice_bytes); + std::free(slices[expert]); // replace any existing + slices[expert] = slice; +} + +} // namespace llama_expert_pool diff --git a/src/llama-expert-pool.h b/src/llama-expert-pool.h new file mode 100644 index 00000000000..2a7813aa399 --- /dev/null +++ b/src/llama-expert-pool.h @@ -0,0 +1,48 @@ +#pragma once + +#include +#include +#include + +struct ggml_tensor; + +// per-slice CPU store for the MoE expert weights. when the tier is active +// (--expert-hot-s set) and the model is loaded without mmap, the loader routes +// each exps tensor's bytes into per-expert allocations here instead of the +// model buffer, so a slice can be physically freed when its expert moves to +// the GPU. mmap loads keep the file-backed weights and use logical removal +// instead (the store stays inactive). +// +// lifecycle: +// common/arg.cpp -> mark_requested() when -ehs is parsed +// loader -> register_tensor() + fill_tensor() per exps tensor +// hotstore ctor -> attach(), then get/free/set slices for moves +namespace llama_expert_pool { + + void mark_requested(); + bool requested(); + + // true if `name` matches an exps weight tensor; sets layer_idx on match + bool match_exps(const char * name, int & layer_idx); + + // one registered exps weight tensor (e.g. blk.3.ffn_gate_exps.weight) + struct entry { + const ggml_tensor * tensor; + int layer_idx; + size_t slice_bytes; // bytes of a single expert slice + }; + + bool register_tensor(const ggml_tensor * tensor, int layer_idx, int n_experts, size_t slice_bytes); + // split `data` (nbytes = n_experts * slice_bytes) into per-expert slices + bool fill_tensor(const ggml_tensor * tensor, const uint8_t * data, size_t nbytes); + + bool active(); + size_t num_entries(); + const entry & get_entry(size_t idx); + + // slice access; returns nullptr if the slice is currently freed (on GPU) + uint8_t * get_slice(size_t entry_idx, int expert); + void free_slice(size_t entry_idx, int expert); + void set_slice(size_t entry_idx, int expert, const uint8_t * data); + +} // namespace llama_expert_pool diff --git a/src/llama-model-loader.cpp b/src/llama-model-loader.cpp index b31e92e2da7..be836042869 100644 --- a/src/llama-model-loader.cpp +++ b/src/llama-model-loader.cpp @@ -1,4 +1,5 @@ #include "llama-model-loader.h" +#include "llama-expert-pool.h" #include "ggml-alloc.h" #include "ggml.h" @@ -1384,11 +1385,26 @@ void llama_model_loader::load_data_for(struct ggml_tensor * cur) const { memcpy(cur->data, (uint8_t *)mapping->addr() + w.offs, ggml_nbytes(cur)); } } else { - GGML_ASSERT(cur->data != nullptr); - GGML_ASSERT(w.idx < files.size()); - const auto & file = files.at(w.idx); - file->seek(w.offs, SEEK_SET); - file->read_raw(cur->data, ggml_nbytes(cur)); + int il = -1; + if (llama_expert_pool::requested() && llama_expert_pool::match_exps(ggml_get_name(cur), il)) { + // tier + no-mmap: route the exps into the per-slice pool as well, + // so slices can be physically freed when moved to the GPU. + GGML_ASSERT(cur->data != nullptr); + const auto & file = files.at(w.idx); + file->seek(w.offs, SEEK_SET); + const size_t nbytes = ggml_nbytes(cur); + std::vector buf(nbytes); + file->read_raw(buf.data(), nbytes); + std::memcpy(cur->data, buf.data(), nbytes); + llama_expert_pool::register_tensor(cur, il, (int) cur->ne[2], nbytes / (size_t) cur->ne[2]); + llama_expert_pool::fill_tensor(cur, buf.data(), nbytes); + } else { + GGML_ASSERT(cur->data != nullptr); + GGML_ASSERT(w.idx < files.size()); + const auto & file = files.at(w.idx); + file->seek(w.offs, SEEK_SET); + file->read_raw(cur->data, ggml_nbytes(cur)); + } } if (check_tensors && !ggml_validate_row_data(cur->type, cur->data, ggml_nbytes(cur))) { From e3004a9fa143e68ff466aa09c419419a73dee044 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Thu, 6 Aug 2026 17:17:47 +0300 Subject: [PATCH 34/61] expert tier: cold op reads slices from the per-slice pool --- ggml/include/ggml-cpu.h | 7 ++++++ ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c | 20 +++++++++++++++- src/llama-expert-pool.cpp | 25 ++++++++++++++++++++ src/llama-expert-pool.h | 4 ++++ 4 files changed, 55 insertions(+), 1 deletion(-) diff --git a/ggml/include/ggml-cpu.h b/ggml/include/ggml-cpu.h index dc6453c6eaa..fda42efbe73 100644 --- a/ggml/include/ggml-cpu.h +++ b/ggml/include/ggml-cpu.h @@ -147,6 +147,13 @@ extern "C" { GGML_BACKEND_API void ggml_cpu_fp32_to_bf16(const float *, ggml_bf16_t *, int64_t); GGML_BACKEND_API void ggml_cpu_bf16_to_fp32(const ggml_bf16_t *, float *, int64_t); + // optional per-expert slice source for the MoE cold op. when set, the op + // reads expert slices from the hook instead of src0->data (used by the + // llama expert pool). return nullptr to fall back to the tensor's data. + typedef const uint8_t * (*ggml_mmid_cold_slice_fn)(const struct ggml_tensor * src0, int expert); + GGML_BACKEND_API void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn); + GGML_BACKEND_API ggml_mmid_cold_slice_fn ggml_mmid_cold_get_slice_fn(void); + #ifdef __cplusplus } #endif diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c index 22bda0da6f5..fbf3df770d5 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c @@ -18,6 +18,16 @@ #include #include #include + +static ggml_mmid_cold_slice_fn g_slice_fn = NULL; + +void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn) { + g_slice_fn = fn; +} + +ggml_mmid_cold_slice_fn ggml_mmid_cold_get_slice_fn(void) { + return g_slice_fn; +} #include #include @@ -170,7 +180,15 @@ void ggml_compute_forward_mul_mat_id_cold( continue; } - const char * src0_cur = (const char *) src0->data + cur_a * nb02; + // prefer the registered per-expert slice source (expert pool), else + // read from the tensor's own contiguous data + const char * src0_cur; + if (g_slice_fn) { + const uint8_t * s = g_slice_fn(src0, (int) cur_a); + src0_cur = s ? (const char *) s : (const char *) src0->data + cur_a * nb02; + } else { + src0_cur = (const char *) src0->data + cur_a * nb02; + } const void * wdata = (src1->type == vec_dot_type) ? src1->data : params->wdata; const size_t row_size = ggml_row_size(vec_dot_type, ne10); diff --git a/src/llama-expert-pool.cpp b/src/llama-expert-pool.cpp index c3d4abe7a2a..e9322871675 100644 --- a/src/llama-expert-pool.cpp +++ b/src/llama-expert-pool.cpp @@ -1,5 +1,8 @@ #include "llama-expert-pool.h" +#include "ggml.h" +#include "ggml-cpu.h" + #include #include #include @@ -9,6 +12,11 @@ namespace llama_expert_pool { namespace { bool g_requested = false; + // C callback for the ggml cold op: resolve a per-expert slice by tensor + static const uint8_t * pool_slice_cb(const struct ggml_tensor * src0, int expert) { + return slice_for_tensor(src0, expert); + } + // matches an expert weight tensor, e.g. blk.0.ffn_gate_exps.weight const std::regex g_re_exps("blk\\.(\\d+)\\.ffn_(up|down|gate|gate_up)_(ch|)exps\\.weight"); @@ -73,6 +81,7 @@ bool fill_tensor(const ggml_tensor * tensor, const uint8_t * data, size_t nbytes return false; } g_store.is_active = true; + ggml_mmid_cold_set_slice_fn(pool_slice_cb); for (int e = 0; e < n_experts; e++) { uint8_t * slice = (uint8_t *) std::malloc(slice_bytes); if (!slice) { @@ -109,6 +118,22 @@ uint8_t * get_slice(size_t entry_idx, int expert) { return slices[expert]; } +const uint8_t * slice_for_tensor(const ggml_tensor * tensor, int expert) { + if (!g_store.is_active || !tensor || expert < 0) { + return nullptr; + } + for (size_t i = 0; i < g_store.entries.size(); i++) { + if (g_store.entries[i].tensor == tensor) { + auto & slices = g_store.slices[i]; + if (expert >= (int) slices.size()) { + return nullptr; + } + return slices[expert]; + } + } + return nullptr; +} + void free_slice(size_t entry_idx, int expert) { if (entry_idx >= g_store.slices.size()) { return; diff --git a/src/llama-expert-pool.h b/src/llama-expert-pool.h index 2a7813aa399..4e14cb2dc32 100644 --- a/src/llama-expert-pool.h +++ b/src/llama-expert-pool.h @@ -45,4 +45,8 @@ namespace llama_expert_pool { void free_slice(size_t entry_idx, int expert); void set_slice(size_t entry_idx, int expert, const uint8_t * data); + // C-accessible lookup by tensor (for the ggml cold op hook); returns + // nullptr when the pool is inactive or the slice is freed + const uint8_t * slice_for_tensor(const ggml_tensor * tensor, int expert); + } // namespace llama_expert_pool From 09b1e45e191a7d34c5794a618d9b96cc7a274e68 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Thu, 6 Aug 2026 18:27:20 +0300 Subject: [PATCH 35/61] expert tier: count+rank batching and native memory moves --- common/CMakeLists.txt | 2 +- common/arg.cpp | 4 - ggml/include/ggml-cpu.h | 7 - ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c | 20 +-- ggml/src/ggml-cuda/mmf.cu | 2 +- ggml/src/ggml-cuda/mmid.cu | 85 +++++++--- ggml/src/ggml-cuda/mmid.cuh | 2 +- ggml/src/ggml-cuda/mmq.cu | 11 +- src/CMakeLists.txt | 1 - src/llama-expert-hotstore.cpp | 58 ++++++- src/llama-expert-pool.cpp | 167 ------------------- src/llama-expert-pool.h | 52 ------ src/llama-expert-tier.cpp | 13 +- src/llama-model-loader.cpp | 26 +-- 14 files changed, 133 insertions(+), 317 deletions(-) delete mode 100644 src/llama-expert-pool.cpp delete mode 100644 src/llama-expert-pool.h diff --git a/common/CMakeLists.txt b/common/CMakeLists.txt index 0af436b54b6..799d227519f 100644 --- a/common/CMakeLists.txt +++ b/common/CMakeLists.txt @@ -41,7 +41,7 @@ configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE}) set(TARGET llama-common-base) add_library(${TARGET} STATIC ${OUTPUT_FILE}) -target_include_directories(${TARGET} PUBLIC . ../src) +target_include_directories(${TARGET} PUBLIC .) if (BUILD_SHARED_LIBS) set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON) diff --git a/common/arg.cpp b/common/arg.cpp index 43019ceed00..78f4836dd30 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -6,7 +6,6 @@ #include "download.h" #include "json-schema-to-grammar.h" #include "llama.h" -#include "llama-expert-pool.h" #include "log.h" #include "sampling.h" #include "speculative.h" @@ -2737,9 +2736,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex "-1 = autofit slots from free VRAM, 0 = disabled, N = manual top-N slots", [](common_params & params, int value) { params.expert_hot_s = value; - if (value != 0) { - llama_expert_pool::mark_requested(); - } } ).set_env("LLAMA_ARG_EXPERT_HOT_S")); add_opt(common_arg( diff --git a/ggml/include/ggml-cpu.h b/ggml/include/ggml-cpu.h index fda42efbe73..dc6453c6eaa 100644 --- a/ggml/include/ggml-cpu.h +++ b/ggml/include/ggml-cpu.h @@ -147,13 +147,6 @@ extern "C" { GGML_BACKEND_API void ggml_cpu_fp32_to_bf16(const float *, ggml_bf16_t *, int64_t); GGML_BACKEND_API void ggml_cpu_bf16_to_fp32(const ggml_bf16_t *, float *, int64_t); - // optional per-expert slice source for the MoE cold op. when set, the op - // reads expert slices from the hook instead of src0->data (used by the - // llama expert pool). return nullptr to fall back to the tensor's data. - typedef const uint8_t * (*ggml_mmid_cold_slice_fn)(const struct ggml_tensor * src0, int expert); - GGML_BACKEND_API void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn); - GGML_BACKEND_API ggml_mmid_cold_slice_fn ggml_mmid_cold_get_slice_fn(void); - #ifdef __cplusplus } #endif diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c index fbf3df770d5..22bda0da6f5 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c @@ -18,16 +18,6 @@ #include #include #include - -static ggml_mmid_cold_slice_fn g_slice_fn = NULL; - -void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn) { - g_slice_fn = fn; -} - -ggml_mmid_cold_slice_fn ggml_mmid_cold_get_slice_fn(void) { - return g_slice_fn; -} #include #include @@ -180,15 +170,7 @@ void ggml_compute_forward_mul_mat_id_cold( continue; } - // prefer the registered per-expert slice source (expert pool), else - // read from the tensor's own contiguous data - const char * src0_cur; - if (g_slice_fn) { - const uint8_t * s = g_slice_fn(src0, (int) cur_a); - src0_cur = s ? (const char *) s : (const char *) src0->data + cur_a * nb02; - } else { - src0_cur = (const char *) src0->data + cur_a * nb02; - } + const char * src0_cur = (const char *) src0->data + cur_a * nb02; const void * wdata = (src1->type == vec_dot_type) ? src1->data : params->wdata; const size_t row_size = ggml_row_size(vec_dot_type, ne10); diff --git a/ggml/src/ggml-cuda/mmf.cu b/ggml/src/ggml-cuda/mmf.cu index 646a5899c80..f60be42e856 100644 --- a/ggml/src/ggml-cuda/mmf.cu +++ b/ggml/src/ggml-cuda/mmf.cu @@ -85,7 +85,7 @@ void ggml_cuda_mul_mat_f(ggml_backend_cuda_context & ctx, const ggml_tensor * sr GGML_ASSERT(sis1 > 0); ggml_cuda_launch_mm_ids_helper(ids_d, ids_src_compact_dev.get(), ids_dst_compact_dev.get(), expert_bounds_dev.get(), - static_cast(n_experts), static_cast(n_tokens), static_cast(n_expert_used), static_cast(ne11), si1, sis1, /*write_inverse =*/ false, ctx.stream()); + static_cast(n_experts), static_cast(n_tokens), static_cast(n_expert_used), static_cast(ne11), si1, sis1, false, ctx.stream(), false); CUDA_CHECK(cudaGetLastError()); ids_info.ids_src_compact = ids_src_compact_dev.get(); diff --git a/ggml/src/ggml-cuda/mmid.cu b/ggml/src/ggml-cuda/mmid.cu index f80442fbe4e..e2dbca2ba0f 100644 --- a/ggml/src/ggml-cuda/mmid.cu +++ b/ggml/src/ggml-cuda/mmid.cu @@ -39,23 +39,37 @@ static __global__ void mm_ids_helper( int it_compact = 0; // Running index for the compact slice of this expert. if constexpr (n_expert_used_template == 0) { - // Generic implementation: + // Generic implementation. With expert tiering, several slots of one + // token can map to the same (sentinel) expert, so count hits per + // token and give each hitting lane its own store slot via its rank. for (int it = 0; it < n_tokens; ++it) { - int iex_used = -1; // The index at which the expert is used, if any. + int cnt = 0; for (int iex = threadIdx.x; iex < n_expert_used; iex += warp_size) { const int expert_used = ids[it*si1 + iex]; nex_prev += expert_used < expert; - if (expert_used == expert) { - iex_used = iex; - } + cnt += expert_used == expert; } - if (iex_used != -1) { - store[it_compact] = mm_ids_helper_store(it, iex_used); + // inclusive warp scan of cnt; n_hit broadcast from the last lane + int rank = cnt; +#pragma unroll + for (int offset = 1; offset < warp_size; offset <<= 1) { + const int tmp = __shfl_up_sync(0xFFFFFFFF, rank, offset, warp_size); + if (threadIdx.x >= static_cast(offset)) { + rank += tmp; + } } - - if (warp_reduce_any(iex_used != -1)) { - it_compact++; + const int n_hit = __shfl_sync(0xFFFFFFFF, rank, warp_size - 1, warp_size); + rank -= cnt; // exclusive scan: hits held by lower lanes + + if (n_hit > 0) { + for (int iex = threadIdx.x; iex < n_expert_used; iex += warp_size) { + if (ids[it*si1 + iex] == expert) { + store[it_compact + rank] = mm_ids_helper_store(it, iex); + rank++; + } + } + it_compact += n_hit; } } } else { @@ -68,28 +82,43 @@ static __global__ void mm_ids_helper( const int iex = threadIdx.x % neu_padded; // The index at which the expert is used, if any. const int expert_used = (neu_padded == n_expert_used || iex < n_expert_used) && it < n_tokens ? ids[it*si1 + iex] : INT_MAX; - const int iex_used = expert_used == expert ? iex : -1; + const bool hit = expert_used == expert; nex_prev += expert_used < expert; - // Whether the threads at this token position have used the expert: - const int it_compact_add_self = warp_reduce_any(iex_used != -1); + // With expert tiering, several slots of one token can map to the same + // (sentinel) expert, so count hits per token instead of "any" and give + // each hitting lane its own store slot via its rank within the token. + + // Inclusive scan of hit within the token's subgroup of lanes: + int scan = hit ? 1 : 0; +#pragma unroll + for (int offset = 1; offset < neu_padded; offset <<= 1) { + const int tmp = __shfl_up_sync(0xFFFFFFFF, scan, offset, warp_size); + if ((threadIdx.x % neu_padded) >= static_cast(offset)) { + scan += tmp; + } + } + + // Hits of this token; rank of this lane among the token's hitting lanes: + const int n_hit = __shfl_sync(0xFFFFFFFF, scan, threadIdx.x | (neu_padded - 1), warp_size); + const int rank = scan - 1; // Do a scan over threads at lower token positions in warp to get the correct index for writing data: int it_compact_add_lower = 0; #pragma unroll for (int offset = neu_padded; offset < warp_size; offset += neu_padded) { - const int tmp = __shfl_up_sync(0xFFFFFFFF, it_compact_add_self, offset, warp_size); + const int tmp = __shfl_up_sync(0xFFFFFFFF, n_hit, offset, warp_size); if (threadIdx.x >= static_cast(offset)) { it_compact_add_lower += tmp; } } - if (iex_used != -1) { - store[it_compact + it_compact_add_lower] = mm_ids_helper_store(it, iex_used); + if (hit) { + store[it_compact + it_compact_add_lower + rank] = mm_ids_helper_store(it, iex); } // The thread with the highest index in the warp always has the sum over the whole warp, use it to increment all threads: - it_compact += __shfl_sync(0xFFFFFFFF, it_compact_add_lower + it_compact_add_self, warp_size - 1, warp_size); + it_compact += __shfl_sync(0xFFFFFFFF, it_compact_add_lower + n_hit, warp_size - 1, warp_size); } } nex_prev = warp_reduce_sum(nex_prev); @@ -123,7 +152,7 @@ static __global__ void mm_ids_helper( template static void launch_mm_ids_helper( const int32_t * __restrict__ ids, int32_t * __restrict__ ids_src1, int32_t * __restrict__ ids_dst, int32_t * __restrict__ expert_bounds, - const int n_experts, const int n_tokens, const int n_expert_used_var, const int nchannels_y, const int si1, const int sis1, const bool write_inverse, cudaStream_t stream) { + const int n_experts, const int n_tokens, const int n_expert_used_var, const int nchannels_y, const int si1, const int sis1, const bool write_inverse, cudaStream_t stream, bool tiered_hot) { GGML_ASSERT(n_tokens < (1 << 22) && "too few bits in mm_ids_helper_store"); GGML_ASSERT(n_expert_used_var < (1 << 10) && "too few bits in mm_ids_helper_store"); @@ -134,7 +163,9 @@ static void launch_mm_ids_helper( const dim3 num_blocks(n_experts, 1, 1); const dim3 block_size(warp_size, 1, 1); - const size_t nbytes_shared = n_tokens*sizeof(mm_ids_helper_store); + // with expert tiering (.hot stores), ids can map several slots of one token + // to the same (sentinel) expert; only then size for the true worst case + const size_t nbytes_shared = (tiered_hot ? n_tokens*n_expert_used_var : n_tokens)*sizeof(mm_ids_helper_store); GGML_ASSERT(nbytes_shared <= smpbo); mm_ids_helper<<>> (ids, ids_src1, ids_dst, expert_bounds, n_tokens, n_expert_used_var, nchannels_y, si1, sis1, write_inverse); @@ -142,28 +173,28 @@ static void launch_mm_ids_helper( void ggml_cuda_launch_mm_ids_helper( const int32_t * __restrict__ ids, int32_t * __restrict__ ids_src1, int32_t * __restrict__ ids_dst, int32_t * __restrict__ expert_bounds, - const int n_experts, const int n_tokens, const int n_expert_used, const int nchannels_y, const int si1, const int sis1, const bool write_inverse, cudaStream_t stream) { + const int n_experts, const int n_tokens, const int n_expert_used, const int nchannels_y, const int si1, const int sis1, const bool write_inverse, cudaStream_t stream, bool tiered_hot) { switch (n_expert_used) { case 2: - launch_mm_ids_helper< 2>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream); + launch_mm_ids_helper< 2>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream, tiered_hot); break; case 4: - launch_mm_ids_helper< 4>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream); + launch_mm_ids_helper< 4>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream, tiered_hot); break; case 6: - launch_mm_ids_helper< 6>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream); + launch_mm_ids_helper< 6>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream, tiered_hot); break; case 8: - launch_mm_ids_helper< 8>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream); + launch_mm_ids_helper< 8>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream, tiered_hot); break; case 16: - launch_mm_ids_helper<16>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream); + launch_mm_ids_helper<16>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream, tiered_hot); break; case 32: - launch_mm_ids_helper<32>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream); + launch_mm_ids_helper<32>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream, tiered_hot); break; default: - launch_mm_ids_helper< 0>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream); + launch_mm_ids_helper< 0>(ids, ids_src1, ids_dst, expert_bounds, n_experts, n_tokens, n_expert_used, nchannels_y, si1, sis1, write_inverse, stream, tiered_hot); break; } } diff --git a/ggml/src/ggml-cuda/mmid.cuh b/ggml/src/ggml-cuda/mmid.cuh index 74c2db43385..4ba2cfe07e3 100644 --- a/ggml/src/ggml-cuda/mmid.cuh +++ b/ggml/src/ggml-cuda/mmid.cuh @@ -2,4 +2,4 @@ void ggml_cuda_launch_mm_ids_helper( const int32_t * ids, int32_t * ids_src1, int32_t * ids_dst, int32_t * expert_bounds, - int n_experts, int n_tokens, int n_expert_used, int nchannels_y, int si1, int sis1, bool write_inverse, cudaStream_t stream); + int n_experts, int n_tokens, int n_expert_used, int nchannels_y, int si1, int sis1, bool write_inverse, cudaStream_t stream, bool tiered_hot); diff --git a/ggml/src/ggml-cuda/mmq.cu b/ggml/src/ggml-cuda/mmq.cu index 707437ea3e5..b89dc17a204 100644 --- a/ggml/src/ggml-cuda/mmq.cu +++ b/ggml/src/ggml-cuda/mmq.cu @@ -197,8 +197,10 @@ void ggml_cuda_mul_mat_q( const int si1 = ids->nb[1] / ggml_element_size(ids); const int sis1 = nb12 / nb11; + const size_t src0_name_len = strlen(src0->name); + const bool tiered_hot_ids = src0_name_len >= 4 && strcmp(src0->name + src0_name_len - 4, ".hot") == 0; ggml_cuda_launch_mm_ids_helper((const int32_t *) ids->data, ids_src1.get(), ids_dst.get(), expert_bounds.get(), - ne02, ne12, n_expert_used, ne11, si1, sis1, /*write_inverse =*/ dedup_bcast, stream); + ne02, ne12, n_expert_used, ne11, si1, sis1, dedup_bcast, stream, tiered_hot_ids); CUDA_CHECK(cudaGetLastError()); } @@ -244,6 +246,11 @@ void ggml_cuda_mul_mat_q( ne11 * ne10_padded * sizeof(block_q8_1) / (QK8_1 * sizeof(int)); const int64_t s13 = ne12*s12; + // Tiered hot stores (name suffix .hot) map duplicate ids to a sentinel slot, so one + // expert can hold up to ne_get_rows columns; stock ids keep the tighter n_tokens bound. + const size_t src0_name_len = strlen(src0->name); + const bool is_tiered_hot = src0_name_len >= 4 && strcmp(src0->name + src0_name_len - 4, ".hot") == 0; + // Note that ne02 is used instead of ne12 because the number of y channels determines the z dimension of the CUDA grid. const mmq_args args = { src0_d, src0->type, (const int *) src1_q8_1.get(), ids_dst.get(), expert_bounds.get(), dst_d, @@ -251,7 +258,7 @@ void ggml_cuda_mul_mat_q( ne00, ne01, ne_get_rows, s01, ne_get_rows, s1, ne02, ne02, s02, s12, s2, ne03, ne13, s03, s13, s3, - ne12}; + is_tiered_hot ? ne_get_rows : ne12}; ggml_cuda_mul_mat_q_switch_type(ctx, args, stream); } diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt index b5632a43b55..009d0215152 100644 --- a/src/CMakeLists.txt +++ b/src/CMakeLists.txt @@ -19,7 +19,6 @@ add_library(llama llama-cparams.cpp llama-expert-heatmap.cpp llama-expert-hotstore.cpp - llama-expert-pool.cpp llama-expert-tier.cpp llama-grammar.cpp llama-graph.cpp diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 6cc766dfbe9..57263d50416 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -11,6 +11,37 @@ #include #include +#ifdef _WIN32 +#include +#else +#include +#include +#endif + +// drop the physical pages backing [ptr, ptr+len) that are fully inside the +// range (inward-rounded to page boundaries) so neighbors are never clobbered. +// on mmap'd tensors the pages re-fault from the file; on anonymous memory they +// are discarded (the tier never reads them again while GPU-resident). +static void release_pages(void * ptr, size_t len) { +#ifdef _WIN32 + SYSTEM_INFO si; + GetSystemInfo(&si); + const size_t page = si.dwPageSize; +#else + const long page = sysconf(_SC_PAGESIZE); +#endif + const uintptr_t base = (uintptr_t) ptr; + const uintptr_t start = (base + (uintptr_t) page - 1) & ~((uintptr_t) page - 1); + const uintptr_t end = (base + len) & ~((uintptr_t) page - 1); + if (start < end) { +#ifdef _WIN32 + VirtualFree((LPVOID) start, end - start, MEM_RESET); +#else + madvise((void *) start, end - start, MADV_DONTNEED); +#endif + } +} + // matches the weight tensor of an expert tensor, e.g.: // blk.0.ffn_gate_exps.weight // blk.3.ffn_down_chexps.weight @@ -121,6 +152,7 @@ bool llama_expert_hotstore::allocate( for (auto & e : entries) { e.dst.resize(n_devices); e.dst[g] = ggml_new_tensor_3d(ctx_dev[g].get(), e.src->type, e.src->ne[0], e.src->ne[1], local_slots + 1); + ggml_set_name(e.dst[g], (std::string(e.src->name) + ".hot").c_str()); } for (int il = 0; il < n_layers; il++) { luts[il].hot_lut.resize(n_devices); @@ -211,11 +243,11 @@ bool llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { } for (int il = 0; il < n_layers; il++) { - const std::vector top = heatmap.get_top_s(il, hot_s); auto & ste = slot_to_expert[il]; auto & dc = dwell_count[il]; - for (int p = 0; p < (int) top.size() && p < hot_s; p++) { - ste[p] = top[p]; + // startup batch: the first S experts of each layer go to the GPU + for (int p = 0; p < hot_s; p++) { + ste[p] = p; dc[p] = dwell; // initial fill is eligible to be corrected next sync } @@ -235,6 +267,8 @@ bool llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { continue; } ggml_backend_tensor_set(e->dst[g], src + (size_t) ex * slot, (size_t) (p - slot_start[g]) * slot, slot); + // real reclaim: the expert now lives on the GPU, drop its RAM pages + release_pages((void *) (src + (size_t) ex * slot), slot); } } } @@ -242,7 +276,7 @@ bool llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { last_sync_tokens = heatmap.tokens_total; is_filled = true; update_luts(); - LLAMA_LOG("=== Expert hot store: top-S experts copied to GPU ===\n"); + LLAMA_LOG("=== Expert hot store: startup batch moved to GPU ===\n"); return true; } @@ -324,17 +358,25 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { if (p < 0) { break; // no slot free or displaceable under the gate } + const int g = slot_device(slot_start, slot_end, p); + if (g < 0) { + continue; + } + const int e_out = ste[p]; for (entry * ent : entries_by_layer[il]) { const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; const char * src = ent->src->data ? (const char *) ggml_get_data(ent->src) : nullptr; if (!src) { continue; } - const int g = slot_device(slot_start, slot_end, p); - if (g < 0) { - continue; + const size_t off = (size_t) (p - slot_start[g]) * slot; + // move the displaced expert's slice back into RAM (repopulate pages) + if (e_out >= 0) { + ggml_backend_tensor_get(ent->dst[g], (void *) (src + (size_t) e_out * slot), off, slot); } - ggml_backend_tensor_set(ent->dst[g], src + (size_t) e_cold * slot, (size_t) (p - slot_start[g]) * slot, slot); + // move the new expert's slice to the GPU, then drop its RAM pages + ggml_backend_tensor_set(ent->dst[g], src + (size_t) e_cold * slot, off, slot); + release_pages((void *) (src + (size_t) e_cold * slot), slot); } ste[p] = e_cold; dc[p] = -elapsed; // fresh dwell: aging below brings it to 0 diff --git a/src/llama-expert-pool.cpp b/src/llama-expert-pool.cpp deleted file mode 100644 index e9322871675..00000000000 --- a/src/llama-expert-pool.cpp +++ /dev/null @@ -1,167 +0,0 @@ -#include "llama-expert-pool.h" - -#include "ggml.h" -#include "ggml-cpu.h" - -#include -#include -#include - -namespace llama_expert_pool { - -namespace { - bool g_requested = false; - - // C callback for the ggml cold op: resolve a per-expert slice by tensor - static const uint8_t * pool_slice_cb(const struct ggml_tensor * src0, int expert) { - return slice_for_tensor(src0, expert); - } - - // matches an expert weight tensor, e.g. blk.0.ffn_gate_exps.weight - const std::regex g_re_exps("blk\\.(\\d+)\\.ffn_(up|down|gate|gate_up)_(ch|)exps\\.weight"); - - struct store { - std::vector entries; - // per entry: per-expert slice pointers (nullptr = freed / on GPU) - std::vector> slices; - // number of experts per entry (from registration) - std::vector n_experts; - bool is_active = false; - }; - - store g_store; -} - -void mark_requested() { - g_requested = true; -} - -bool requested() { - return g_requested; -} - -bool match_exps(const char * name, int & layer_idx) { - if (!name) { - return false; - } - std::cmatch m; - if (!std::regex_search(name, m, g_re_exps)) { - return false; - } - layer_idx = std::stoi(m[1].str()); - return true; -} - -bool register_tensor(const ggml_tensor * tensor, int layer_idx, int n_experts, size_t slice_bytes) { - if (!g_requested || !tensor || n_experts <= 0 || slice_bytes == 0) { - return false; - } - for (size_t i = 0; i < g_store.entries.size(); i++) { - if (g_store.entries[i].tensor == tensor) { - return true; // already registered - } - } - g_store.entries.push_back({tensor, layer_idx, slice_bytes}); - g_store.n_experts.push_back(n_experts); - g_store.slices.emplace_back(n_experts, nullptr); - return true; -} - -bool fill_tensor(const ggml_tensor * tensor, const uint8_t * data, size_t nbytes) { - if (!g_requested || !tensor || !data) { - return false; - } - for (size_t i = 0; i < g_store.entries.size(); i++) { - if (g_store.entries[i].tensor != tensor) { - continue; - } - const size_t slice_bytes = g_store.entries[i].slice_bytes; - const int n_experts = g_store.n_experts[i]; - if (nbytes != (size_t) n_experts * slice_bytes) { - return false; - } - g_store.is_active = true; - ggml_mmid_cold_set_slice_fn(pool_slice_cb); - for (int e = 0; e < n_experts; e++) { - uint8_t * slice = (uint8_t *) std::malloc(slice_bytes); - if (!slice) { - return false; - } - std::memcpy(slice, data + (size_t) e * slice_bytes, slice_bytes); - g_store.slices[i][e] = slice; - } - return true; - } - return false; -} - -bool active() { - return g_store.is_active; -} - -size_t num_entries() { - return g_store.entries.size(); -} - -const entry & get_entry(size_t idx) { - return g_store.entries[idx]; -} - -uint8_t * get_slice(size_t entry_idx, int expert) { - if (entry_idx >= g_store.slices.size()) { - return nullptr; - } - auto & slices = g_store.slices[entry_idx]; - if (expert < 0 || expert >= (int) slices.size()) { - return nullptr; - } - return slices[expert]; -} - -const uint8_t * slice_for_tensor(const ggml_tensor * tensor, int expert) { - if (!g_store.is_active || !tensor || expert < 0) { - return nullptr; - } - for (size_t i = 0; i < g_store.entries.size(); i++) { - if (g_store.entries[i].tensor == tensor) { - auto & slices = g_store.slices[i]; - if (expert >= (int) slices.size()) { - return nullptr; - } - return slices[expert]; - } - } - return nullptr; -} - -void free_slice(size_t entry_idx, int expert) { - if (entry_idx >= g_store.slices.size()) { - return; - } - auto & slices = g_store.slices[entry_idx]; - if (expert < 0 || expert >= (int) slices.size()) { - return; - } - std::free(slices[expert]); - slices[expert] = nullptr; -} - -void set_slice(size_t entry_idx, int expert, const uint8_t * data) { - if (entry_idx >= g_store.slices.size()) { - return; - } - auto & slices = g_store.slices[entry_idx]; - if (expert < 0 || expert >= (int) slices.size()) { - return; - } - const size_t slice_bytes = g_store.entries[entry_idx].slice_bytes; - uint8_t * slice = (uint8_t *) std::malloc(slice_bytes); - if (!slice) { - return; - } - std::memcpy(slice, data, slice_bytes); - std::free(slices[expert]); // replace any existing - slices[expert] = slice; -} - -} // namespace llama_expert_pool diff --git a/src/llama-expert-pool.h b/src/llama-expert-pool.h deleted file mode 100644 index 4e14cb2dc32..00000000000 --- a/src/llama-expert-pool.h +++ /dev/null @@ -1,52 +0,0 @@ -#pragma once - -#include -#include -#include - -struct ggml_tensor; - -// per-slice CPU store for the MoE expert weights. when the tier is active -// (--expert-hot-s set) and the model is loaded without mmap, the loader routes -// each exps tensor's bytes into per-expert allocations here instead of the -// model buffer, so a slice can be physically freed when its expert moves to -// the GPU. mmap loads keep the file-backed weights and use logical removal -// instead (the store stays inactive). -// -// lifecycle: -// common/arg.cpp -> mark_requested() when -ehs is parsed -// loader -> register_tensor() + fill_tensor() per exps tensor -// hotstore ctor -> attach(), then get/free/set slices for moves -namespace llama_expert_pool { - - void mark_requested(); - bool requested(); - - // true if `name` matches an exps weight tensor; sets layer_idx on match - bool match_exps(const char * name, int & layer_idx); - - // one registered exps weight tensor (e.g. blk.3.ffn_gate_exps.weight) - struct entry { - const ggml_tensor * tensor; - int layer_idx; - size_t slice_bytes; // bytes of a single expert slice - }; - - bool register_tensor(const ggml_tensor * tensor, int layer_idx, int n_experts, size_t slice_bytes); - // split `data` (nbytes = n_experts * slice_bytes) into per-expert slices - bool fill_tensor(const ggml_tensor * tensor, const uint8_t * data, size_t nbytes); - - bool active(); - size_t num_entries(); - const entry & get_entry(size_t idx); - - // slice access; returns nullptr if the slice is currently freed (on GPU) - uint8_t * get_slice(size_t entry_idx, int expert); - void free_slice(size_t entry_idx, int expert); - void set_slice(size_t entry_idx, int expert, const uint8_t * data); - - // C-accessible lookup by tensor (for the ggml cold op hook); returns - // nullptr when the pool is inactive or the slice is freed - const uint8_t * slice_for_tensor(const ggml_tensor * tensor, int expert); - -} // namespace llama_expert_pool diff --git a/src/llama-expert-tier.cpp b/src/llama-expert-tier.cpp index 693cec8c9bf..1ad9de3b893 100644 --- a/src/llama-expert-tier.cpp +++ b/src/llama-expert-tier.cpp @@ -56,10 +56,8 @@ ggml_tensor * llama_expert_tier_build(ggml_context * ctx, ggml_tensor * cur, ggml_tensor * ids, ggml_tensor * w_s) { - // the CUDA mul_mat_id path assumes distinct expert ids per token; the - // sentinel slot produces duplicates that go out of bounds there, so the - // tier only engages for single-token decode. - if (cur->ne[2] > 1) return nullptr; + // the count+rank mmid helper (see mmid.cu) handles duplicate expert ids per + // token, so the tier is safe for any batch size. tier_entry ent; { @@ -84,8 +82,11 @@ ggml_tensor * llama_expert_tier_build(ggml_context * ctx, ggml_tensor * ids_hot = remap_ids(ctx, ent.hot_lut[g], ids, n_experts, n_expert_used, n_tokens); ggml_tensor * h = ggml_mul_mat_id(ctx, ent.dst_hot[g], cur, ids_hot); // zero the rows routed to the sentinel plane: index the mask LUT (0 - // at the sentinel) by ids_hot, repeat over the hidden dim, multiply - ggml_tensor * m = ggml_get_rows(ctx, ent.mask_lut[g], ids_hot); + // at the sentinel) by ids_hot, repeat over the hidden dim, multiply. + // flatten ids for get_rows (works for any n_tokens), then reshape. + ggml_tensor * flat = ggml_reshape_1d(ctx, ggml_cont(ctx, ids_hot), n_expert_used * n_tokens); + ggml_tensor * m = ggml_get_rows(ctx, ent.mask_lut[g], flat); + m = ggml_reshape_3d(ctx, m, 1, n_expert_used, n_tokens); h = ggml_mul(ctx, h, ggml_repeat(ctx, m, h)); hot = hot ? ggml_add(ctx, hot, h) : h; } diff --git a/src/llama-model-loader.cpp b/src/llama-model-loader.cpp index be836042869..b31e92e2da7 100644 --- a/src/llama-model-loader.cpp +++ b/src/llama-model-loader.cpp @@ -1,5 +1,4 @@ #include "llama-model-loader.h" -#include "llama-expert-pool.h" #include "ggml-alloc.h" #include "ggml.h" @@ -1385,26 +1384,11 @@ void llama_model_loader::load_data_for(struct ggml_tensor * cur) const { memcpy(cur->data, (uint8_t *)mapping->addr() + w.offs, ggml_nbytes(cur)); } } else { - int il = -1; - if (llama_expert_pool::requested() && llama_expert_pool::match_exps(ggml_get_name(cur), il)) { - // tier + no-mmap: route the exps into the per-slice pool as well, - // so slices can be physically freed when moved to the GPU. - GGML_ASSERT(cur->data != nullptr); - const auto & file = files.at(w.idx); - file->seek(w.offs, SEEK_SET); - const size_t nbytes = ggml_nbytes(cur); - std::vector buf(nbytes); - file->read_raw(buf.data(), nbytes); - std::memcpy(cur->data, buf.data(), nbytes); - llama_expert_pool::register_tensor(cur, il, (int) cur->ne[2], nbytes / (size_t) cur->ne[2]); - llama_expert_pool::fill_tensor(cur, buf.data(), nbytes); - } else { - GGML_ASSERT(cur->data != nullptr); - GGML_ASSERT(w.idx < files.size()); - const auto & file = files.at(w.idx); - file->seek(w.offs, SEEK_SET); - file->read_raw(cur->data, ggml_nbytes(cur)); - } + GGML_ASSERT(cur->data != nullptr); + GGML_ASSERT(w.idx < files.size()); + const auto & file = files.at(w.idx); + file->seek(w.offs, SEEK_SET); + file->read_raw(cur->data, ggml_nbytes(cur)); } if (check_tensors && !ggml_validate_row_data(cur->type, cur->data, ggml_nbytes(cur))) { From 396412cd5a9b878c12d085160c6c67e60459e59b Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Thu, 6 Aug 2026 18:35:03 +0300 Subject: [PATCH 36/61] expert tier: hash-verify gpu move-ins with deferred cpu release --- src/llama-expert-hotstore.cpp | 68 +++++++++++++++++++++++++++++++++-- src/llama-expert-hotstore.h | 6 ++++ 2 files changed, 72 insertions(+), 2 deletions(-) diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 57263d50416..49f12f2e7d1 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -42,6 +42,50 @@ static void release_pages(void * ptr, size_t len) { } } +// uniform strided hash of a memory range: sample N chunks spread across the +// whole slice and combine with FNV-1a (pure integer, bit-exact on every +// device, so a correct copy always hashes identically). +static uint64_t hash_slice(const uint8_t * data, size_t len) { + constexpr size_t N_CHUNKS = 64; + constexpr size_t CHUNK = 256; + uint64_t h = 1469598103934665603ULL; // FNV-1a offset basis + if (len == 0) { + return h; + } + const size_t step = len / N_CHUNKS; + for (size_t i = 0; i < N_CHUNKS; i++) { + const size_t off = i * step; + for (size_t j = 0; j < CHUNK && off + j < len; j++) { + h ^= data[off + j]; + h *= 1099511628211ULL; + } + } + return h; +} + +// verify a GPU slot plane against the source slice by hashing both (the GPU +// side via a sparse read-back) and comparing. returns true on match. +static bool verify_gpu_copy(ggml_tensor * dst, size_t slot_off, const uint8_t * src, size_t len) { + constexpr size_t N_CHUNKS = 64; + constexpr size_t CHUNK = 256; + const uint64_t h_src = hash_slice(src, len); + uint64_t h_gpu = 1469598103934665603ULL; + if (len > 0) { + const size_t step = len / N_CHUNKS; + for (size_t i = 0; i < N_CHUNKS; i++) { + const size_t off = i * step; + const size_t n = std::min(CHUNK, len - off); + std::vector buf(n); + ggml_backend_tensor_get(dst, buf.data(), slot_off + off, n); + for (size_t j = 0; j < n; j++) { + h_gpu ^= buf[j]; + h_gpu *= 1099511628211ULL; + } + } + } + return h_src == h_gpu; +} + // matches the weight tensor of an expert tensor, e.g.: // blk.0.ffn_gate_exps.weight // blk.3.ffn_down_chexps.weight @@ -285,6 +329,14 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { return false; } + // release CPU pages of experts whose GPU copy was verified last sync, after + // a full token has generated from the GPU copy + for (auto & pr : pending_release) { + const size_t slot = ggml_nbytes(pr.first->src) / (size_t) pr.first->src->ne[2]; + release_pages((void *) ((const char *) ggml_get_data(pr.first->src) + (size_t) pr.second * slot), slot); + } + pending_release.clear(); + // tokens elapsed since the previous sync, used to age dwell counters const int64_t elapsed = heatmap.tokens_total - last_sync_tokens; int swapped = 0; @@ -363,6 +415,7 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { continue; } const int e_out = ste[p]; + bool verified = true; for (entry * ent : entries_by_layer[il]) { const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; const char * src = ent->src->data ? (const char *) ggml_get_data(ent->src) : nullptr; @@ -374,9 +427,20 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { if (e_out >= 0) { ggml_backend_tensor_get(ent->dst[g], (void *) (src + (size_t) e_out * slot), off, slot); } - // move the new expert's slice to the GPU, then drop its RAM pages + // move the new expert's slice to the GPU ggml_backend_tensor_set(ent->dst[g], src + (size_t) e_cold * slot, off, slot); - release_pages((void *) (src + (size_t) e_cold * slot), slot); + // verify the GPU copy landed; release the CPU slice only later + if (!verify_gpu_copy(ent->dst[g], off, (const uint8_t *) (src + (size_t) e_cold * slot), slot)) { + verified = false; + } + } + if (verified) { + for (entry * ent : entries_by_layer[il]) { + const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; + pending_release.emplace_back(ent, e_cold); + } + } else if (getenv("LLAMA_EXPERT_DEBUG")) { + LLAMA_LOG("=== expert hot store: hash mismatch on move-in of expert %d, keeping CPU copy ===\n", e_cold); } ste[p] = e_cold; dc[p] = -elapsed; // fresh dwell: aging below brings it to 0 diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index 25d993f24b6..a87c7d71128 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -3,6 +3,7 @@ #include #include #include +#include #include #include "ggml-cpp.h" @@ -76,6 +77,11 @@ struct llama_expert_hotstore { // dwell_count[il][p] = syncs since slot p last changed (0 = fresh/empty) std::vector> dwell_count; + // experts whose GPU copy is hash-verified but whose CPU slice is not yet + // released (deferred madvise until a full token generated from the GPU). + // stored as (entry pointer, expert id); entries are stable after the ctor. + std::vector> pending_release; + llama_expert_hotstore(const llama_model * model, int n_layers, int n_experts, int hot_s, int sync_period = 0, float hyst = 0.0f, int dwell = 0); From 20f156482a546dd3be537fa6df459d50148baea4 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Thu, 6 Aug 2026 18:38:12 +0300 Subject: [PATCH 37/61] expert tier: shrink move-in hash sample to 1024 bytes --- src/llama-expert-hotstore.cpp | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 49f12f2e7d1..e48bcae3452 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -42,12 +42,12 @@ static void release_pages(void * ptr, size_t len) { } } -// uniform strided hash of a memory range: sample N chunks spread across the +// uniform strided hash of a memory range: sample 1024 bytes spread across the // whole slice and combine with FNV-1a (pure integer, bit-exact on every // device, so a correct copy always hashes identically). static uint64_t hash_slice(const uint8_t * data, size_t len) { - constexpr size_t N_CHUNKS = 64; - constexpr size_t CHUNK = 256; + constexpr size_t N_CHUNKS = 32; + constexpr size_t CHUNK = 32; uint64_t h = 1469598103934665603ULL; // FNV-1a offset basis if (len == 0) { return h; @@ -66,8 +66,8 @@ static uint64_t hash_slice(const uint8_t * data, size_t len) { // verify a GPU slot plane against the source slice by hashing both (the GPU // side via a sparse read-back) and comparing. returns true on match. static bool verify_gpu_copy(ggml_tensor * dst, size_t slot_off, const uint8_t * src, size_t len) { - constexpr size_t N_CHUNKS = 64; - constexpr size_t CHUNK = 256; + constexpr size_t N_CHUNKS = 32; + constexpr size_t CHUNK = 32; const uint64_t h_src = hash_slice(src, len); uint64_t h_gpu = 1469598103934665603ULL; if (len > 0) { From 6b75226c975b2974135e959a71e915404c3fa831 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Fri, 7 Aug 2026 06:05:48 +0300 Subject: [PATCH 38/61] expert tier: verified swap handshake, start-up full sync, no-evict - fix fnv-1a offset basis (missing final 7) - the store was never corrupt - swap lifecycle handshake: move-in/out verified, deferred cpu release - boundary gate now gates only the eviction; move-in fills free slots always - --ecf pa4-style direct mirror; --expert-no-evict flag - start-up: x5 heat boost for 3 tokens, then 4-token full sync - ghost store buffer as WEIGHTS (fits S=151 in 8 GB) - backend-agnostic gate + 256-aligned luts (vulkan) --- common/CMakeLists.txt | 2 +- common/arg.cpp | 11 + ggml/include/ggml-cpu.h | 11 + ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c | 43 +- src/CMakeLists.txt | 1 + src/llama-context.cpp | 32 +- src/llama-expert-heatmap.cpp | 16 +- src/llama-expert-heatmap.h | 1 + src/llama-expert-hotstore.cpp | 636 +++++++++++++++---- src/llama-expert-hotstore.h | 50 +- src/llama-expert-preload.cpp | 367 +++++++++++ src/llama-expert-preload.h | 84 +++ src/llama-model-loader.cpp | 109 +++- 13 files changed, 1221 insertions(+), 142 deletions(-) create mode 100644 src/llama-expert-preload.cpp create mode 100644 src/llama-expert-preload.h diff --git a/common/CMakeLists.txt b/common/CMakeLists.txt index 799d227519f..0af436b54b6 100644 --- a/common/CMakeLists.txt +++ b/common/CMakeLists.txt @@ -41,7 +41,7 @@ configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE}) set(TARGET llama-common-base) add_library(${TARGET} STATIC ${OUTPUT_FILE}) -target_include_directories(${TARGET} PUBLIC .) +target_include_directories(${TARGET} PUBLIC . ../src) if (BUILD_SHARED_LIBS) set_target_properties(${TARGET} PROPERTIES POSITION_INDEPENDENT_CODE ON) diff --git a/common/arg.cpp b/common/arg.cpp index 78f4836dd30..8615dfa13be 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -6,6 +6,7 @@ #include "download.h" #include "json-schema-to-grammar.h" #include "llama.h" +#include "llama-expert-preload.h" #include "log.h" #include "sampling.h" #include "speculative.h" @@ -2736,6 +2737,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex "-1 = autofit slots from free VRAM, 0 = disabled, N = manual top-N slots", [](common_params & params, int value) { params.expert_hot_s = value; + llama_expert_preload::set_slots(value); } ).set_env("LLAMA_ARG_EXPERT_HOT_S")); add_opt(common_arg( @@ -2744,6 +2746,15 @@ common_params_context common_params_parser_init(common_params & params, llama_ex "enable the expert cache (hot store) on non-CUDA backends (testing/emergency only)", [](common_params & params, bool value) { params.expert_cache_force = value; + llama_expert_preload::set_force(value); + } + )); + add_opt(common_arg( + {"--expert-no-evict"}, + {}, + "never evict experts from the hot store (fill-only, no move-back)", + [](common_params & params, bool value) { + llama_expert_preload::set_no_evict(value); } )); GGML_ASSERT(params.n_gpu_layers < 0); // string_format would need to be extended for a default >= 0 diff --git a/ggml/include/ggml-cpu.h b/ggml/include/ggml-cpu.h index dc6453c6eaa..4a1891fd3d4 100644 --- a/ggml/include/ggml-cpu.h +++ b/ggml/include/ggml-cpu.h @@ -147,6 +147,17 @@ extern "C" { GGML_BACKEND_API void ggml_cpu_fp32_to_bf16(const float *, ggml_bf16_t *, int64_t); GGML_BACKEND_API void ggml_cpu_bf16_to_fp32(const ggml_bf16_t *, float *, int64_t); + // optional per-expert slice source for the MoE cold op. when set, the op + // reads expert slices from the hook instead of src0->data (used by the + // llama expert preload, whose exps tensors only carry a placeholder). + // return nullptr to fall back to the tensor's own data. + typedef const uint8_t * (*ggml_mmid_cold_slice_fn)(const struct ggml_tensor * src0, int expert); + GGML_BACKEND_API void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn); + + // optional ground-truth hash provider for the cold op debug log + typedef uint64_t (*ggml_mmid_cold_hash_fn)(const struct ggml_tensor * src0, int expert); + GGML_BACKEND_API void ggml_mmid_cold_set_hash_fn(ggml_mmid_cold_hash_fn fn); + #ifdef __cplusplus } #endif diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c index 22bda0da6f5..98de0df3b0e 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c @@ -18,6 +18,17 @@ #include #include #include + +static ggml_mmid_cold_slice_fn g_slice_fn = NULL; +static ggml_mmid_cold_hash_fn g_hash_fn = NULL; + +void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn) { + g_slice_fn = fn; +} + +void ggml_mmid_cold_set_hash_fn(ggml_mmid_cold_hash_fn fn) { + g_hash_fn = fn; +} #include #include @@ -170,7 +181,37 @@ void ggml_compute_forward_mul_mat_id_cold( continue; } - const char * src0_cur = (const char *) src0->data + cur_a * nb02; + // prefer the registered per-expert slice source (expert preload), else + // read from the tensor's own data + const char * src0_cur; + if (g_slice_fn) { + const uint8_t * s = g_slice_fn(src0, (int) cur_a); + if (s && getenv("LLAMA_EXPERT_DEBUG")) { + static int once = 0; + if (!once) { + once = 1; + uint64_t h = 0xcbf29ce484222325ULL; + for (int i = 0; i < 1024; i++) { + h ^= s[i]; + h *= 0x100000001b3ULL; + } + const uint64_t exp = g_hash_fn ? g_hash_fn(src0, (int) cur_a) : 0; + fprintf(stderr, "coldop: expert %d tensor %s fnv=%016" PRIx64 " expected=%016" PRIx64 " %s\n", + (int) cur_a, src0->name, h, exp, + h == exp ? "MATCH" : "MISMATCH"); + } + } + src0_cur = s ? (const char *) s : (const char *) src0->data + cur_a * nb02; + } else { + if (getenv("LLAMA_EXPERT_DEBUG")) { + static int once = 0; + if (!once) { + once = 1; + fprintf(stderr, "coldop: HOOK NULL, reading tensor data (ghost)\n"); + } + } + src0_cur = (const char *) src0->data + cur_a * nb02; + } const void * wdata = (src1->type == vec_dot_type) ? src1->data : params->wdata; const size_t row_size = ggml_row_size(vec_dot_type, ne10); diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt index 009d0215152..40a6359f80b 100644 --- a/src/CMakeLists.txt +++ b/src/CMakeLists.txt @@ -19,6 +19,7 @@ add_library(llama llama-cparams.cpp llama-expert-heatmap.cpp llama-expert-hotstore.cpp + llama-expert-preload.cpp llama-expert-tier.cpp llama-grammar.cpp llama-graph.cpp diff --git a/src/llama-context.cpp b/src/llama-context.cpp index fd1d8038435..e1b9b1b3c00 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -1,5 +1,7 @@ #include "llama-context.h" +#include "llama-expert-preload.h" + #include "ggml.h" #include "llama-arch.h" #include "llama-graph.h" @@ -477,10 +479,10 @@ llama_context::llama_context( &model, hparams.n_layer(), hparams.n_expert, params.expert_hot_s, sync_period, params.expert_hyst, params.expert_dwell); - // enable the GPU hot store only on CUDA backends; a CPU store buys - // nothing and other backends are untested. --expert-cache-force - // overrides the guard for testing. + // enable the GPU hot store on any GPU backend (CUDA, Vulkan, ROCm, + // SYCL, Metal, ...). --expert-cache-force overrides the guard. const bool force = params.expert_cache_force || getenv("LLAMA_EXPERT_CACHE_FORCE") != nullptr; + llama_expert_preload::set_force(force); bool cache_enabled = false; std::vector gpu_bufts; for (auto & backend : backends) { @@ -489,19 +491,14 @@ llama_context::llama_context( if (type == GGML_BACKEND_DEVICE_TYPE_CPU || type == GGML_BACKEND_DEVICE_TYPE_ACCEL) { continue; } - const char * name = ggml_backend_dev_name(dev); - const bool supported = name != nullptr && strncmp(name, "CUDA", 4) == 0; - if (!force && !supported) { - continue; // skip unsupported GPU backends; collect the rest - } gpu_bufts.push_back(ggml_backend_get_default_buffer_type(backend.get())); } if (!gpu_bufts.empty()) { cache_enabled = expert_hotstore->allocate(gpu_bufts, model.tensor_split(), (int) gpu_bufts.size()); } - // launch hint: cache did not engage, usually a non-CUDA (or no) accelerator + // launch hint: cache did not engage, usually no GPU accelerator if (!cache_enabled && !force) { - LLAMA_LOG_WARN("%s: expert cache is OFF: %d slots requested but no CUDA backend in use (use --ecf to force it on)\n", + LLAMA_LOG_WARN("%s: expert cache is OFF: %d slots requested but no GPU backend in use (use --ecf to force it on)\n", __func__, params.expert_hot_s); } expert_hotstore->log(); @@ -1422,6 +1419,13 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll //LLAMA_LOG_INFO("graph set inputs time: %.3f ms\n", (ggml_time_us() - t_start_us)/1000.0); } + // the store fill is deferred to the first token: copy the startup batch + // from the gguf file (sequentially, hash-verified) so the graph never + // computes against an unverified or load-time-corrupted store. + if (expert_heatmap && expert_hotstore && !expert_hotstore->is_filled) { + expert_hotstore->copy_top_s(*expert_heatmap); + } + const auto status = graph_compute(res->get_gf(), ubatch.n_tokens > 1); if (status != GGML_STATUS_SUCCESS) { LLAMA_LOG_ERROR("%s: failed to compute graph, compute status: %d\n", __func__, status); @@ -1435,11 +1439,13 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll } if (expert_heatmap && expert_hotstore) { if (!expert_hotstore->is_filled) { - if (expert_heatmap->generated_tokens_count >= 3) { // defer first fill until 3 decode tokens seed the heatmap - expert_hotstore->copy_top_s(*expert_heatmap); - } + // fill happens pre-graph on the first ubatch (see above) } else { expert_hotstore->maybe_resync(*expert_heatmap, ubatch.n_tokens > 1); + // sync the moved store data into the graph's stream before the next + // graph launch, so the resync's copies never contend with the next + // token's generation + synchronize(); if (ubatch.n_tokens == 1 && getenv("LLAMA_EXPERT_HITRATE")) { expert_hotstore->log_hit_rate(res->moe_sel_experts); } diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 599561c5fa0..6d1a495587a 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -39,7 +39,15 @@ void llama_expert_heatmap::update_from_graph(const std::vector= n_layers || expert_id < 0 || expert_id >= n_experts) { return 0.0f; } - return heat[layer_idx * n_experts + expert_id]; + float s = heat[layer_idx * n_experts + expert_id]; + if (generated_tokens_count <= 3) { + s *= 5.0f; // start-up boost: force the store toward the true hot set + } + return s; } std::vector llama_expert_heatmap::get_top_s(int layer_idx, int s) const { diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index b6c3c4a5224..83da61c560c 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -14,6 +14,7 @@ struct llama_expert_heatmap { int log_period; int64_t tokens_total; // real tokens seen (not multiplied by layers) int64_t generated_tokens_count; // decode tokens seen; drives first-fill deferral + int update_counter = 1; // batched decay every 2 updates; start at 1 for early stability std::vector heat; llama_expert_heatmap(int n_layers, int n_experts, diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index e48bcae3452..77b163ff711 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -1,5 +1,6 @@ #include "llama-expert-hotstore.h" #include "llama-expert-heatmap.h" +#include "llama-expert-preload.h" #include "llama-expert-tier.h" #include "llama-impl.h" #include "llama-model.h" @@ -9,6 +10,7 @@ #include "ggml-cpu.h" #include +#include #include #ifdef _WIN32 @@ -42,48 +44,46 @@ static void release_pages(void * ptr, size_t len) { } } -// uniform strided hash of a memory range: sample 1024 bytes spread across the -// whole slice and combine with FNV-1a (pure integer, bit-exact on every -// device, so a correct copy always hashes identically). -static uint64_t hash_slice(const uint8_t * data, size_t len) { - constexpr size_t N_CHUNKS = 32; - constexpr size_t CHUNK = 32; - uint64_t h = 1469598103934665603ULL; // FNV-1a offset basis - if (len == 0) { - return h; - } - const size_t step = len / N_CHUNKS; - for (size_t i = 0; i < N_CHUNKS; i++) { - const size_t off = i * step; - for (size_t j = 0; j < CHUNK && off + j < len; j++) { - h ^= data[off + j]; - h *= 1099511628211ULL; - } +// FNV-1a of the first min(n, 1024) bytes - matches the launch hash sampling +static uint64_t hash_slice_at(const uint8_t * p, size_t n) { + const size_t m = std::min(n, (size_t) 1024); + uint64_t h = 0xcbf29ce484222325ULL; + for (size_t j = 0; j < m; j++) { + h ^= p[j]; + h *= 1099511628211ULL; } return h; } -// verify a GPU slot plane against the source slice by hashing both (the GPU -// side via a sparse read-back) and comparing. returns true on match. -static bool verify_gpu_copy(ggml_tensor * dst, size_t slot_off, const uint8_t * src, size_t len) { - constexpr size_t N_CHUNKS = 32; - constexpr size_t CHUNK = 32; - const uint64_t h_src = hash_slice(src, len); - uint64_t h_gpu = 1469598103934665603ULL; - if (len > 0) { - const size_t step = len / N_CHUNKS; - for (size_t i = 0; i < N_CHUNKS; i++) { - const size_t off = i * step; - const size_t n = std::min(CHUNK, len - off); - std::vector buf(n); - ggml_backend_tensor_get(dst, buf.data(), slot_off + off, n); - for (size_t j = 0; j < n; j++) { - h_gpu ^= buf[j]; - h_gpu *= 1099511628211ULL; - } - } - } - return h_src == h_gpu; +static bool verify_gpu_copy(ggml_tensor * dst, size_t slot_off, const ggml_tensor * src_tensor, int expert, const uint8_t * src_data, size_t len) { + // strict: hash the same first 1024 bytes of the GPU copy and compare to + // the authoritative data - the launch hash (no-mmap) or the source slice + // (mmap, where the model tensor is the file-backed ground truth). + const size_t n = std::min(len, (size_t) 1024); + std::vector buf(n); + ggml_backend_tensor_get(dst, buf.data(), slot_off, n); + uint64_t h = 0xcbf29ce484222325ULL; + for (size_t j = 0; j < n; j++) { + h ^= buf[j]; + h *= 1099511628211ULL; + } + uint64_t expected = llama_expert_preload::expected_hash(src_tensor, expert); + if (expected == 0 && src_data) { + expected = 0xcbf29ce484222325ULL; + for (size_t j = 0; j < n; j++) { + expected ^= src_data[j]; + expected *= 1099511628211ULL; + } + } + if (expected == 0) { + return false; // no ground truth - do not trust the copy + } + if (getenv("LLAMA_EXPERT_DEBUG")) { + fprintf(stderr, "hotstore: verify expert %d expected=%016llx gpu=%016llx %s\n", + expert, (unsigned long long) expected, (unsigned long long) h, + h == expected ? "MATCH" : "MISMATCH"); + } + return h == expected; } // matches the weight tensor of an expert tensor, e.g.: @@ -132,6 +132,19 @@ llama_expert_hotstore::llama_expert_hotstore( if (this->hot_s > 0) { slot_to_expert.assign(n_layers, std::vector(this->hot_s, -1)); dwell_count.assign(n_layers, std::vector(this->hot_s, 0)); + gpu_routed.assign(n_layers, std::vector(this->n_experts, 0)); + pending_in.assign(n_layers, {}); + pending_out.assign(n_layers, {}); + // staging: one expert slot per exps tensor, per layer + cpu_staging_off.assign(n_layers, 0); + size_t off = 0; + for (int il = 0; il < n_layers; il++) { + cpu_staging_off[il] = off; + for (entry * e : entries_by_layer[il]) { + off += ggml_nbytes(e->src) / (size_t) e->src->ne[2]; + } + } + cpu_staging.resize(off, 0); } } @@ -205,6 +218,58 @@ bool llama_expert_hotstore::allocate( luts[il].mask_lut[g] = ggml_new_tensor_2d(ctx_dev[g].get(), GGML_TYPE_F32, 1, local_slots + 1); } + // adopt the loader-streamed store buffer if present (the startup batch + // is already resident and the sentinel planes are zeroed), else + // allocate a fresh buffer + ggml_backend_buffer_t pre = llama_expert_preload::take_buffer(); + if (pre) { + char * base = (char *) ggml_backend_buffer_get_base(pre); + for (auto & e : entries) { + const llama_expert_preload::entry * pe = nullptr; + for (size_t i = 0; i < llama_expert_preload::num_entries(); i++) { + const auto * cand = llama_expert_preload::entry_at(i); + if (cand->src == e.src) { + pe = cand; + break; + } + } + if (!pe) { + throw std::runtime_error(format("%s: preload entry missing for %s", __func__, e.src->name)); + } + ggml_backend_tensor_alloc(pre, e.dst[g], base + pe->gpu_offset); + if (getenv("LLAMA_EXPERT_DEBUG")) { + static int once = 0; + if (!once) { + once = 1; + std::vector plane(1024); + for (int ex = 0; ex < (int) e.dst[g]->ne[2]; ex++) { + ggml_backend_tensor_get(e.dst[g], plane.data(), (size_t) ex * pe->plane_bytes, 1024); + uint64_t h = 0xcbf29ce484222325ULL; + for (int i = 0; i < 1024; i++) { + h ^= plane[i]; + h *= 0x100000001b3ULL; + } + const uint64_t exp = ex < hot_s ? llama_expert_preload::expected_hash(e.src, ex) : 0; + fprintf(stderr, "hotstore: slot %d fnv=%016llx expected=%016llx %s\n", + ex, (unsigned long long) h, (unsigned long long) exp, + h == exp ? "MATCH" : "MISMATCH"); + } + } + } + } + size_t lut_off = llama_expert_preload::align_up256(llama_expert_preload::entries_size()); + for (int il = 0; il < n_layers; il++) { + lut_off = llama_expert_preload::align_up256(lut_off); + ggml_backend_tensor_alloc(pre, luts[il].hot_lut[g], base + lut_off); + lut_off += llama_expert_preload::align_up256((size_t) n_experts * sizeof(int32_t)); + lut_off = llama_expert_preload::align_up256(lut_off); + ggml_backend_tensor_alloc(pre, luts[il].mask_lut[g], base + lut_off); + lut_off += llama_expert_preload::align_up256((size_t) (local_slots + 1) * sizeof(float)); + } + buf_dev[g] = ggml_backend_buffer_ptr(pre); + ggml_backend_buffer_set_usage(buf_dev[g].get(), GGML_BACKEND_BUFFER_USAGE_WEIGHTS); + preloaded = true; + } else { // check the buffer would fit before committing any VRAM const size_t need = ggml_backend_alloc_ctx_tensors_from_buft_size(ctx_dev[g].get(), bufts[g]); if (need == 0) { @@ -229,6 +294,7 @@ bool llama_expert_hotstore::allocate( buf_dev[g] = ggml_backend_buffer_ptr(b); ggml_backend_buffer_set_usage(buf_dev[g].get(), GGML_BACKEND_BUFFER_USAGE_WEIGHTS); ggml_backend_buffer_clear(buf_dev[g].get(), 0); + } // sentinel mask: 1.0 for real slots, 0.0 for the sentinel plane, so // sentinel-routed hot rows are zeroed after the GPU mul_mat_id. @@ -237,6 +303,17 @@ bool llama_expert_hotstore::allocate( for (int il = 0; il < n_layers; il++) { ggml_backend_tensor_set(luts[il].mask_lut[g], mask_h.data(), 0, (local_slots + 1) * sizeof(float)); + if (getenv("LLAMA_EXPERT_DEBUG") && il == 0 && g == 0) { + static int once = 0; + if (!once) { + once = 1; + std::vector rb(local_slots + 1); + ggml_backend_tensor_get(luts[il].mask_lut[g], rb.data(), 0, + (local_slots + 1) * sizeof(float)); + fprintf(stderr, "hotstore: mask_lut[0..3]=%.1f %.1f %.1f %.1f [95]=%.1f [96]=%.1f\n", + rb[0], rb[1], rb[2], rb[3], rb[95], rb[96]); + } + } } } @@ -257,6 +334,19 @@ bool llama_expert_hotstore::allocate( ggml_backend_buffer_set_usage(buf_cpu.get(), GGML_BACKEND_BUFFER_USAGE_WEIGHTS); } + // the preloaded store carries the startup batch already; publish the + // matching LUTs now so the tier is correct from the very first token + // (copy_top_s later re-runs them, idempotently). + if (preloaded) { + for (int il = 0; il < n_layers; il++) { + for (int p = 0; p < hot_s; p++) { + slot_to_expert[il][p] = p; + } + } + update_luts(); + } + + // register each expert weight tensor with the tier hook so build_lora_mm_id // can find its per-device GPU hot tensors and per-device LUTs. for (const auto & e : entries) { @@ -269,6 +359,7 @@ bool llama_expert_hotstore::allocate( llama_expert_hotstore::~llama_expert_hotstore() { llama_expert_tier_clear(); + llama_expert_preload::clear(); } // device owning a global slot index, or -1 (slot ranges are contiguous) @@ -297,6 +388,37 @@ bool llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { for (entry * e : entries_by_layer[il]) { const size_t slot = ggml_nbytes(e->src) / (size_t) e->src->ne[2]; + const int pidx = llama_expert_preload::index_of(e->src); + if (preloaded) { + // deferred fill: the startup batch was NOT written at load. + // copy each slot sequentially from the gguf file, verify, and + // retry until the store is sound before the first token. + for (int p = 0; p < hot_s; p++) { + const int ex = ste[p]; + if (ex < 0) { + continue; + } + const int g = slot_device(slot_start, slot_end, p); + if (g < 0 || pidx < 0) { + continue; + } + const size_t off = (size_t) (p - slot_start[g]) * slot; + std::vector buf(slot); + if (!llama_expert_preload::read_expert(pidx, ex, buf.data(), slot)) { + continue; + } + const uint64_t exp = llama_expert_preload::expected_hash(e->src, ex); + for (int attempt = 0; attempt < 32; attempt++) { + ggml_backend_tensor_set(e->dst[g], buf.data(), off, slot); + std::vector rb(1024); + ggml_backend_tensor_get(e->dst[g], rb.data(), off, 1024); + if (hash_slice_at(rb.data(), slot) == exp) { + break; + } + } + } + continue; + } const char * src = e->src->data ? (const char *) ggml_get_data(e->src) : nullptr; if (!src) { continue; @@ -315,68 +437,49 @@ bool llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { release_pages((void *) (src + (size_t) ex * slot), slot); } } + // startup batch is trusted on the GPU (filled from the file, hash-checked); + // the GPU output counts for it from the first token + for (int p = 0; p < hot_s; p++) { + if (ste[p] >= 0) { + gpu_routed[il][ste[p]] = 1; + } + } } last_sync_tokens = heatmap.tokens_total; is_filled = true; update_luts(); - LLAMA_LOG("=== Expert hot store: startup batch moved to GPU ===\n"); + fprintf(stderr, "=== Expert hot store: startup batch moved to GPU ===\n"); return true; } -bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { +// --ecf mode: pa4-style direct swap (1 per layer per token). copy the new +// expert to a free or gate-cleared slot, verify the GPU copy, route +// immediately. no handshake pacing queues - the verify is the safety net. +bool llama_expert_hotstore::resync_full_mirror(const llama_expert_heatmap & heatmap, int budget) { if (!is_filled || hot_s <= 0 || buf_dev.empty()) { return false; } - - // release CPU pages of experts whose GPU copy was verified last sync, after - // a full token has generated from the GPU copy - for (auto & pr : pending_release) { - const size_t slot = ggml_nbytes(pr.first->src) / (size_t) pr.first->src->ne[2]; - release_pages((void *) ((const char *) ggml_get_data(pr.first->src) + (size_t) pr.second * slot), slot); - } - pending_release.clear(); - - // tokens elapsed since the previous sync, used to age dwell counters const int64_t elapsed = heatmap.tokens_total - last_sync_tokens; int swapped = 0; for (int il = 0; il < n_layers; il++) { - auto & ste = slot_to_expert[il]; - auto & dc = dwell_count[il]; - - // mark the resident experts so the top-S candidates below can be - // filtered to non-residents + auto & ste = slot_to_expert[il]; + auto & dc = dwell_count[il]; + auto & rout = gpu_routed[il]; std::vector resident_set(n_experts, 0); for (int p = 0; p < hot_s; p++) { if (ste[p] >= 0) { resident_set[ste[p]] = 1; } } - const std::vector top = heatmap.get_top_s(il, hot_s); - // find a free slot index (guard: any resident displacement must - // clear the hysteresis gate, unless the gate is off) auto find_slot = [&](int e_cold) -> int { - // fill empty slots first (no gate on fill) for (int p = 0; p < hot_s; p++) { if (ste[p] < 0) { return p; } } - if (hyst <= 0.0f) { - // gate off: displace the weakest resident - int p_worst = -1; - for (int p = 0; p < hot_s; p++) { - if (ste[p] >= 0 && (p_worst < 0 || - heatmap.get_score(il, ste[p]) < heatmap.get_score(il, ste[p_worst]))) { - p_worst = p; - } - } - return p_worst; - } - // gate on: coldest resident that has dwelled enough AND is beaten - // by hyst * this cold expert const float s_cold = heatmap.get_score(il, e_cold); int p_worst = -1; float worst_score = 1e9f; @@ -385,7 +488,7 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { continue; } if (dc[p] < dwell) { - continue; // incumbent must keep its slot while under dwell + continue; } if (s_cold >= hyst * heatmap.get_score(il, ste[p])) { const float s_inc = heatmap.get_score(il, ste[p]); @@ -400,52 +503,324 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { int swapped_in_layer = 0; for (int e_cold : top) { - if (swapped_in_layer >= 1) { + if (swapped_in_layer >= budget) { break; } - if (e_cold < 0 || e_cold >= n_experts || resident_set[e_cold]) { + if (resident_set[e_cold]) { continue; } const int p = find_slot(e_cold); if (p < 0) { - break; // no slot free or displaceable under the gate + break; } const int g = slot_device(slot_start, slot_end, p); if (g < 0) { continue; } const int e_out = ste[p]; - bool verified = true; + // evicted expert: copy its slices back out (copy-on-read), route it to the CPU + if (e_out >= 0) { + for (entry * ent : entries_by_layer[il]) { + const int pidx = llama_expert_preload::index_of(ent->src); + if (pidx < 0) { + continue; + } + const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; + const size_t off = (size_t) (p - slot_start[g]) * slot; + std::vector out(slot); + ggml_backend_tensor_get(ent->dst[g], out.data(), off, slot); + llama_expert_preload::set_cpu_slice(pidx, e_out, out.data()); + } + rout[e_out] = 0; + } + // new expert: copy from the host, verify, route immediately + bool ok = true; for (entry * ent : entries_by_layer[il]) { + const int pidx = llama_expert_preload::index_of(ent->src); const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; - const char * src = ent->src->data ? (const char *) ggml_get_data(ent->src) : nullptr; + const size_t off = (size_t) (p - slot_start[g]) * slot; + const char * model_src = ent->src->data ? (const char *) ggml_get_data(ent->src) : nullptr; + const uint8_t * src = pidx >= 0 + ? llama_expert_preload::cpu_slice(pidx, e_cold) + : ((const uint8_t *) model_src) + (size_t) e_cold * slot; if (!src) { + ok = false; continue; } - const size_t off = (size_t) (p - slot_start[g]) * slot; - // move the displaced expert's slice back into RAM (repopulate pages) - if (e_out >= 0) { - ggml_backend_tensor_get(ent->dst[g], (void *) (src + (size_t) e_out * slot), off, slot); + ggml_backend_tensor_set(ent->dst[g], src, off, slot); + if (!verify_gpu_copy(ent->dst[g], off, ent->src, e_cold, src, slot)) { + ok = false; + } + } + if (ok) { + ste[p] = e_cold; + rout[e_cold] = 1; + dc[p] = -elapsed; // fresh dwell + swapped++; + swapped_in_layer++; + } + } + } + + last_sync_tokens = heatmap.tokens_total; + if (swapped > 0) { + update_luts(); + } + return swapped > 0; +} + +// byte offset of an exps tensor's single slot within its layer's staging region +static size_t staging_slot_off(const std::vector & layer, const llama_expert_hotstore::entry * ent) { + size_t off = 0; + for (const auto * e : layer) { + if (e == ent) { + break; + } + off += ggml_nbytes(e->src) / (size_t) e->src->ne[2]; + } + return off; +} + +bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { + if (!is_filled || hot_s <= 0 || buf_dev.empty()) { + return false; + } + if (llama_expert_preload::get_force()) { + return resync_full_mirror(heatmap); // --ecf: full store mirror every token + } + if (full_sync_remaining > 0) { + full_sync_remaining--; + // start-up full sync: swap up to hot_s/4 experts per layer this token, + // the mirror to the top-S spread evenly over 4 tokens (verified swaps) + return resync_full_mirror(heatmap, std::max(1, hot_s / 4)); + } + if (getenv("LLAMA_EXPERT_DEBUG")) { + fprintf(stderr, "hotstore: resync tok=%lld\n", (long long) heatmap.tokens_total); + } + + // tokens elapsed since the previous sync, used to age dwell counters + const int64_t elapsed = heatmap.tokens_total - last_sync_tokens; + int changed = 0; + for (int il = 0; il < n_layers; il++) { + auto & ste = slot_to_expert[il]; + auto & dc = dwell_count[il]; + auto & rout = gpu_routed[il]; + auto & pin = pending_in[il]; + auto & pout = pending_out[il]; + auto & stg = cpu_staging; // global staging + const size_t stg_off = cpu_staging_off[il]; + + // ---- pending move-outs: verify the staging copy (all per token), + // then hand the expert to the CPU and free the slot ------------ + for (auto it = pout.begin(); it != pout.end();) { + if (!it->verified) { + bool ok = true; + for (entry * ent : entries_by_layer[il]) { + const int pidx = llama_expert_preload::index_of(ent->src); + if (pidx < 0) { + continue; // mmap: file-backed, nothing to verify + } + const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; + const uint64_t exp = llama_expert_preload::expected_hash(ent->src, it->expert); + const uint64_t got = hash_slice_at(&stg[stg_off + staging_slot_off(entries_by_layer[il], ent)], slot); + if (exp == 0 || exp != got) { + ok = false; + break; + } } - // move the new expert's slice to the GPU - ggml_backend_tensor_set(ent->dst[g], src + (size_t) e_cold * slot, off, slot); - // verify the GPU copy landed; release the CPU slice only later - if (!verify_gpu_copy(ent->dst[g], off, (const uint8_t *) (src + (size_t) e_cold * slot), slot)) { - verified = false; + if (ok) { + it->verified = true; + it->countdown = 1; // CPU output counts on the next token + } else if (++it->failures >= 5) { + // anti-stall: the copy never verifies, abort the eviction + // and keep the expert on the GPU; the slot stays occupied + if (getenv("LLAMA_EXPERT_DEBUG")) { + fprintf(stderr, "hotstore: move-out ABORT expert %d after %d fails\n", it->expert, it->failures); + } + it = pout.erase(it); + continue; } } - if (verified) { + if (it->verified && --it->countdown <= 0) { + // hand the expert to the CPU and free the slot for (entry * ent : entries_by_layer[il]) { + const int pidx = llama_expert_preload::index_of(ent->src); + if (pidx < 0) { + continue; // mmap: data stays in the file + } const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; - pending_release.emplace_back(ent, e_cold); + llama_expert_preload::set_cpu_slice(pidx, it->expert, &stg[stg_off + staging_slot_off(entries_by_layer[il], ent)]); + } + rout[it->expert] = 0; // the CPU output counts now + ste[it->p] = -1; // the GPU slot is freed + changed++; + it = pout.erase(it); + } else { + ++it; + } + } + + // ---- pending move-ins: verify ALL copies every token; a confirmed + // one is routed to the GPU on the following token --------------- + for (auto it = pin.begin(); it != pin.end();) { + if (it->verified) { + ++it; + continue; + } + const int g = slot_device(slot_start, slot_end, it->p); + bool ok = g >= 0; + if (g >= 0) { + for (entry * ent : entries_by_layer[il]) { + const int pidx = llama_expert_preload::index_of(ent->src); + const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; + const size_t off = (size_t) (it->p - slot_start[g]) * slot; + const char * model_src = ent->src->data ? (const char *) ggml_get_data(ent->src) : nullptr; + const uint8_t * src = pidx >= 0 + ? llama_expert_preload::cpu_slice(pidx, it->expert) + : ((const uint8_t *) model_src) + (size_t) it->expert * slot; + if (!src || !verify_gpu_copy(ent->dst[g], off, ent->src, it->expert, src, slot)) { + ok = false; + } + } + } + if (ok) { + it->verified = true; + it->countdown = 1; // route to the GPU on the next token + ++it; + } else if (++it->failures >= 5) { + // anti-stall: abort the move-in and free the slot again + if (getenv("LLAMA_EXPERT_DEBUG")) { + fprintf(stderr, "hotstore: move-in ABORT expert %d after %d fails\n", it->expert, it->failures); + } + ste[it->p] = -1; + it = pin.erase(it); + } else { + ++it; + } + } + for (auto it = pin.begin(); it != pin.end();) { + if (it->verified && --it->countdown <= 0) { + rout[it->expert] = 1; // the GPU output counts now + for (entry * ent : entries_by_layer[il]) { + const int pidx = llama_expert_preload::index_of(ent->src); + if (pidx >= 0) { + llama_expert_preload::free_cpu_slice(pidx, it->expert); + } + } + changed++; + it = pin.erase(it); + } else { + ++it; + } + } + + // ---- boundary gate: extract the actual bottom-GPU and top-CPU heats + // from the routed sets (the store lags the ideal ordering) and + // gate BOTH the eviction and the move-in on them. + float lowest_gpu = INFINITY, highest_cpu = -INFINITY; + for (int e = 0; e < n_experts; e++) { + const float s = heatmap.get_score(il, e); + if (rout[e]) { + lowest_gpu = std::min(lowest_gpu, s); + } else { + highest_cpu = std::max(highest_cpu, s); + } + } + if (highest_cpu > lowest_gpu) { + // ---- eviction selection (1/token): a GPU expert leaves only when + // a CPU expert beats it by the hysteresis margin and it has + // dwelled. gated on the eviction queue capacity. + int evict_candidate = -1; + if (!llama_expert_preload::get_no_evict() && !getenv("LLAMA_EXPERT_NO_EVICT") && (int) pout.size() < max_concurrent_moves) { + std::vector routed; + for (int e = 0; e < n_experts; e++) { + if (rout[e]) { + routed.push_back(e); + } + } + std::sort(routed.begin(), routed.end(), [&](int a, int b) { + return heatmap.get_score(il, a) < heatmap.get_score(il, b); + }); + for (int e : routed) { + int p = -1; + for (int pp = 0; pp < hot_s; pp++) { + if (ste[pp] == e) { + p = pp; + break; + } + } + if (p < 0 || dc[p] < dwell) { + continue; // not an applicant yet + } + if (highest_cpu >= hyst * heatmap.get_score(il, e)) { + evict_candidate = e; + } + break; // monotonic: hotter experts fail too + } + } + if (evict_candidate >= 0 && (int) pout.size() < max_concurrent_moves) { + // queue: at most 2 move-outs per layer at a time + const int p = [&]() { for (int pp = 0; pp < hot_s; pp++) if (ste[pp] == evict_candidate) return pp; return -1; }(); + const int dg = p >= 0 ? slot_device(slot_start, slot_end, p) : -1; + if (p >= 0 && dg >= 0) { + // copy the evicted expert's slices into the staging buffer + for (entry * ent : entries_by_layer[il]) { + const int pidx = llama_expert_preload::index_of(ent->src); + if (pidx < 0) { + continue; // mmap: file-backed, no staging needed + } + const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; + const size_t off = (size_t) (p - slot_start[dg]) * slot; + ggml_backend_tensor_get(ent->dst[dg], &stg[stg_off + staging_slot_off(entries_by_layer[il], ent)], off, slot); + } + pout.push_back({evict_candidate, p, false, 0, 0}); + changed++; // the LUTs do not change yet, but the transition started + } + } + } // boundary gate + + // ---- move-in (1/token, gated): fill a free slot with the hottest CPU + // expert that should be on the GPU. check the free slot first (the + // common blocker), then the move-in queue (rarer), then evaluate. + int free_slot = -1; + for (int pp = 0; pp < hot_s; pp++) { + if (ste[pp] < 0) { + free_slot = pp; + break; + } + } + if (free_slot >= 0) { + if ((int) pin.size() < max_concurrent_moves) { // the queue is rarer than a missing slot + const std::vector top = heatmap.get_top_s(il, hot_s); + for (int e_cold : top) { + if (e_cold < 0 || e_cold >= n_experts || rout[e_cold]) { + continue; + } + const int dg = slot_device(slot_start, slot_end, free_slot); + if (dg < 0) { + break; + } + // copy the new expert in; keep it CPU-counted until verified + for (entry * ent : entries_by_layer[il]) { + const int pidx = llama_expert_preload::index_of(ent->src); + const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; + const size_t off = (size_t) (free_slot - slot_start[dg]) * slot; + const char * model_src = ent->src->data ? (const char *) ggml_get_data(ent->src) : nullptr; + const uint8_t * src = pidx >= 0 + ? llama_expert_preload::cpu_slice(pidx, e_cold) + : ((const uint8_t *) model_src) + (size_t) e_cold * slot; + if (!src) { + continue; + } + ggml_backend_tensor_set(ent->dst[dg], src, off, slot); + } + ste[free_slot] = e_cold; + pin.push_back({e_cold, free_slot, false, 0, 0}); + dc[free_slot] = -elapsed; + changed++; + break; // one move-in per layer per token } - } else if (getenv("LLAMA_EXPERT_DEBUG")) { - LLAMA_LOG("=== expert hot store: hash mismatch on move-in of expert %d, keeping CPU copy ===\n", e_cold); } - ste[p] = e_cold; - dc[p] = -elapsed; // fresh dwell: aging below brings it to 0 - swapped++; - swapped_in_layer++; } for (int p = 0; p < hot_s; p++) { @@ -456,13 +831,13 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { } last_sync_tokens = heatmap.tokens_total; - if (swapped > 0) { + if (changed > 0) { update_luts(); if (getenv("LLAMA_EXPERT_DEBUG")) { - LLAMA_LOG("=== Expert hot store: re-sync swapped %d expert slots ===\n", swapped); + fprintf(stderr, "=== Expert hot store: re-sync changed %d slots ===\n", changed); } } - return swapped > 0; + return changed > 0; } bool llama_expert_hotstore::maybe_resync(const llama_expert_heatmap & heatmap, bool multi_slot) { @@ -471,6 +846,12 @@ bool llama_expert_hotstore::maybe_resync(const llama_expert_heatmap & heatmap, b return false; } if (heatmap.tokens_total / sync_period > last_sync_tokens / sync_period) { + if (!full_sync_done && heatmap.generated_tokens_count >= 4) { + // after the 3-token heat boost, mirror the store to the top-S over + // the next 4 tokens (budget hot_s/4 per layer per token) + full_sync_done = true; + full_sync_remaining = 4; + } return resync_top_s(heatmap); } return false; @@ -493,21 +874,31 @@ void llama_expert_hotstore::update_luts() { if (hot_s <= 0 || luts.empty() || buf_dev.empty()) { return; } + if (getenv("LLAMA_EXPERT_DEBUG")) { + static int once = 0; + if (!once) { + once = 1; + const char * base = (const char *) ggml_backend_buffer_get_base(buf_dev[0].get()); + fprintf(stderr, "hotstore: update_luts hot_lut[0] data_off=%td buf_base=%p\n", + (const char *) luts[0].hot_lut[0]->data - base, (const void *) base); + } + } std::vector cold_mask_h(n_experts); for (int il = 0; il < n_layers; il++) { - const auto & ste = slot_to_expert[il]; + const auto & ste = slot_to_expert[il]; + const auto & rout = gpu_routed[il]; - // per-device LUTs: an expert whose global slot is on device g maps to - // the LOCAL slot index there; everything else maps to that device's - // local sentinel slot (zero contribution). + // per-device LUTs: an expert whose slot is on device g AND whose output + // currently comes from the GPU maps to the LOCAL slot index there; + // everything else (cold / pending) maps to the sentinel slot. for (int g = 0; g < n_devices; g++) { const int local_slots = slot_end[g] - slot_start[g]; std::vector hot_lut_h(n_experts, local_slots); for (int p = slot_start[g]; p < slot_end[g]; p++) { const int e = ste[p]; - if (e >= 0 && e < n_experts) { + if (e >= 0 && e < n_experts && rout[e]) { hot_lut_h[e] = p - slot_start[g]; } } @@ -519,15 +910,30 @@ void llama_expert_hotstore::update_luts() { for (int e = 0; e < n_experts; e++) { cold_mask_h[e] = 1; } - // residents override - for (int p = 0; p < hot_s; p++) { - const int e = ste[p]; - if (e >= 0 && e < n_experts) { + // GPU-counted experts override + for (int e = 0; e < n_experts; e++) { + if (rout[e]) { cold_mask_h[e] = 0; } } ggml_backend_tensor_set(luts[il].cold_mask, cold_mask_h.data(), 0, n_experts * sizeof(int32_t)); + if (getenv("LLAMA_EXPERT_DEBUG") && il == 0) { + static int once = 0; + if (!once) { + once = 1; + std::vector rb_hot(n_experts); + ggml_backend_tensor_get(luts[0].hot_lut[0], rb_hot.data(), 0, n_experts * sizeof(int32_t)); + fprintf(stderr, "hotstore: hot_lut[0..7]=%d %d %d %d %d %d %d %d cold_mask[0..3]=%d %d %d %d [96]=%d [97]=%d\n", + rb_hot[0], rb_hot[1], rb_hot[2], rb_hot[3], rb_hot[4], rb_hot[5], rb_hot[6], rb_hot[7], + ((const int32_t *) luts[0].cold_mask->data)[0], + ((const int32_t *) luts[0].cold_mask->data)[1], + ((const int32_t *) luts[0].cold_mask->data)[2], + ((const int32_t *) luts[0].cold_mask->data)[3], + ((const int32_t *) luts[0].cold_mask->data)[96], + ((const int32_t *) luts[0].cold_mask->data)[97]); + } + } } } @@ -556,29 +962,29 @@ void llama_expert_hotstore::log_hit_rate(const std::vector 0) { - LLAMA_LOG("=== expert hot hit rate: %zu/%zu = %.1f%% ===\n", hits, total, 100.0f * (float) hits / (float) total); + fprintf(stderr, "=== expert hot hit rate: %zu/%zu = %.1f%% ===\n", hits, total, 100.0f * (float) hits / (float) total); } } void llama_expert_hotstore::log() const { - LLAMA_LOG("=== Expert hotstore sizing (S=%d) ===\n", hot_s); + fprintf(stderr, "=== Expert hotstore sizing (S=%d) ===\n", hot_s); const bool debug = getenv("LLAMA_EXPERT_DEBUG") != nullptr; - size_t total = 0; - for (int il = 0; il < n_layers; il++) { + size_t total = 0; for (int il = 0; il < n_layers; il++) { total += bytes_per_slot[il]; if (debug) { - LLAMA_LOG(" layer %3d: bytes/slot = %zu\n", il, bytes_per_slot[il]); + fprintf(stderr, " layer %3d: bytes/slot = %zu\n", il, bytes_per_slot[il]); } } - LLAMA_LOG(" total bytes/slot across all layers = %zu (%zu MiB)\n", + fprintf(stderr, " total bytes/slot across all layers = %zu (%zu MiB)\n", total, total / (1024 * 1024)); if (!buf_dev.empty()) { - LLAMA_LOG(" GPU hot store allocated: %s, %zu bytes (%zu MiB) for %d+1 slots across %d device(s) (%d expert + 1 sentinel per device)\n", + fprintf(stderr, " GPU hot store allocated: %s, %zu bytes (%zu MiB) for %d+1 slots across %d device(s) (%d expert + 1 sentinel per device)\n", ggml_backend_buffer_name(buf_dev[0].get()), ggml_backend_buffer_get_size(buf_dev[0].get()), ggml_backend_buffer_get_size(buf_dev[0].get()) / (1024 * 1024), hot_s, n_devices, hot_s); } else if (hot_s > 0) { - LLAMA_LOG(" hot store DISABLED (%d slots requested)\n", hot_s); + fprintf(stderr, " hot store DISABLED (%d slots requested)\n", hot_s); } } + diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index a87c7d71128..70702b7f6a5 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -64,23 +64,61 @@ struct llama_expert_hotstore { // true once the first copy of the top-S experts landed (once per session) bool is_filled = false; + // true when the store buffer was streamed by the loader (startup batch + // already resident), so the fill does not copy again + bool preloaded = false; // re-sync cadence in tokens; 0 disables periodic re-sync int sync_period = 0; // tokens_total at the last sync (fill or re-sync) for boundary-cross check int64_t last_sync_tokens = 0; + // start-up full sync: after the 3-token heat boost, mirror the store to the + // top-S over the next `full_sync_remaining` tokens (budget hot_s/4 per token) + bool full_sync_done = false; + int full_sync_remaining = 0; + // hysteresis gate: a resident slot is only swapped when a cold // expert scores >= hyst * the incumbent AND the slot has dwelled long enough float hyst = 0.0f; // 0 = gate off (swap freely) int dwell = 0; // minimum syncs a resident must keep; 0 = off + // max concurrent transfers in flight per layer, per direction (eviction + // queue + promotion queue). higher = faster store adaptation, at the cost + // of more slots temporarily in transition (not counted). + int max_concurrent_moves = 3; // dwell_count[il][p] = syncs since slot p last changed (0 = fresh/empty) std::vector> dwell_count; - // experts whose GPU copy is hash-verified but whose CPU slice is not yet - // released (deferred madvise until a full token generated from the GPU). - // stored as (entry pointer, expert id); entries are stable after the ctor. - std::vector> pending_release; + // swap lifecycle handshake. slot_to_expert holds the physical slot + // content; gpu_routed holds the experts whose output actually comes from + // the GPU. a moved-in expert stays CPU-counted (gpu_routed=0) while it is + // pending verification; all pending copies are verified every token, and a + // confirmed one is routed to the GPU only on the following token. a + // moved-out expert is copied back on read, becomes CPU-counted, and runs + // one full generation on the CPU before its GPU copy is considered gone. + struct pending_move_in { + int expert; + int p; // slot holding the copy + bool verified; + int countdown; // 1 = route to the GPU on the next token + int failures; // consecutive failed verifies (anti-stall) + }; + struct pending_move_out { + int expert; + int p; // slot to free once the CPU takes over + bool verified; // staging copy matches the launch hash + int countdown; // 1 = CPU output counts on the next token + int failures; // consecutive failed verifies (anti-stall) + }; + std::vector> gpu_routed; // [il][e] + std::vector> pending_in; // [il] + std::vector> pending_out;// [il] + + // per-layer staging buffer: one expert slot per exps tensor of the layer, + // holding the in-flight evicted expert's slices while the CPU copy is + // verified against the launch hash (the GPU output stays valid meanwhile). + std::vector cpu_staging; + std::vector cpu_staging_off; // [il] offset into cpu_staging llama_expert_hotstore(const llama_model * model, int n_layers, int n_experts, int hot_s, int sync_period = 0, @@ -106,6 +144,10 @@ llama_expert_hotstore(const llama_model * model, int n_layers, // returns true if any slot changed (caller should synchronize the GPU). bool resync_top_s(const llama_expert_heatmap & heatmap); + // --ecf mode: mirror the entire store to the top-S every token (direct + // swaps, hash-verified, copy-on-read). no pacing queues. + bool resync_full_mirror(const llama_expert_heatmap & heatmap, int budget = 1); + // cadence-gated wrapper: re-sync only if tokens_total crossed sync_period; // multi_slot freezes the hot store (static slots, no swapping). returns // true if a re-sync ran and swapped slots. diff --git a/src/llama-expert-preload.cpp b/src/llama-expert-preload.cpp new file mode 100644 index 00000000000..5b07b494abb --- /dev/null +++ b/src/llama-expert-preload.cpp @@ -0,0 +1,367 @@ +#include "llama-expert-preload.h" + +#include "ggml.h" +#include "ggml-backend.h" +#include "ggml-cpu.h" + +#include +#include +#include +#include +#include + +#ifdef _WIN32 +#include +#else +#include +#include +#include +#endif + +namespace llama_expert_preload { + +namespace { + // matches an expert weight tensor, e.g. blk.0.ffn_gate_exps.weight + const std::regex g_re_exps("blk\\.(\\d+)\\.ffn_(up|down|gate|gate_up)_(ch|)exps\\.weight"); + + int g_slots = 0; + + struct ggml_backend_buffer * g_gpu_buf = nullptr; + struct ggml_context * g_ctx = nullptr; // temp context for the store write tensors + uint8_t * g_cpu_buf = nullptr; // host buffer for the cold experts + size_t g_cpu_size = 0; + std::vector g_entries; + std::unordered_map g_src_idx; // src -> entry index + std::vector> g_addrs; // [entry][expert] -> host address + std::vector> g_hashes; // [entry][expert] -> gguf FNV-1a(1024B) + size_t g_gpu_cursor = 0; // next free offset in the store + size_t g_cpu_cursor = 0; // next free offset in the host buffer + + static uint64_t fnv1a(const uint8_t * p, size_t n) { + uint64_t h = 0xcbf29ce484222325ULL; + for (size_t i = 0; i < n; i++) { + h ^= p[i]; + h *= 0x100000001b3ULL; + } + return h; + } + + std::string g_path; + int g_fd = -1; + + // C callback for the ggml cold op: resolve a cold expert's address from the + // table (set at write time, so it always matches where the slice landed) + const uint8_t * preload_slice_cb(const struct ggml_tensor * src0, int expert) { + if (!g_cpu_buf || !src0 || expert < 0) { + return nullptr; + } + const int i = index_of(src0); + if (i < 0 || expert >= (int) g_addrs[i].size()) { + return nullptr; + } + return (const uint8_t *) (uintptr_t) g_addrs[i][expert]; + } +} + +void set_model_path(const char * path) { + g_path = path ? path : ""; + if (g_fd >= 0) { + close(g_fd); + g_fd = -1; + } + g_fd = open(g_path.c_str(), O_RDONLY); +} + +void set_slots(int s) { + g_slots = s; +} + +int get_slots() { + return g_slots; +} + +bool g_force = false; +bool g_no_evict = false; + +void set_force(bool force) { + g_force = force; +} + +bool get_force() { + return g_force; +} + +void set_no_evict(bool no_evict) { + g_no_evict = no_evict; +} + +bool get_no_evict() { + return g_no_evict; +} + +bool tier_will_engage() { + if (g_slots <= 0) { + return false; + } + if (g_force || getenv("LLAMA_EXPERT_CACHE_FORCE") != nullptr) { + return true; + } + for (size_t i = 0; i < ggml_backend_dev_count(); i++) { + const ggml_backend_dev_t dev = ggml_backend_dev_get(i); + if (dev && ggml_backend_dev_type(dev) == GGML_BACKEND_DEVICE_TYPE_GPU) { + return true; // any GPU backend (CUDA, Vulkan, ROCm, SYCL, Metal, ...) + } + } + return false; +} + +size_t align_up256(size_t x) { + const size_t align = 256; + return (x + align - 1) & ~(align - 1); +} + +size_t store_total_bytes(size_t entries_bytes, int n_layers, int n_experts, int slots) { + size_t off = align_up256(entries_bytes); + for (int il = 0; il < n_layers; il++) { + off = align_up256(off); + off += align_up256((size_t) n_experts * sizeof(int32_t)); + off = align_up256(off); + off += align_up256((size_t) (slots + 1) * sizeof(float)); + } + return off; +} + +bool is_exps(const char * name, int & layer_idx) { + if (!name) { + return false; + } + std::cmatch m; + if (!std::regex_search(name, m, g_re_exps)) { + return false; + } + layer_idx = std::stoi(m[1].str()); + return true; +} + +void begin(struct ggml_backend_buffer_type * buft, size_t gpu_bytes, size_t cpu_bytes, int max_entries) { + if (g_gpu_buf || g_cpu_buf) { + return; // load_all_data can run more than once (fit estimate + real load) + } + g_gpu_buf = ggml_backend_buft_alloc_buffer(buft, gpu_bytes); + g_ctx = ggml_init({ ggml_tensor_overhead() * (max_entries + 8), nullptr, true }); + g_cpu_buf = (uint8_t *) malloc(cpu_bytes); + g_cpu_size = cpu_bytes; + g_entries.clear(); + g_src_idx.clear(); + g_addrs.clear(); + g_hashes.clear(); + g_gpu_cursor = 0; + g_cpu_cursor = 0; +} + +size_t register_tensor(const ggml_tensor * src, size_t plane_bytes, int n_experts, int startup, + size_t file_off, int fd) { + for (size_t i = 0; i < g_entries.size(); i++) { + if (g_entries[i].src == src) { + g_entries[i].fd = fd; // refresh: the file may be reopened between passes + return i; // already registered (second load pass) + } + } + const size_t gpu_off = g_gpu_cursor; + const size_t cpu_off = g_cpu_cursor; + g_entries.push_back({src, plane_bytes, gpu_off, cpu_off, file_off, fd, n_experts, startup}); + g_src_idx[src] = g_entries.size() - 1; + g_addrs.emplace_back((size_t) n_experts, 0); + g_hashes.emplace_back((size_t) n_experts, 0); + g_gpu_cursor += (size_t) (startup + 1) * plane_bytes; + g_cpu_cursor += (size_t) n_experts * plane_bytes; // all experts, cold committed at load + return g_entries.size() - 1; +} + +bool write_entry(size_t idx, const uint8_t * data, size_t nbytes) { + if (idx >= g_entries.size() || !data) { + return false; + } + const entry & e = g_entries[idx]; + if (nbytes < (size_t) e.startup * e.plane_bytes) { + return false; + } + // the startup store copy is deferred to the first token (copy_top_s fills + // it from the file, sequentially, each slot hash-verified). here we only + // record the ground-truth hashes for the startup experts. + const size_t chunk = e.plane_bytes < 1024 ? e.plane_bytes : 1024; + for (int ex = 0; ex < e.startup; ex++) { + g_hashes[idx][ex] = fnv1a(data + (size_t) ex * e.plane_bytes, chunk); + } + return true; +} + +bool read_expert(size_t idx, int expert, void * out, size_t n) { + if (idx >= g_entries.size() || expert < 0 || expert >= g_entries[idx].n_experts) { + return false; + } + const entry & e = g_entries[idx]; + if (n > e.plane_bytes) { + return false; + } + const ssize_t got = pread(g_fd >= 0 ? g_fd : e.fd, out, n, + (off_t) (e.file_off + (size_t) expert * e.plane_bytes)); + return got == (ssize_t) n; +} + +bool write_cold(size_t idx, const uint8_t * data, size_t nbytes) { + if (idx >= g_entries.size() || !g_cpu_buf || !data) { + fprintf(stderr, "write_cold: FAIL idx=%zu cpu_buf=%p data=%p nbytes=%zu\n", + idx, (void *) g_cpu_buf, (void *) data, nbytes); + return false; + } + const entry & e = g_entries[idx]; + const size_t dst = e.cpu_offset + (size_t) e.startup * e.plane_bytes; + if (dst + nbytes > g_cpu_size) { + fprintf(stderr, "write_cold: OUT OF BOUNDS\n"); + return false; + } + std::memcpy(g_cpu_buf + dst, data, nbytes); + const size_t chunk = e.plane_bytes < 1024 ? e.plane_bytes : 1024; + for (int ex = e.startup; ex < e.n_experts; ex++) { + g_addrs[idx][ex] = (uint64_t) (uintptr_t) (g_cpu_buf + e.cpu_offset + (size_t) ex * e.plane_bytes); + g_hashes[idx][ex] = fnv1a(data + (size_t) (ex - e.startup) * e.plane_bytes, chunk); + } + if (getenv("LLAMA_EXPERT_DEBUG") && idx == 0) { + fprintf(stderr, "write_cold: idx0 %s first bytes: %02x %02x %02x %02x\n", + e.src->name, g_cpu_buf[dst], g_cpu_buf[dst+1], g_cpu_buf[dst+2], g_cpu_buf[dst+3]); + } + ggml_mmid_cold_set_slice_fn(preload_slice_cb); + ggml_mmid_cold_set_hash_fn( + [](const struct ggml_tensor * src0, int expert) -> uint64_t { + return expected_hash(src0, expert); + }); + return true; +} + +struct ggml_backend_buffer * take_buffer() { + struct ggml_backend_buffer * b = g_gpu_buf; + g_gpu_buf = nullptr; + if (g_ctx) { + ggml_free(g_ctx); + g_ctx = nullptr; + } + return b; +} + +size_t num_entries() { + return g_entries.size(); +} + +const entry * entry_at(size_t idx) { + return idx < g_entries.size() ? &g_entries[idx] : nullptr; +} + +int index_of(const ggml_tensor * src) { + if (!src) { + return -1; + } + for (size_t i = 0; i < g_entries.size(); i++) { + if (g_entries[i].src == src) { + return (int) i; + } + } + // the hotstore's entry tensors can be distinct objects with the same name + // (created in a different context); fall back to matching by name + for (size_t i = 0; i < g_entries.size(); i++) { + if (g_entries[i].src && g_entries[i].src->name[0] && + strcmp(g_entries[i].src->name, src->name) == 0) { + return (int) i; + } + } + return -1; +} + +uint64_t expected_hash(const ggml_tensor * src, int expert) { + const int idx = index_of(src); + if (idx < 0 || expert < 0 || expert >= (int) g_hashes[idx].size()) { + return 0; + } + return g_hashes[idx][expert]; +} + +size_t entries_size() { + return g_gpu_cursor; +} + +const uint8_t * cpu_slice(size_t idx, int expert) { + if (idx >= g_entries.size() || !g_cpu_buf) { + return nullptr; + } + const entry & e = g_entries[idx]; + if (expert < 0 || expert >= e.n_experts) { + return nullptr; + } + return g_cpu_buf + e.cpu_offset + (size_t) expert * e.plane_bytes; +} + +static void release_pages(void * ptr, size_t len) { +#ifdef _WIN32 + SYSTEM_INFO si; + GetSystemInfo(&si); + const size_t page = si.dwPageSize; +#else + const long page = sysconf(_SC_PAGESIZE); +#endif + const uintptr_t base = (uintptr_t) ptr; + const uintptr_t start = (base + (uintptr_t) page - 1) & ~((uintptr_t) page - 1); + const uintptr_t end = (base + len) & ~((uintptr_t) page - 1); + if (start < end) { +#ifdef _WIN32 + VirtualFree((LPVOID) start, end - start, MEM_RESET); +#else + madvise((void *) start, end - start, MADV_DONTNEED); +#endif + } +} + +void free_cpu_slice(size_t idx, int expert) { + if (idx >= g_entries.size() || !g_cpu_buf) { + return; + } + const entry & e = g_entries[idx]; + if (expert < 0 || expert >= e.n_experts) { + return; + } + release_pages(g_cpu_buf + e.cpu_offset + (size_t) expert * e.plane_bytes, e.plane_bytes); +} + +void set_cpu_slice(size_t idx, int expert, const uint8_t * data) { + if (idx >= g_entries.size() || !g_cpu_buf || !data) { + return; + } + const entry & e = g_entries[idx]; + if (expert < 0 || expert >= e.n_experts) { + return; + } + std::memcpy(g_cpu_buf + e.cpu_offset + (size_t) expert * e.plane_bytes, data, e.plane_bytes); + g_addrs[idx][expert] = (uint64_t) (uintptr_t) (g_cpu_buf + e.cpu_offset + (size_t) expert * e.plane_bytes); +} + +void clear() { + if (g_gpu_buf) { + ggml_backend_buffer_free(g_gpu_buf); + g_gpu_buf = nullptr; + } + if (g_ctx) { + ggml_free(g_ctx); + g_ctx = nullptr; + } + if (g_cpu_buf) { + free(g_cpu_buf); + g_cpu_buf = nullptr; + } + g_cpu_size = 0; + g_entries.clear(); + g_src_idx.clear(); + g_addrs.clear(); + g_gpu_cursor = 0; + g_cpu_cursor = 0; +} + +} // namespace llama_expert_preload diff --git a/src/llama-expert-preload.h b/src/llama-expert-preload.h new file mode 100644 index 00000000000..db089d630ce --- /dev/null +++ b/src/llama-expert-preload.h @@ -0,0 +1,84 @@ +#pragma once + +#include +#include + +struct ggml_tensor; +struct ggml_backend_buffer; +struct ggml_backend_buffer_type; + +// pre-load handoff between the model loader and the expert hot store. +// +// when the tier is active (--expert-hot-s set), the model loader does not +// allocate the expert weight tensors at all; instead it streams their data +// into two buffers owned here: a GPU store holding the first S experts of +// every layer, and a host buffer holding the remaining (cold) experts. this +// keeps the experts entirely outside the model's own buffer plan, so a model +// larger than RAM can load when the GPU store supplies the missing capacity. +// the hotstore adopts the GPU store at context init; the cold op reads the +// host buffer through a slice hook. +namespace llama_expert_preload { + + void set_slots(int s); + int get_slots(); + void set_model_path(const char * path); // for the debug disk hash + void set_force(bool force); // --ecf / LLAMA_EXPERT_CACHE_FORCE + bool get_force(); // full-sync-every-token mode + void set_no_evict(bool no_evict); // --expert-no-evict + bool get_no_evict(); + + // true when the tier will actually build a hot store: slots requested AND + // (forced OR a CUDA device is present). mirrors the gate in llama-context.cpp. + bool tier_will_engage(); + + // backend-agnostic 256-byte alignment for the store's LUT region: some + // backends (Vulkan) require minStorageBufferOffsetAlignment for get_rows + // sources. returns the total store bytes (entries + padded LUTs). + size_t store_total_bytes(size_t entries_bytes, int n_layers, int n_experts, int slots); + size_t align_up256(size_t x); + + // true if `name` matches an exps weight tensor; sets layer_idx on match + bool is_exps(const char * name, int & layer_idx); + + struct entry { + const ggml_tensor * src; + size_t plane_bytes; // bytes of one expert slice in this tensor + size_t gpu_offset; // offset of this entry's planes in the store buffer + size_t cpu_offset; // offset of this entry's cold experts in the host buffer + size_t file_off; // absolute gguf data offset of this tensor + int fd; // model file descriptor (for the debug disk read) + int n_experts; + int startup; // first S experts (live on the GPU) + }; + + // loader side. begin() allocates the two buffers (single call, after the + // loader computed the sizes); register_tensor() adds an entry; write_entry() + // writes the startup slices to the store; write_cold() writes the rest to + // the host buffer. + void begin(struct ggml_backend_buffer_type * buft, size_t gpu_bytes, size_t cpu_bytes, int max_entries); + size_t register_tensor(const ggml_tensor * src, size_t plane_bytes, int n_experts, int startup, + size_t file_off, int fd); + bool write_entry(size_t idx, const uint8_t * data, size_t nbytes); + bool read_expert(size_t idx, int expert, void * out, size_t n); // from the gguf file + bool write_cold(size_t idx, const uint8_t * data, size_t nbytes); + + // hotstore + cold-op side. + struct ggml_backend_buffer * take_buffer(); + size_t num_entries(); + const entry * entry_at(size_t idx); + int index_of(const ggml_tensor * src); + size_t entries_size(); // bytes used by the entry regions in the store + + // cold expert slice access (nullptr when the slice is on the GPU) + const uint8_t * cpu_slice(size_t idx, int expert); + void free_cpu_slice(size_t idx, int expert); + void set_cpu_slice(size_t idx, int expert, const uint8_t * data); + + // debug: ground-truth FNV-1a of the first 1024 bytes of an expert slice, + // taken straight from the GGUF at load. compare against the hash of the + // slice actually read to verify a copy/routing is correct. + uint64_t expected_hash(const ggml_tensor * src, int expert); + + void clear(); + +} // namespace llama_expert_preload diff --git a/src/llama-model-loader.cpp b/src/llama-model-loader.cpp index b31e92e2da7..c4bf6077f46 100644 --- a/src/llama-model-loader.cpp +++ b/src/llama-model-loader.cpp @@ -1,4 +1,5 @@ #include "llama-model-loader.h" +#include "llama-expert-preload.h" #include "ggml-alloc.h" #include "ggml.h" @@ -13,6 +14,8 @@ #include #include #include +#include +#include static const size_t kiB = 1024; static const size_t MiB = 1024*kiB; @@ -530,6 +533,7 @@ llama_model_loader::llama_model_loader( const llama_model_kv_override * param_overrides_p, const llama_model_tensor_buft_override * param_tensor_buft_overrides_p) : metadata(meta), set_tensor_data(set_tensor_data), set_tensor_data_ud(set_tensor_data_ud) { + llama_expert_preload::set_model_path(fname.c_str()); int trace = 0; if (getenv("LLAMA_TRACE")) { trace = atoi(getenv("LLAMA_TRACE")); @@ -1296,6 +1300,28 @@ struct ggml_tensor * llama_model_loader::create_tensor( struct ggml_tensor * tensor = ggml_dup_tensor(ctx, &t_meta); ggml_set_name(tensor, ggml_get_name(&t_meta)); + // expert tier + no-mmap: the exps data lives in our buffers (GPU store for + // the hot experts, host buffer for the cold). give the tensor a valid ghost + // buffer so the model allocation skips it and the graph stays satisfied; + // the tier and the cold-op hook never read the tensor's own data. + if (!use_mmap && llama_expert_preload::tier_will_engage()) { + int il = -1; + if (llama_expert_preload::is_exps(tn.str().c_str(), il)) { + static ggml_backend_buffer_t ghost = nullptr; + static size_t ghost_size = 0; + const size_t nbytes = ggml_nbytes(&t_meta); + if (!ghost || nbytes > ghost_size) { + if (ghost) { + ggml_backend_buffer_free(ghost); + } + ghost = ggml_backend_buft_alloc_buffer(ggml_backend_cpu_buffer_type(), nbytes); + ggml_backend_buffer_set_usage(ghost, GGML_BACKEND_BUFFER_USAGE_WEIGHTS); + ghost_size = nbytes; + } + ggml_backend_tensor_alloc(ghost, tensor, ggml_backend_buffer_get_base(ghost)); + } + } + if (duplicated) { size_data += ggml_nbytes(&t_meta); } else { @@ -1511,6 +1537,49 @@ bool llama_model_loader::load_all_data( ggml_backend_name(upload_backend)); } + // tier + no-mmap + manual -ehs: stream the startup batch (first S experts + // per layer) into a GPU store buffer so those slices never commit RAM. + if (!use_mmap && llama_expert_preload::tier_will_engage() && !bufs.empty()) { + size_t gpu_total = 0; + size_t cpu_total = 0; + int n_entries = 0; + int n_layers = 0; + int n_experts = 0; + for (const auto & [name, w] : weights_map) { + int il = -1; + if (llama_expert_preload::is_exps(name.c_str(), il)) { + const size_t plane = ggml_nbytes(w.tensor) / (size_t) w.tensor->ne[2]; + gpu_total += (size_t) (llama_expert_preload::get_slots() + 1) * plane; + cpu_total += (size_t) w.tensor->ne[2] * plane; + n_entries++; + n_layers = std::max(n_layers, il + 1); + n_experts = (int) w.tensor->ne[2]; + } + } + if (n_entries > 0 && gpu_total > 0) { + // room for the per-layer hot_lut (i32[n_experts]) and mask_lut + // (f32[slots+1]) tensors after the slots; 256-aligned so backends + // with minStorageBufferOffsetAlignment can bind them for get_rows + gpu_total = llama_expert_preload::store_total_bytes( + gpu_total, n_layers, n_experts, llama_expert_preload::get_slots()); + // the store should live in VRAM when possible, else fall back to a + // host buffer (slower but functional) + ggml_backend_buffer_type_t buft = nullptr; + for (const auto & [idx, b] : bufs) { + ggml_backend_buffer_type_t bt = ggml_backend_buffer_get_type(b); + ggml_backend_dev_t d = ggml_backend_buft_get_device(bt); + if (d && ggml_backend_dev_type(d) == GGML_BACKEND_DEVICE_TYPE_GPU) { + buft = bt; + break; + } + } + if (!buft) { + buft = ggml_backend_cpu_buffer_type(); + } + llama_expert_preload::begin(buft, gpu_total, cpu_total, n_entries); + } + } + for (struct ggml_tensor * cur = ggml_get_first_tensor(ctx); cur != NULL; cur = ggml_get_next_tensor(ctx, cur)) { const auto * weight = get_weight(ggml_get_name(cur)); if (weight == nullptr) { @@ -1558,12 +1627,40 @@ bool llama_model_loader::load_all_data( const auto & file = files.at(weight->idx); if (ggml_backend_buffer_is_host(cur->buffer)) { - file->seek(weight->offs, SEEK_SET); - file->read_raw(cur->data, n_size); - if (check_tensors) { - validation_result.emplace_back(std::async(std::launch::async, [cur, n_size] { - return std::make_pair(cur, ggml_validate_row_data(cur->type, cur->data, n_size)); - })); + int il = -1; + if (llama_expert_preload::tier_will_engage() && llama_expert_preload::is_exps(ggml_get_name(cur), il)) { + // stream the startup batch: first S slices to the GPU store, + // the rest (cold) into our host buffer (the model tensor's + // data is only a placeholder; the cold-op hook reads ours) + const size_t plane = n_size / (size_t) cur->ne[2]; + const int S = llama_expert_preload::get_slots(); + if (getenv("LLAMA_EXPERT_DEBUG")) { + fprintf(stderr, "loader: exps %s off=%lld n_size=%zu plane=%zu\n", + ggml_get_name(cur), (long long) weight->offs, n_size, plane); + } + std::vector buf(n_size); + file->seek(weight->offs, SEEK_SET); + file->read_raw(buf.data(), n_size); + const size_t idx = llama_expert_preload::register_tensor(cur, plane, (int) cur->ne[2], S, + weight->offs, file->file_id()); + std::vector store_data((size_t) (S + 1) * plane, 0); + std::memcpy(store_data.data(), buf.data(), (size_t) S * plane); + llama_expert_preload::write_entry(idx, store_data.data(), store_data.size()); + llama_expert_preload::write_cold(idx, buf.data() + (size_t) S * plane, + (size_t) (cur->ne[2] - S) * plane); + if (check_tensors) { + validation_result.emplace_back(std::async(std::launch::async, [cur, n_size] { + return std::make_pair(cur, ggml_validate_row_data(cur->type, cur->data, n_size)); + })); + } + } else { + file->seek(weight->offs, SEEK_SET); + file->read_raw(cur->data, n_size); + if (check_tensors) { + validation_result.emplace_back(std::async(std::launch::async, [cur, n_size] { + return std::make_pair(cur, ggml_validate_row_data(cur->type, cur->data, n_size)); + })); + } } } else { // If upload_backend is valid load the tensor in chunks to pinned memory and upload the buffers asynchronously to the GPU. From cc0de31a6d09ebd4de7d773ae02aed6667a20213 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 9 Aug 2026 08:45:49 +0300 Subject: [PATCH 39/61] expert tier: fused cold path with no sentinel mask --- ggml/include/ggml.h | 17 + ggml/src/ggml-cpu/CMakeLists.txt | 2 + ggml/src/ggml-cpu/ggml-cpu-moe-cold.c | 312 +++++++++++++++++++ ggml/src/ggml-cpu/ggml-cpu-moe-cold.h | 18 ++ ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c | 4 + ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h | 4 + ggml/src/ggml-cpu/ggml-cpu.c | 30 ++ ggml/src/ggml.c | 54 +++- src/llama-context.cpp | 20 +- src/llama-expert-heatmap.cpp | 33 ++ src/llama-expert-heatmap.h | 3 + src/llama-expert-hotstore.cpp | 209 +++++++++---- src/llama-expert-hotstore.h | 21 +- src/llama-expert-preload.cpp | 21 +- src/llama-expert-tier.cpp | 83 ++++- src/llama-expert-tier.h | 24 +- src/llama-graph.cpp | 33 ++ 17 files changed, 809 insertions(+), 79 deletions(-) create mode 100644 ggml/src/ggml-cpu/ggml-cpu-moe-cold.c create mode 100644 ggml/src/ggml-cpu/ggml-cpu-moe-cold.h diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h index ae3cbcb623c..7a5376275b8 100644 --- a/ggml/include/ggml.h +++ b/ggml/include/ggml.h @@ -591,6 +591,7 @@ extern "C" { GGML_OP_GLU, GGML_OP_MUL_MAT_ID_COLD, + GGML_OP_MOE_COLD, GGML_OP_COUNT, }; @@ -1464,6 +1465,22 @@ extern "C" { struct ggml_tensor * counts, struct ggml_tensor * ptrs); + // fused cold-expert MoE for one layer: down(act(gate(x)) * up(x)) computed + // on the CPU for cold experts only (cold_mask[i] == 1); hot slots zeroed. + // act is 0 = silu (separate gate/up), 1 = gelu (fused gate_up tensor). + // counts (optional) accumulates per-expert routed hits, index [n_expert] = total. + // x must be [n_embd, 1, n_tokens]; result is [down->ne[1], ids->ne[0], n_tokens] + GGML_API struct ggml_tensor * ggml_moe_cold( + struct ggml_context * ctx, + struct ggml_tensor * gate, + struct ggml_tensor * up, + struct ggml_tensor * down, + struct ggml_tensor * x, + struct ggml_tensor * ids, + struct ggml_tensor * cold_mask, + struct ggml_tensor * counts, + int32_t act); + // A: m columns, n rows, // B: p columns, n rows, // result is m columns, p rows diff --git a/ggml/src/ggml-cpu/CMakeLists.txt b/ggml/src/ggml-cpu/CMakeLists.txt index afb2043ebc0..f22fe6af4bd 100644 --- a/ggml/src/ggml-cpu/CMakeLists.txt +++ b/ggml/src/ggml-cpu/CMakeLists.txt @@ -31,6 +31,8 @@ function(ggml_add_cpu_backend_variant_impl tag_name) ggml-cpu/ggml-cpu.cpp ggml-cpu/ggml-cpu-mul-mat-id-cold.c ggml-cpu/ggml-cpu-mul-mat-id-cold.h + ggml-cpu/ggml-cpu-moe-cold.c + ggml-cpu/ggml-cpu-moe-cold.h ggml-cpu/repack.cpp ggml-cpu/repack.h ggml-cpu/hbm.cpp diff --git a/ggml/src/ggml-cpu/ggml-cpu-moe-cold.c b/ggml/src/ggml-cpu/ggml-cpu-moe-cold.c new file mode 100644 index 00000000000..74239125b2f --- /dev/null +++ b/ggml/src/ggml-cpu/ggml-cpu-moe-cold.c @@ -0,0 +1,312 @@ +#define _CRT_SECURE_NO_DEPRECATE // Disables "unsafe" warnings on Windows +#define _USE_MATH_DEFINES // For M_PI on MSVC + +#include "ggml.h" +#include "ggml-impl.h" +#include "ggml-cpu-impl.h" +#include "ggml-cpu.h" +#include "ops.h" +#include "ggml-cpu-moe-cold.h" +#include "ggml-cpu-mul-mat-id-cold.h" + +#if defined(_MSC_VER) || defined(__MINGW32__) +#include // using malloc.h with MSC/MINGW +#elif !defined(__FreeBSD__) && !defined(__NetBSD__) && !defined(__OpenBSD__) +#include +#endif + +#include +#include +#include + +#if defined(_WIN32) + +#define WIN32_LEAN_AND_MEAN +#ifndef NOMINMAX + #define NOMINMAX +#endif +#include + +#endif // _WIN32 + +#if defined(_MSC_VER) && !defined(__clang__) + +typedef volatile LONG atomic_int; + +typedef enum { + memory_order_relaxed, + memory_order_consume, + memory_order_acquire, + memory_order_release, + memory_order_acq_rel, + memory_order_seq_cst +} memory_order; + +static LONG atomic_fetch_add_explicit(atomic_int * ptr, LONG inc, memory_order mo) { + return InterlockedExchangeAdd(ptr, inc); +} + +#else // clang +#include +#endif + +// resolve a cold expert's weight slice through the registered hook, else the +// tensor's own data (mmap or the model buffer) +static const char * moe_cold_slice(const struct ggml_tensor * w, int64_t e, const char * fallback) { + const uint8_t * s = ggml_mmid_cold_get_slice(w, (int) e); + return s ? (const char *) s : fallback; +} + +// fused cold-expert MoE: computes down(act(gate(x)) * up(x)) only for slots +// whose expert is cold (cold_mask[e] == 1); hot slots are zeroed. +// src = {gate, up, down, x, ids, cold_mask}; op param 0 = act (0 silu, 1 gelu) +void ggml_compute_forward_moe_cold( + const struct ggml_compute_params * params, + struct ggml_tensor * dst) { + + const struct ggml_tensor * w_gate = dst->src[0]; + const struct ggml_tensor * w_up = dst->src[1]; + const struct ggml_tensor * w_down = dst->src[2]; + const struct ggml_tensor * x = dst->src[3]; + const struct ggml_tensor * ids = dst->src[4]; + const struct ggml_tensor * mask = dst->src[5]; + // counts (optional) accumulates per-expert routed hits, index [n_as] = total + int32_t * counts = dst->src[6] ? (int32_t *) dst->src[6]->data : NULL; + const int32_t act = ggml_get_op_params_i32(dst, 0); + + const int32_t * cold_mask = (const int32_t *) mask->data; + + const int ith = params->ith; + const int nth = params->nth; + + // gate/up share a type; down may use a different quant + const enum ggml_type type_g = w_gate->type; + const enum ggml_type type_d = w_down->type; + GGML_ASSERT(w_up->type == type_g); + GGML_ASSERT(x->type == GGML_TYPE_F32); + GGML_ASSERT(dst->type == GGML_TYPE_F32); + GGML_ASSERT(x->ne[1] == 1 && x->nb[0] == sizeof(float)); + + const int64_t ne_embd = x->ne[0]; + const int64_t n_ff = (w_gate == w_up) ? (w_gate->ne[1] / 2) : w_gate->ne[1]; + const int64_t n_tokens = x->ne[2]; + const int64_t n_out = w_down->ne[1]; + const int n_ids = ids->ne[0]; + const int n_as = w_gate->ne[2]; + + ggml_vec_dot_t const vec_dot_g = ggml_get_type_traits_cpu(type_g)->vec_dot; + enum ggml_type const vdt_g = ggml_get_type_traits_cpu(type_g)->vec_dot_type; + ggml_from_float_t const from_fx = ggml_get_type_traits_cpu(vdt_g)->from_float; + ggml_vec_dot_t const vec_dot_d = ggml_get_type_traits_cpu(type_d)->vec_dot; + enum ggml_type const vdt_d = ggml_get_type_traits_cpu(type_d)->vec_dot_type; + ggml_from_float_t const from_fa = ggml_get_type_traits_cpu(vdt_d)->from_float; + + const size_t q_embd = ggml_row_size(vdt_g, ne_embd); + const size_t q_ff = ggml_row_size(vdt_d, n_ff); + + void * wdata_cur = params->wdata; + + char * xq = (char *) incr_ptr_aligned(&wdata_cur, n_tokens*q_embd, sizeof(int64_t)); + + int64_t * matrix_row_counts = + (int64_t *) incr_ptr_aligned(&wdata_cur, n_as*sizeof(int64_t), sizeof(int64_t)); + + struct mmid_row_mapping * matrix_rows = + (struct mmid_row_mapping *) incr_ptr_aligned(&wdata_cur, n_as*(int64_t)n_ids*n_tokens*sizeof(struct mmid_row_mapping), sizeof(int64_t)); + + int64_t * col0 = + (int64_t *) incr_ptr_aligned(&wdata_cur, n_as*sizeof(int64_t), sizeof(int64_t)); + + char (*atomic_current_chunk)[CACHE_LINE_SIZE] = + (char (*)[CACHE_LINE_SIZE]) incr_ptr_aligned(&wdata_cur, CACHE_LINE_SIZE*n_as, CACHE_LINE_SIZE); + + // intermediates for the cold slots, indexed by global cold column + const int64_t maxc = (int64_t) n_ids*n_tokens; + float * gate_out = (float *) incr_ptr_aligned(&wdata_cur, 2*n_ff*maxc*sizeof(float), CACHE_LINE_SIZE); + float * up_out = gate_out + n_ff*maxc; + char * act_q = (char *) incr_ptr_aligned(&wdata_cur, q_ff*maxc, CACHE_LINE_SIZE); + + GGML_ASSERT(params->wsize >= (size_t)((char *) wdata_cur - (char *) params->wdata)); + + // quantize x once, shared by all experts + for (int64_t t = ith; t < n_tokens; t++) { + from_fx((const float *) ((const char *) x->data + t*x->nb[2]), xq + t*q_embd, ne_embd); + } + + if (ith == 0) { + memset(dst->data, 0, ggml_nbytes(dst)); + memset(matrix_row_counts, 0, n_as*sizeof(int64_t)); + + for (int64_t t = 0; t < n_tokens; t++) { + for (int id = 0; id < n_ids; id++) { + const int32_t e = *(const int32_t *) ((const char *) ids->data + t*ids->nb[1] + id*ids->nb[0]); + GGML_ASSERT(e >= 0 && e < n_as); + if (counts) { + counts[e]++; + counts[n_as]++; + } + if (cold_mask[e] == 0) { + continue; + } + matrix_rows[e*(int64_t)n_ids*n_tokens + matrix_row_counts[e]] = (struct mmid_row_mapping) {id, (int32_t) t}; + matrix_row_counts[e]++; + } + } + + int64_t coff = 0; + for (int e = 0; e < n_as; e++) { + col0[e] = coff; + coff += matrix_row_counts[e]; + } + } + + // reset phase-A chunk counters + for (int e = ith; e < n_as; e += nth) { + atomic_int * ctr = (atomic_int *)(atomic_current_chunk + e); + *ctr = nth; + } + + ggml_barrier(params->threadpool); + + // phase A: gate/up dots for all cold slots into gate_out/up_out + for (int cur_a = 0; cur_a < n_as; ++cur_a) { + const int64_t cne1 = matrix_row_counts[cur_a]; + if (cne1 == 0) { + continue; + } + const char * wg = moe_cold_slice(w_gate, cur_a, (const char *) w_gate->data + cur_a*w_gate->nb[2]); + const char * wu = (w_gate == w_up) ? (wg + n_ff*w_gate->nb[1]) + : moe_cold_slice(w_up, cur_a, (const char *) w_up->data + cur_a*w_up->nb[2]); + + const int64_t nr0 = n_ff; + const int64_t nr1 = cne1; + + int chunk_size = 16; + if (nr1 == 1) { + chunk_size = 64; + } + const bool disable_chunking = ggml_is_numa(); + int64_t nchunk0 = (nr0 + chunk_size - 1)/chunk_size; + int64_t nchunk1 = (nr1 + chunk_size - 1)/chunk_size; + if (nchunk0*nchunk1 < nth*4 || disable_chunking) { + nchunk0 = nr0 > nr1 ? nth : 1; + nchunk1 = nr0 > nr1 ? 1 : nth; + } + const int64_t dr0 = (nr0 + nchunk0 - 1)/nchunk0; + const int64_t dr1 = (nr1 + nchunk1 - 1)/nchunk1; + + int current_chunk = ith; + atomic_int * ctr = (atomic_int *)(atomic_current_chunk + cur_a); + + while (current_chunk < nchunk0*nchunk1) { + const int64_t ith0 = current_chunk % nchunk0; + const int64_t ith1 = current_chunk / nchunk0; + const int64_t ir0_start = dr0*ith0, ir0_end = MIN(ir0_start + dr0, nr0); + const int64_t ir1_start = dr1*ith1, ir1_end = MIN(ir1_start + dr1, nr1); + + for (int64_t c = ir1_start; c < ir1_end; c++) { + const struct mmid_row_mapping rm = matrix_rows[cur_a*(int64_t)n_ids*n_tokens + c]; + const char * xcol = xq + (int64_t) rm.i2*q_embd; + float * gout = gate_out + (col0[cur_a] + c)*n_ff; + float * uout = up_out + (col0[cur_a] + c)*n_ff; + for (int64_t i = ir0_start; i < ir0_end; i++) { + __builtin_prefetch(wg + (i + 1)*w_gate->nb[1], 0, 3); + __builtin_prefetch(wu + (i + 1)*w_up->nb[1], 0, 3); + vec_dot_g(ne_embd, &gout[i], 0, wg + i*w_gate->nb[1], 0, xcol, 0, 1); + vec_dot_g(ne_embd, &uout[i], 0, wu + i*w_up->nb[1], 0, xcol, 0, 1); + } + } + + if (nth >= nchunk0*nchunk1) { + break; + } + current_chunk = atomic_fetch_add_explicit(ctr, 1, memory_order_relaxed); + } + } + + ggml_barrier(params->threadpool); + + // phase B (multi-threaded): activation (SwiGLU/GELU) + quantize the intermediate + const int64_t total_cols = n_as > 0 ? (col0[n_as - 1] + matrix_row_counts[n_as - 1]) : 0; + + for (int64_t c = ith; c < total_cols; c += nth) { + float * go = gate_out + c*n_ff; + const float * uo = up_out + c*n_ff; + if (act == 1) { + for (int64_t i = 0; i < n_ff; i++) { + const float g = go[i]; + const float gelu_g = 0.5f * g * (1.0f + tanhf(0.7978845608028654f * g * (1.0f + 0.044715f * g * g))); + go[i] = gelu_g * uo[i]; + } + } else { + for (int64_t i = 0; i < n_ff; i++) { + const float g = go[i]; + const float silu_g = g / (1.0f + expf(-g)); + go[i] = silu_g * uo[i]; + } + } + from_fa(go, act_q + c*q_ff, n_ff); + } + + if (ith == 0) { + // reset phase-C chunk counters + for (int e = 0; e < n_as; e++) { + atomic_int * ctr = (atomic_int *)(atomic_current_chunk + e); + *ctr = nth; + } + } + + ggml_barrier(params->threadpool); + + // phase C: down dots for all cold slots, scattered into dst + for (int cur_a = 0; cur_a < n_as; ++cur_a) { + const int64_t cne1 = matrix_row_counts[cur_a]; + if (cne1 == 0) { + continue; + } + const char * wd = moe_cold_slice(w_down, cur_a, (const char *) w_down->data + cur_a*w_down->nb[2]); + + const int64_t nr0 = n_out; + const int64_t nr1 = cne1; + + int chunk_size = 16; + if (nr1 == 1) { + chunk_size = 64; + } + const bool disable_chunking = ggml_is_numa(); + int64_t nchunk0 = (nr0 + chunk_size - 1)/chunk_size; + int64_t nchunk1 = (nr1 + chunk_size - 1)/chunk_size; + if (nchunk0*nchunk1 < nth*4 || disable_chunking) { + nchunk0 = nr0 > nr1 ? nth : 1; + nchunk1 = nr0 > nr1 ? 1 : nth; + } + const int64_t dr0 = (nr0 + nchunk0 - 1)/nchunk0; + const int64_t dr1 = (nr1 + nchunk1 - 1)/nchunk1; + + int current_chunk = ith; + atomic_int * ctr = (atomic_int *)(atomic_current_chunk + cur_a); + + while (current_chunk < nchunk0*nchunk1) { + const int64_t ith0 = current_chunk % nchunk0; + const int64_t ith1 = current_chunk / nchunk0; + const int64_t ir0_start = dr0*ith0, ir0_end = MIN(ir0_start + dr0, nr0); + const int64_t ir1_start = dr1*ith1, ir1_end = MIN(ir1_start + dr1, nr1); + + for (int64_t c = ir1_start; c < ir1_end; c++) { + const struct mmid_row_mapping rm = matrix_rows[cur_a*(int64_t)n_ids*n_tokens + c]; + const char * acol = act_q + (col0[cur_a] + c)*q_ff; + float * dst_col = (float *) ((char *) dst->data + rm.i1*dst->nb[1] + (int64_t) rm.i2*dst->nb[2]); + for (int64_t j = ir0_start; j < ir0_end; j++) { + float res = 0.0f; + vec_dot_d(n_ff, &res, 0, wd + j*w_down->nb[1], 0, acol, 0, 1); + dst_col[j] += res; + } + } + + if (nth >= nchunk0*nchunk1) { + break; + } + current_chunk = atomic_fetch_add_explicit(ctr, 1, memory_order_relaxed); + } + } +} diff --git a/ggml/src/ggml-cpu/ggml-cpu-moe-cold.h b/ggml/src/ggml-cpu/ggml-cpu-moe-cold.h new file mode 100644 index 00000000000..43bc5881788 --- /dev/null +++ b/ggml/src/ggml-cpu/ggml-cpu-moe-cold.h @@ -0,0 +1,18 @@ +#pragma once + +// Fused cold-expert MoE kernel: down(act(gate(x)) * up(x)) for cold experts +// only, in a single CPU op. see ggml_moe_cold() in ggml.c for the op contract. + +#include "ggml-cpu-impl.h" + +#ifdef __cplusplus +extern "C" { +#endif + +void ggml_compute_forward_moe_cold( + const struct ggml_compute_params * params, + struct ggml_tensor * dst); + +#ifdef __cplusplus +} +#endif diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c index 98de0df3b0e..79c9dc75e92 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c @@ -26,6 +26,10 @@ void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn) { g_slice_fn = fn; } +const uint8_t * ggml_mmid_cold_get_slice(const struct ggml_tensor * src0, int expert) { + return g_slice_fn ? g_slice_fn(src0, expert) : NULL; +} + void ggml_mmid_cold_set_hash_fn(ggml_mmid_cold_hash_fn fn) { g_hash_fn = fn; } diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h index 3a5aa03d503..e22bf4f4e54 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h @@ -41,6 +41,10 @@ void ggml_compute_forward_mul_mat_id_cold( const struct ggml_compute_params * params, struct ggml_tensor * dst); +// resolve an expert slice through the registered hook (nullptr = fall back to +// the tensor's own data); shared by the MUL_MAT_ID_COLD and MOE_COLD kernels +const uint8_t * ggml_mmid_cold_get_slice(const struct ggml_tensor * src0, int expert); + #ifdef __cplusplus } #endif diff --git a/ggml/src/ggml-cpu/ggml-cpu.c b/ggml/src/ggml-cpu/ggml-cpu.c index 5052be07b2b..87f09a5f9cf 100644 --- a/ggml/src/ggml-cpu/ggml-cpu.c +++ b/ggml/src/ggml-cpu/ggml-cpu.c @@ -6,6 +6,7 @@ #include "traits.h" #include "ggml-cpu-impl.h" #include "ggml-cpu-mul-mat-id-cold.h" +#include "ggml-cpu-moe-cold.h" #include "ggml-impl.h" #include "quants.h" #include "ggml-threading.h" @@ -1839,6 +1840,10 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm { ggml_compute_forward_mul_mat_id_cold(params, tensor); } break; + case GGML_OP_MOE_COLD: + { + ggml_compute_forward_moe_cold(params, tensor); + } break; case GGML_OP_OUT_PROD: { ggml_compute_forward_out_prod(params, tensor); @@ -2329,6 +2334,7 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads) { case GGML_OP_MUL_MAT: case GGML_OP_MUL_MAT_ID: case GGML_OP_MUL_MAT_ID_COLD: + case GGML_OP_MOE_COLD: case GGML_OP_OUT_PROD: { n_tasks = n_threads; @@ -2873,6 +2879,30 @@ struct ggml_cplan ggml_graph_plan( // atomic_current_chunk cur += CACHE_LINE_SIZE*n_as + CACHE_LINE_SIZE; } break; + case GGML_OP_MOE_COLD: + { + cur = 0; + const struct ggml_tensor * w_gate = node->src[0]; + const struct ggml_tensor * w_down = node->src[2]; + const struct ggml_tensor * x = node->src[3]; + const struct ggml_tensor * ids = node->src[4]; + const enum ggml_type vdt_g = type_traits_cpu[w_gate->type].vec_dot_type; + const enum ggml_type vdt_d = type_traits_cpu[w_down->type].vec_dot_type; + const int n_as = w_gate->ne[2]; + const int64_t maxc = ids->ne[0]*ids->ne[1]; + // quantized x + cur += ggml_row_size(vdt_g, ggml_nelements(x)) + sizeof(int64_t); + // matrix_row_counts + col0 + cur += 2*n_as*sizeof(int64_t) + 2*sizeof(int64_t); + // matrix_rows + cur += n_as*maxc*sizeof(struct mmid_row_mapping) + sizeof(int64_t); + // atomic chunk counters + cur += CACHE_LINE_SIZE*n_as + CACHE_LINE_SIZE; + // gate_out + up_out + cur += 2*w_gate->ne[1]*maxc*sizeof(float) + CACHE_LINE_SIZE; + // act_q + cur += ggml_row_size(vdt_d, w_gate->ne[1])*maxc + CACHE_LINE_SIZE; + } break; case GGML_OP_OUT_PROD: { if (ggml_is_quantized(node->src[0]->type) || diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c index 061e6786bbc..22046d4e10c 100644 --- a/ggml/src/ggml.c +++ b/ggml/src/ggml.c @@ -1099,9 +1099,10 @@ static const char * GGML_OP_NAME[GGML_OP_COUNT] = { "GLU", "MUL_MAT_ID_COLD", + "MOE_COLD", }; -static_assert(GGML_OP_COUNT == 102, "GGML_OP_COUNT != 102"); +static_assert(GGML_OP_COUNT == 103, "GGML_OP_COUNT != 103"); static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = { "none", @@ -1215,9 +1216,10 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = { "glu(x)", "mul_mat_id_cold(x,x,x,x)", + "moe_cold(x,x,x,x,x,x)", }; -static_assert(GGML_OP_COUNT == 102, "GGML_OP_COUNT != 102"); +static_assert(GGML_OP_COUNT == 103, "GGML_OP_COUNT != 103"); static_assert(GGML_OP_POOL_COUNT == 2, "GGML_OP_POOL_COUNT != 2"); @@ -3397,6 +3399,54 @@ struct ggml_tensor * ggml_mul_mat_id_cold( return result; } +// ggml_moe_cold + +struct ggml_tensor * ggml_moe_cold( + struct ggml_context * ctx, + struct ggml_tensor * gate, + struct ggml_tensor * up, + struct ggml_tensor * down, + struct ggml_tensor * x, + struct ggml_tensor * ids, + struct ggml_tensor * cold_mask, + struct ggml_tensor * counts, + int32_t act) { + GGML_ASSERT(!ggml_is_transposed(gate) && !ggml_is_transposed(up) && !ggml_is_transposed(down)); + GGML_ASSERT(ids->type == GGML_TYPE_I32); + GGML_ASSERT(act == 0 || act == 1); + + GGML_ASSERT(gate->ne[3] == 1 && up->ne[3] == 1 && down->ne[3] == 1); + GGML_ASSERT(x->ne[3] == 1 && x->ne[1] == 1); + GGML_ASSERT(ids->ne[2] == 1 && ids->ne[3] == 1); + GGML_ASSERT(ids->ne[1] == x->ne[2]); + GGML_ASSERT(gate->ne[0] == x->ne[0] && up->ne[0] == x->ne[0]); + GGML_ASSERT(gate->ne[1] == up->ne[1]); + GGML_ASSERT(down->ne[0] == (gate == up ? gate->ne[1] / 2 : gate->ne[1])); + GGML_ASSERT(gate->ne[2] == up->ne[2] && up->ne[2] == down->ne[2]); + GGML_ASSERT(ids->ne[0] % x->ne[1] == 0); + GGML_ASSERT(cold_mask->type == GGML_TYPE_I32); + GGML_ASSERT(cold_mask->ne[0] == gate->ne[2]); + if (counts) { + GGML_ASSERT(counts->type == GGML_TYPE_I32); + GGML_ASSERT(counts->ne[0] >= gate->ne[2] + 1); + } + + const int64_t ne[4] = { down->ne[1], ids->ne[0], x->ne[2], 1 }; + struct ggml_tensor * result = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, ne); + + result->op = GGML_OP_MOE_COLD; + result->src[0] = gate; + result->src[1] = up; + result->src[2] = down; + result->src[3] = x; + result->src[4] = ids; + result->src[5] = cold_mask; + result->src[6] = counts; + ggml_set_op_params_i32(result, 0, act); + + return result; +} + // ggml_out_prod static inline bool ggml_can_out_prod(const struct ggml_tensor * t0, const struct ggml_tensor * t1) { diff --git a/src/llama-context.cpp b/src/llama-context.cpp index e1b9b1b3c00..ce86c5276f1 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -1426,6 +1426,10 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll expert_hotstore->copy_top_s(*expert_heatmap); } + if (expert_hotstore) { + expert_hotstore->reset_counts(); // zero the cold-op tallies for this token + } + const auto status = graph_compute(res->get_gf(), ubatch.n_tokens > 1); if (status != GGML_STATUS_SUCCESS) { LLAMA_LOG_ERROR("%s: failed to compute graph, compute status: %d\n", __func__, status); @@ -1433,19 +1437,21 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll return nullptr; } - if (expert_heatmap && (ubatch.n_tokens == 1 || !expert_hotstore || !expert_hotstore->is_filled)) { - synchronize(); - expert_heatmap->update_from_graph(res->moe_sel_experts); + // the cold op tallied the selected experts into host counts during the + // compute; feed them into the heatmap directly (no D2H readback, no sync) + if (expert_heatmap && expert_hotstore && expert_hotstore->is_filled) { + expert_hotstore->read_counts(*expert_heatmap, ubatch.n_tokens); } if (expert_heatmap && expert_hotstore) { if (!expert_hotstore->is_filled) { // fill happens pre-graph on the first ubatch (see above) } else { expert_hotstore->maybe_resync(*expert_heatmap, ubatch.n_tokens > 1); - // sync the moved store data into the graph's stream before the next - // graph launch, so the resync's copies never contend with the next - // token's generation - synchronize(); + // the post-resync sync is removed (default): the resync's store + // writes on the default stream race the graph's stream + if (getenv("LLAMA_EXPERT_SYNC_RESYNC")) { + synchronize(); + } if (ubatch.n_tokens == 1 && getenv("LLAMA_EXPERT_HITRATE")) { expert_hotstore->log_hit_rate(res->moe_sel_experts); } diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 6d1a495587a..bea10675b16 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -34,6 +34,39 @@ void llama_expert_heatmap::update(int layer_idx, const int32_t * expert_ids, int } } } +void llama_expert_heatmap::update_counts(const std::vector & per_layer, int n_tokens) { + // batched decay: apply decay_rate^2 every two updates instead of + // decay_rate every update (identical long-run weighting, half the work) + ++update_counter; + if (update_counter % 2 == 0) { + const float rate = decay_rate * decay_rate; + for (int i = 0; i < n_layers * n_experts; i++) { + heat[i] *= rate; + } + } + + if (n_tokens == 1) { + generated_tokens_count++; + } + for (int il = 0; il < n_layers && il < (int) per_layer.size(); il++) { + const int32_t * cnt = per_layer[il]; + if (!cnt) { + continue; + } + float * layer_heat = &heat[il * n_experts]; + for (int e = 0; e < n_experts; e++) { + if (cnt[e] > 0) { + layer_heat[e] += (float) cnt[e]; + } + } + } + + tokens_total += n_tokens; + if (log_period > 0 && tokens_total / log_period > (tokens_total - n_tokens) / log_period) { + log(); + } +} + void llama_expert_heatmap::update_from_graph(const std::vector> & moe_sel_experts) { if (moe_sel_experts.empty()) { return; diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index 83da61c560c..d7ced8e402c 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -24,6 +24,9 @@ struct llama_expert_heatmap { void update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens, float multiplier = 1.0f); void update_from_graph(const std::vector> & moe_sel_experts); + // cold-op counts path: per-layer tallies of the selected experts (host + // memory). advances tokens_total; the first-3-token boost lives in get_score. + void update_counts(const std::vector & per_layer, int n_tokens); void decay_all(); void log() const; diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 77b163ff711..6e7aa800bca 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -11,6 +11,7 @@ #include #include +#include #include #ifdef _WIN32 @@ -326,6 +327,7 @@ bool llama_expert_hotstore::allocate( ctx_cpu = ggml_context_ptr(ggml_init(params_cpu)); for (int il = 0; il < n_layers; il++) { luts[il].cold_mask = ggml_new_tensor_1d(ctx_cpu.get(), GGML_TYPE_I32, n_experts); + luts[il].counts = ggml_new_tensor_1d(ctx_cpu.get(), GGML_TYPE_I32, n_experts + 1); } ggml_backend_buffer_type_t cpu_buft = ggml_backend_cpu_buffer_type(); ggml_backend_buffer_t b_cpu = ggml_backend_alloc_ctx_tensors_from_buft(ctx_cpu.get(), cpu_buft); @@ -351,7 +353,7 @@ bool llama_expert_hotstore::allocate( // can find its per-device GPU hot tensors and per-device LUTs. for (const auto & e : entries) { const auto & L = luts[e.layer_idx]; - llama_expert_tier_register(e.src, e.dst, L.hot_lut, L.mask_lut, L.cold_mask); + llama_expert_tier_register(e.src, e.dst, L.hot_lut, L.mask_lut, L.cold_mask, L.counts); } return true; @@ -390,30 +392,15 @@ bool llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { const size_t slot = ggml_nbytes(e->src) / (size_t) e->src->ne[2]; const int pidx = llama_expert_preload::index_of(e->src); if (preloaded) { - // deferred fill: the startup batch was NOT written at load. - // copy each slot sequentially from the gguf file, verify, and - // retry until the store is sound before the first token. - for (int p = 0; p < hot_s; p++) { - const int ex = ste[p]; - if (ex < 0) { - continue; - } - const int g = slot_device(slot_start, slot_end, p); - if (g < 0 || pidx < 0) { - continue; - } - const size_t off = (size_t) (p - slot_start[g]) * slot; - std::vector buf(slot); - if (!llama_expert_preload::read_expert(pidx, ex, buf.data(), slot)) { - continue; - } - const uint64_t exp = llama_expert_preload::expected_hash(e->src, ex); - for (int attempt = 0; attempt < 32; attempt++) { - ggml_backend_tensor_set(e->dst[g], buf.data(), off, slot); - std::vector rb(1024); - ggml_backend_tensor_get(e->dst[g], rb.data(), off, 1024); - if (hash_slice_at(rb.data(), slot) == exp) { - break; + // the startup slices were streamed into the store at load + // (write_entry), so the GPU store is already sound; reclaim the + // model's host pages for the startup experts (no-mmap). + const char * src = e->src->data ? (const char *) ggml_get_data(e->src) : nullptr; + if (src) { + for (int p = 0; p < hot_s; p++) { + const int ex = ste[p]; + if (ex >= 0) { + release_pages((void *) (src + (size_t) ex * slot), slot); } } } @@ -533,7 +520,7 @@ bool llama_expert_hotstore::resync_full_mirror(const llama_expert_heatmap & heat } rout[e_out] = 0; } - // new expert: copy from the host, verify, route immediately + // new expert: copy from the host, route immediately (verify dropped) bool ok = true; for (entry * ent : entries_by_layer[il]) { const int pidx = llama_expert_preload::index_of(ent->src); @@ -548,9 +535,6 @@ bool llama_expert_hotstore::resync_full_mirror(const llama_expert_heatmap & heat continue; } ggml_backend_tensor_set(ent->dst[g], src, off, slot); - if (!verify_gpu_copy(ent->dst[g], off, ent->src, e_cold, src, slot)) { - ok = false; - } } if (ok) { ste[p] = e_cold; @@ -588,12 +572,6 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { if (llama_expert_preload::get_force()) { return resync_full_mirror(heatmap); // --ecf: full store mirror every token } - if (full_sync_remaining > 0) { - full_sync_remaining--; - // start-up full sync: swap up to hot_s/4 experts per layer this token, - // the mirror to the top-S spread evenly over 4 tokens (verified swaps) - return resync_full_mirror(heatmap, std::max(1, hot_s / 4)); - } if (getenv("LLAMA_EXPERT_DEBUG")) { fprintf(stderr, "hotstore: resync tok=%lld\n", (long long) heatmap.tokens_total); } @@ -601,6 +579,7 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { // tokens elapsed since the previous sync, used to age dwell counters const int64_t elapsed = heatmap.tokens_total - last_sync_tokens; int changed = 0; + std::vector dirty(n_layers, 0); // layers whose LUTs need rebuilding for (int il = 0; il < n_layers; il++) { auto & ste = slot_to_expert[il]; auto & dc = dwell_count[il]; @@ -614,6 +593,9 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { // then hand the expert to the CPU and free the slot ------------ for (auto it = pout.begin(); it != pout.end();) { if (!it->verified) { + if (getenv("LLAMA_EXPERT_NO_VERIFY")) { + it->verified = true; // safety dropped: trust the staging copy + } else { bool ok = true; for (entry * ent : entries_by_layer[il]) { const int pidx = llama_expert_preload::index_of(ent->src); @@ -630,16 +612,42 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { } if (ok) { it->verified = true; - it->countdown = 1; // CPU output counts on the next token } else if (++it->failures >= 5) { - // anti-stall: the copy never verifies, abort the eviction - // and keep the expert on the GPU; the slot stays occupied + // corruption recovery: the GPU -> staging copy kept failing, + // so re-read the expert straight from the gguf file into the + // CPU slice (ground truth); only then route it cold + bool recovered = true; + for (entry * ent : entries_by_layer[il]) { + const int pidx = llama_expert_preload::index_of(ent->src); + if (pidx < 0) { + continue; // mmap: data stays in the file + } + const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; + std::vector buf(slot); + if (!llama_expert_preload::read_expert(pidx, it->expert, buf.data(), slot)) { + recovered = false; + continue; + } + if (llama_expert_preload::expected_hash(ent->src, it->expert) != hash_slice_at(buf.data(), slot)) { + recovered = false; + } + llama_expert_preload::set_cpu_slice(pidx, it->expert, buf.data()); + } + if (recovered) { + rout[it->expert] = 0; + ste[it->p] = -1; + dirty[il] = 1; + changed++; + it = pout.erase(it); + continue; + } if (getenv("LLAMA_EXPERT_DEBUG")) { fprintf(stderr, "hotstore: move-out ABORT expert %d after %d fails\n", it->expert, it->failures); } it = pout.erase(it); continue; } + } } if (it->verified && --it->countdown <= 0) { // hand the expert to the CPU and free the slot @@ -653,6 +661,7 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { } rout[it->expert] = 0; // the CPU output counts now ste[it->p] = -1; // the GPU slot is freed + dirty[il] = 1; changed++; it = pout.erase(it); } else { @@ -667,6 +676,11 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { ++it; continue; } + if (getenv("LLAMA_EXPERT_NO_VERIFY")) { + it->verified = true; // safety dropped: trust the GPU copy + ++it; + continue; + } const int g = slot_device(slot_start, slot_end, it->p); bool ok = g >= 0; if (g >= 0) { @@ -688,12 +702,33 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { it->countdown = 1; // route to the GPU on the next token ++it; } else if (++it->failures >= 5) { - // anti-stall: abort the move-in and free the slot again - if (getenv("LLAMA_EXPERT_DEBUG")) { - fprintf(stderr, "hotstore: move-in ABORT expert %d after %d fails\n", it->expert, it->failures); + // corruption recovery: the CPU slice kept failing to verify, so + // re-read the expert straight from the gguf file (ground truth) + // and re-copy it; keep the move-in only if the disk copy verifies + bool recovered = true; + const int g2 = it->p >= 0 ? slot_device(slot_start, slot_end, it->p) : -1; + for (entry * ent : entries_by_layer[il]) { + const int pidx = llama_expert_preload::index_of(ent->src); + const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; + std::vector buf(slot); + if (pidx < 0 || g2 < 0 || !llama_expert_preload::read_expert(pidx, it->expert, buf.data(), slot)) { + recovered = false; + continue; + } + const size_t off = (size_t) (it->p - slot_start[g2]) * slot; + ggml_backend_tensor_set(ent->dst[g2], buf.data(), off, slot); + if (!verify_gpu_copy(ent->dst[g2], off, ent->src, it->expert, buf.data(), slot)) { + recovered = false; + } + } + if (recovered) { + it->verified = true; + it->countdown = 1; // route to the GPU on the next token + ++it; + } else { + ste[it->p] = -1; + it = pin.erase(it); } - ste[it->p] = -1; - it = pin.erase(it); } else { ++it; } @@ -707,6 +742,7 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { llama_expert_preload::free_cpu_slice(pidx, it->expert); } } + dirty[il] = 1; changed++; it = pin.erase(it); } else { @@ -732,6 +768,13 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { // dwelled. gated on the eviction queue capacity. int evict_candidate = -1; if (!llama_expert_preload::get_no_evict() && !getenv("LLAMA_EXPERT_NO_EVICT") && (int) pout.size() < max_concurrent_moves) { + // never evict an expert still in the top-S: a swap must move a + // genuinely cold expert out, not shuffle two GPU-bound experts + const std::vector top = heatmap.get_top_s(il, hot_s); + std::vector in_top(n_experts, 0); + for (int te : top) { + in_top[te] = 1; + } std::vector routed; for (int e = 0; e < n_experts; e++) { if (rout[e]) { @@ -742,6 +785,9 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { return heatmap.get_score(il, a) < heatmap.get_score(il, b); }); for (int e : routed) { + if (in_top[e]) { + break; // monotonic: warmer residents are in the top-S too + } int p = -1; for (int pp = 0; pp < hot_s; pp++) { if (ste[pp] == e) { @@ -774,6 +820,7 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { ggml_backend_tensor_get(ent->dst[dg], &stg[stg_off + staging_slot_off(entries_by_layer[il], ent)], off, slot); } pout.push_back({evict_candidate, p, false, 0, 0}); + dirty[il] = 1; changed++; // the LUTs do not change yet, but the transition started } } @@ -817,6 +864,7 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { ste[free_slot] = e_cold; pin.push_back({e_cold, free_slot, false, 0, 0}); dc[free_slot] = -elapsed; + dirty[il] = 1; changed++; break; // one move-in per layer per token } @@ -832,7 +880,7 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { last_sync_tokens = heatmap.tokens_total; if (changed > 0) { - update_luts(); + update_luts(dirty); if (getenv("LLAMA_EXPERT_DEBUG")) { fprintf(stderr, "=== Expert hot store: re-sync changed %d slots ===\n", changed); } @@ -842,15 +890,20 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { bool llama_expert_hotstore::maybe_resync(const llama_expert_heatmap & heatmap, bool multi_slot) { // n_tokens>1 (multi-slot) freezes the hot store: no swapping during the batch - if (multi_slot || sync_period <= 0 || heatmap.tokens_total <= 0) { + if (multi_slot || heatmap.tokens_total <= 0) { return false; } - if (heatmap.tokens_total / sync_period > last_sync_tokens / sync_period) { - if (!full_sync_done && heatmap.generated_tokens_count >= 4) { - // after the 3-token heat boost, mirror the store to the top-S over - // the next 4 tokens (budget hot_s/4 per layer per token) - full_sync_done = true; - full_sync_remaining = 4; + // continuous adaptive cadence: the sync period grows with the hit rate + // relative to the target. floor of 10 tokens (never resync more often), + // growing up to 32 as the hit rate climbs far above the target. no hard + // disable thresholds - the period just keeps growing. + float ratio = hit_rate_valid ? hit_rate / target_hit_rate() : 0.0f; + const int eff_period = std::max(10, std::min(32, 1 + (int) (4.0f * ratio))); + if (heatmap.tokens_total / eff_period > last_sync_tokens / eff_period) { + if (getenv("LLAMA_EXPERT_FULL_SYNC")) { + // test: mirror the whole store to the top-S on each sync instead of + // the incremental handshake (pair with --expert-sync-period N) + return resync_full_mirror(heatmap, std::max(1, hot_s)); } return resync_top_s(heatmap); } @@ -870,7 +923,7 @@ int llama_expert_hotstore::slot_of(int layer_idx, int expert_id) const { return -1; } -void llama_expert_hotstore::update_luts() { +void llama_expert_hotstore::update_luts(const std::vector & dirty) { if (hot_s <= 0 || luts.empty() || buf_dev.empty()) { return; } @@ -887,6 +940,9 @@ void llama_expert_hotstore::update_luts() { std::vector cold_mask_h(n_experts); for (int il = 0; il < n_layers; il++) { + if (!dirty.empty() && !dirty[il]) { + continue; // this layer's store did not change; LUT already current + } const auto & ste = slot_to_expert[il]; const auto & rout = gpu_routed[il]; @@ -966,6 +1022,55 @@ void llama_expert_hotstore::log_hit_rate(const std::vectordata) { + memset(c->data, 0, (size_t) (n_experts + 1) * sizeof(int32_t)); + } + } +} + +void llama_expert_hotstore::read_counts(llama_expert_heatmap & heatmap, int n_tokens) { + if (luts.size() != (size_t) n_layers) { + return; + } + std::vector per_layer((size_t) n_layers, nullptr); + int64_t total = 0, hot = 0; + for (int il = 0; il < n_layers; il++) { + ggml_tensor * c = luts[il].counts; + const int32_t * cnt = c && c->data ? (const int32_t *) c->data : nullptr; + per_layer[il] = cnt; + if (!cnt) { + continue; + } + const auto & rout = gpu_routed[il]; + for (int e = 0; e < n_experts; e++) { + if (cnt[e] > 0) { + total += cnt[e]; + if (rout[e]) { + hot += cnt[e]; + } + } + } + } + if (total > 0) { + const float inst = (float) hot / (float) total; + hit_rate = hit_rate_valid ? 0.9f * hit_rate + 0.1f * inst : inst; + hit_rate_valid = true; + } + heatmap.update_counts(per_layer, n_tokens); +} + +float llama_expert_hotstore::target_hit_rate() const { + if (n_experts <= 0) { + return 0.5f; + } + const float frac = (float) hot_s / (float) n_experts; + const float t = 0.8f * std::pow(frac, 0.6f); + return std::max(0.2f, std::min(0.9f, t)); +} + void llama_expert_hotstore::log() const { fprintf(stderr, "=== Expert hotstore sizing (S=%d) ===\n", hot_s); const bool debug = getenv("LLAMA_EXPERT_DEBUG") != nullptr; diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index 70702b7f6a5..f9ae823f6c0 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -47,6 +47,7 @@ struct llama_expert_hotstore { std::vector hot_lut; // per-device i32[n_experts] std::vector mask_lut; // per-device f32[local_slots+1], 0 at sentinel ggml_tensor * cold_mask = nullptr; // i32[n_experts] + ggml_tensor * counts = nullptr; // i32[n_experts+1], tallied by the cold op }; std::vector luts; // size n_layers @@ -73,6 +74,15 @@ struct llama_expert_hotstore { // tokens_total at the last sync (fill or re-sync) for boundary-cross check int64_t last_sync_tokens = 0; + // adaptive cadence: smoothed hit rate + the target the store must reach + // before the resync slows. target = 0.8 * (hot_s/n_experts)^0.6, clamped to + // [0.2, 0.9]: small models (store ~ full) aim ~80%, 1/5-fit models ~30%. + // hit_rate >= 0.95 disables the resync entirely. + float hit_rate = 0.0f; + bool hit_rate_valid = false; + + float target_hit_rate() const; + // start-up full sync: after the 3-token heat boost, mirror the store to the // top-S over the next `full_sync_remaining` tokens (budget hot_s/4 per token) bool full_sync_done = false; @@ -156,14 +166,21 @@ llama_expert_hotstore(const llama_model * model, int n_layers, // returns the GPU slot index holding expert_id in layer il, or -1 if none int slot_of(int layer_idx, int expert_id) const; + // zero the cold-op per-expert counts (call before the graph compute) + void reset_counts(); + + // feed the cold-op counts into the heatmap (host memory, no D2H readback). + // call after the graph compute; n_tokens advances the heatmap clock. + void read_counts(llama_expert_heatmap & heatmap, int n_tokens); + // diagnostic: count how many router-selected expert ids hit a hot slot. // reads the selected_experts tensors (call after synchronize). void log_hit_rate(const std::vector> & moe_sel); // rebuild hot_lut/cold_mask from slot_to_expert for every layer // and copy them into the tensors. called from copy_top_s (initial - // fill) and resync_top_s (swaps). - void update_luts(); + // fill) and resync_top_s (swaps). empty dirty = all layers. + void update_luts(const std::vector & dirty = {}); void log() const; }; diff --git a/src/llama-expert-preload.cpp b/src/llama-expert-preload.cpp index 5b07b494abb..c6272a40c86 100644 --- a/src/llama-expert-preload.cpp +++ b/src/llama-expert-preload.cpp @@ -186,9 +186,24 @@ bool write_entry(size_t idx, const uint8_t * data, size_t nbytes) { if (nbytes < (size_t) e.startup * e.plane_bytes) { return false; } - // the startup store copy is deferred to the first token (copy_top_s fills - // it from the file, sequentially, each slot hash-verified). here we only - // record the ground-truth hashes for the startup experts. + // stream the startup slices into the store buffer at load (fast startup, + // no token-1 file reads). the store adopts this buffer and re-allocates + // its dst tensors at the same gpu_offset; the scratch tensor below dies + // with g_ctx at take_buffer(). the cold op's slice callback ignores the + // startup experts (they are GPU-counted), so no host copy is needed. + if (g_gpu_buf && g_ctx) { + ggml_tensor * t = ggml_new_tensor_1d(g_ctx, GGML_TYPE_I8, e.plane_bytes); + uint8_t * base = (uint8_t *) ggml_backend_buffer_get_base(g_gpu_buf); + for (int ex = 0; ex < e.startup; ex++) { + uint8_t * dst = base + e.gpu_offset + (size_t) ex * e.plane_bytes; + if (ex == 0) { + ggml_backend_tensor_alloc(g_gpu_buf, t, dst); + } else { + t->data = dst; // manual view into the adopted store buffer + } + ggml_backend_tensor_set(t, data + (size_t) ex * e.plane_bytes, 0, e.plane_bytes); + } + } const size_t chunk = e.plane_bytes < 1024 ? e.plane_bytes : 1024; for (int ex = 0; ex < e.startup; ex++) { g_hashes[idx][ex] = fnv1a(data + (size_t) ex * e.plane_bytes, chunk); diff --git a/src/llama-expert-tier.cpp b/src/llama-expert-tier.cpp index 1ad9de3b893..0a0ee60dd1e 100644 --- a/src/llama-expert-tier.cpp +++ b/src/llama-expert-tier.cpp @@ -9,19 +9,29 @@ namespace { std::vector hot_lut; // per-device LUTs std::vector mask_lut; // per-device sentinel masks ggml_tensor * cold_mask; + ggml_tensor * counts; // i32[n_experts+1], tallied by the cold op }; std::mutex g_mtx; std::unordered_map g_table; + + // fused cold path: while a layer's experts are being built, the tier build + // returns hot-only results; the fused op (built by end_fused) covers cold. + bool g_fused_active = false; + + // fused path only kicks in for batches up to this many tokens (gated on + // ids->ne[1]); larger batches fall back to the per-op cold path. + static int g_tmax = 16; } void llama_expert_tier_register(ggml_tensor * src, const std::vector & dst_hot, const std::vector & hot_lut, const std::vector & mask_lut, - ggml_tensor * cold_mask) { + ggml_tensor * cold_mask, + ggml_tensor * counts) { std::lock_guard lk(g_mtx); - g_table[src] = {dst_hot, hot_lut, mask_lut, cold_mask}; + g_table[src] = {dst_hot, hot_lut, mask_lut, cold_mask, counts}; } void llama_expert_tier_clear() { @@ -81,21 +91,72 @@ ggml_tensor * llama_expert_tier_build(ggml_context * ctx, for (size_t g = 0; g < ent.dst_hot.size(); g++) { ggml_tensor * ids_hot = remap_ids(ctx, ent.hot_lut[g], ids, n_experts, n_expert_used, n_tokens); ggml_tensor * h = ggml_mul_mat_id(ctx, ent.dst_hot[g], cur, ids_hot); - // zero the rows routed to the sentinel plane: index the mask LUT (0 - // at the sentinel) by ids_hot, repeat over the hidden dim, multiply. - // flatten ids for get_rows (works for any n_tokens), then reshape. - ggml_tensor * flat = ggml_reshape_1d(ctx, ggml_cont(ctx, ids_hot), n_expert_used * n_tokens); - ggml_tensor * m = ggml_get_rows(ctx, ent.mask_lut[g], flat); - m = ggml_reshape_3d(ctx, m, 1, n_expert_used, n_tokens); - h = ggml_mul(ctx, h, ggml_repeat(ctx, m, h)); hot = hot ? ggml_add(ctx, hot, h) : h; } + // fused cold path active for this layer: the CPU cold op is deferred to + // end_fused, so return the hot contribution only + if (g_fused_active) { + (void)w_s; + return hot; + } + // cold: dedicated CPU op that computes only the cold-selected experts, - // skipping hot ones via the integer zero-check on cold_mask. - ggml_tensor * cold = ggml_mul_mat_id_cold(ctx, w, cur, ids, ent.cold_mask, nullptr, nullptr); + // skipping hot ones via the integer zero-check on cold_mask. the same op + // tallies the selected ids into ent.counts (host memory) for the heatmap. + ggml_tensor * cold = ggml_mul_mat_id_cold(ctx, w, cur, ids, ent.cold_mask, ent.counts, nullptr); (void)w_s; // per-expert quant scale is intentionally discarded on the tiered path return ggml_add(ctx, hot, cold); +} + +bool llama_expert_tier_begin_fused(ggml_tensor * gate_w, + ggml_tensor * up_w, + ggml_tensor * down_w, + ggml_tensor * ids) { + g_fused_active = false; + if (!gate_w || !up_w || !down_w) { + return false; + } + if (ids->ne[1] > (int64_t) g_tmax) { + return false; // batch too large for the fused path + } + const int n_experts = (int) down_w->ne[2]; + std::lock_guard lk(g_mtx); + if (g_table.find(gate_w) == g_table.end() || + g_table.find(up_w) == g_table.end() || + g_table.find(down_w) == g_table.end()) { + return false; // some tensors of this layer are not tiered + } + if (up_w != gate_w && (int) up_w->ne[2] != n_experts) { + return false; + } + g_fused_active = true; + return true; +} + +ggml_tensor * llama_expert_tier_end_fused(ggml_context * ctx, + ggml_tensor * gate_w, + ggml_tensor * up_w, + ggml_tensor * down_w, + ggml_tensor * x, + ggml_tensor * ids, + int32_t act) { + if (!g_fused_active) { + return nullptr; + } + g_fused_active = false; + + tier_entry ent; + { + std::lock_guard lk(g_mtx); + auto it = g_table.find(down_w); + if (it == g_table.end()) { + return nullptr; + } + ent = it->second; + } + + return ggml_moe_cold(ctx, gate_w, up_w, down_w, x, ids, ent.cold_mask, ent.counts, act); } \ No newline at end of file diff --git a/src/llama-expert-tier.h b/src/llama-expert-tier.h index 1c7ac2896f2..ec0161b0d7a 100644 --- a/src/llama-expert-tier.h +++ b/src/llama-expert-tier.h @@ -33,7 +33,8 @@ void llama_expert_tier_register(ggml_tensor * src, const std::vector & dst_hot, const std::vector & hot_lut, const std::vector & mask_lut, - ggml_tensor * cold_mask); + ggml_tensor * cold_mask, + ggml_tensor * counts); // drop the entire table (called by hotstore destructor) void llama_expert_tier_clear(); @@ -54,4 +55,23 @@ ggml_tensor * llama_expert_tier_build(ggml_context * ctx, ggml_tensor * w, ggml_tensor * cur, ggml_tensor * ids, - ggml_tensor * w_s); \ No newline at end of file + ggml_tensor * w_s); + +// fused cold path (GGML_OP_MOE_COLD), one call pair per MoE layer: +// begin_fused is called before the layer's expert matmuls and makes +// llama_expert_tier_build return hot-only results; end_fused (after the down +// matmul) returns the cold contribution tensor to add to the down result, or +// nullptr when the fused path is not active. gate/up/down must all be +// registered. act = 0 (silu, separate gate/up) or 1 (gelu, fused gate_up). +bool llama_expert_tier_begin_fused(ggml_tensor * gate_w, + ggml_tensor * up_w, + ggml_tensor * down_w, + ggml_tensor * ids); + +ggml_tensor * llama_expert_tier_end_fused(ggml_context * ctx, + ggml_tensor * gate_w, + ggml_tensor * up_w, + ggml_tensor * down_w, + ggml_tensor * x, + ggml_tensor * ids, + int32_t act); \ No newline at end of file diff --git a/src/llama-graph.cpp b/src/llama-graph.cpp index 89074a79f04..e8feea3ea3d 100644 --- a/src/llama-graph.cpp +++ b/src/llama-graph.cpp @@ -2097,6 +2097,25 @@ ggml_tensor * llm_graph_context::build_moe_ffn( cb(cur, "ffn_moe_weighted", il); } + // expert tiering: fused cold path. when active, build_lora_mm_id returns + // hot-only results and the fused op (built after the down matmul so the + // CPU cold work overlaps the GPU hot work) covers the cold experts. + ggml_tensor * gw = gate_exps ? gate_exps : gate_up_exps; + ggml_tensor * uw = up_exps ? up_exps : gate_up_exps; + constexpr float clamp_eps = 1e-6f; + const bool swiglu_clamped = (type_op == LLM_FFN_SILU) && gate_exps && il >= 0 && + hparams.swiglu_clamp_exp[il] > clamp_eps; + const bool cold_ok = !weight_before_ffn && gw && uw && down_exps && + !up_exps_b && !gate_exps_b && !down_exps_b && !gate_up_exps_b && + !up_exps_s && !gate_exps_s && + (type_op == LLM_FFN_SILU || type_op == LLM_FFN_GELU) && + arch != LLM_ARCH_STEP35 && + loras->empty() && !swiglu_clamped; + const int32_t act = type_op == LLM_FFN_GELU ? 1 : 0; + const bool moe_cold = cold_ok && + llama_expert_tier_begin_fused(gw, uw, down_exps, selected_experts); + ggml_tensor * x_in = cur; + ggml_tensor * up = nullptr; ggml_tensor * experts = nullptr; @@ -2230,6 +2249,20 @@ ggml_tensor * llm_graph_context::build_moe_ffn( cb(experts, "ffn_moe_down_scaled", il); } + if (moe_cold) { + ggml_tensor * cold = llama_expert_tier_end_fused(ctx0, gw, uw, down_exps, x_in, selected_experts, act); + if (cold) { + if (down_exps_s) { + ggml_tensor * s = ggml_reshape_3d(ctx0, down_exps_s, 1, down_exps_s->ne[0], 1); + s = ggml_repeat_4d(ctx0, s, 1, down_exps_s->ne[0], cold->ne[2], 1); + s = ggml_get_rows(ctx0, s, selected_experts); + cold = ggml_mul(ctx0, cold, s); + } + experts = ggml_add(ctx0, experts, cold); + cb(experts, "ffn_moe_down_cold", il); + } + } + if (down_exps_b) { experts = ggml_add_id(ctx0, experts, down_exps_b, selected_experts); cb(experts, "ffn_moe_down_biased", il); From 8e3e8e1cb3cb560be51ec6f59c478624bb291a77 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 9 Aug 2026 10:36:35 +0300 Subject: [PATCH 40/61] expert tier: zero the store buffer at preload --- src/llama-expert-preload.cpp | 3 +++ 1 file changed, 3 insertions(+) diff --git a/src/llama-expert-preload.cpp b/src/llama-expert-preload.cpp index c6272a40c86..d9a48218162 100644 --- a/src/llama-expert-preload.cpp +++ b/src/llama-expert-preload.cpp @@ -148,6 +148,9 @@ void begin(struct ggml_backend_buffer_type * buft, size_t gpu_bytes, size_t cpu_ return; // load_all_data can run more than once (fit estimate + real load) } g_gpu_buf = ggml_backend_buft_alloc_buffer(buft, gpu_bytes); + // zero the whole store up front: the sentinel plane and any unwritten gaps + // would otherwise carry per-launch garbage into the graph output (Vulkan) + ggml_backend_buffer_clear(g_gpu_buf, 0); g_ctx = ggml_init({ ggml_tensor_overhead() * (max_entries + 8), nullptr, true }); g_cpu_buf = (uint8_t *) malloc(cpu_bytes); g_cpu_size = cpu_bytes; From d29493919b4e8b41f4d437e5185f1854f21e764e Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 9 Aug 2026 10:51:40 +0300 Subject: [PATCH 41/61] expert tier: drop dead heatmap paths and debug hash hook --- ggml/include/ggml-cpu.h | 4 -- ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c | 27 -------- src/llama-context.cpp | 17 ++--- src/llama-expert-heatmap.cpp | 65 -------------------- src/llama-expert-heatmap.h | 4 -- src/llama-expert-preload.cpp | 4 -- 6 files changed, 4 insertions(+), 117 deletions(-) diff --git a/ggml/include/ggml-cpu.h b/ggml/include/ggml-cpu.h index 4a1891fd3d4..c9f04834b2d 100644 --- a/ggml/include/ggml-cpu.h +++ b/ggml/include/ggml-cpu.h @@ -154,10 +154,6 @@ extern "C" { typedef const uint8_t * (*ggml_mmid_cold_slice_fn)(const struct ggml_tensor * src0, int expert); GGML_BACKEND_API void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn); - // optional ground-truth hash provider for the cold op debug log - typedef uint64_t (*ggml_mmid_cold_hash_fn)(const struct ggml_tensor * src0, int expert); - GGML_BACKEND_API void ggml_mmid_cold_set_hash_fn(ggml_mmid_cold_hash_fn fn); - #ifdef __cplusplus } #endif diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c index 79c9dc75e92..d01f7a94d54 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c @@ -20,7 +20,6 @@ #include static ggml_mmid_cold_slice_fn g_slice_fn = NULL; -static ggml_mmid_cold_hash_fn g_hash_fn = NULL; void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn) { g_slice_fn = fn; @@ -29,10 +28,6 @@ void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn) { const uint8_t * ggml_mmid_cold_get_slice(const struct ggml_tensor * src0, int expert) { return g_slice_fn ? g_slice_fn(src0, expert) : NULL; } - -void ggml_mmid_cold_set_hash_fn(ggml_mmid_cold_hash_fn fn) { - g_hash_fn = fn; -} #include #include @@ -190,30 +185,8 @@ void ggml_compute_forward_mul_mat_id_cold( const char * src0_cur; if (g_slice_fn) { const uint8_t * s = g_slice_fn(src0, (int) cur_a); - if (s && getenv("LLAMA_EXPERT_DEBUG")) { - static int once = 0; - if (!once) { - once = 1; - uint64_t h = 0xcbf29ce484222325ULL; - for (int i = 0; i < 1024; i++) { - h ^= s[i]; - h *= 0x100000001b3ULL; - } - const uint64_t exp = g_hash_fn ? g_hash_fn(src0, (int) cur_a) : 0; - fprintf(stderr, "coldop: expert %d tensor %s fnv=%016" PRIx64 " expected=%016" PRIx64 " %s\n", - (int) cur_a, src0->name, h, exp, - h == exp ? "MATCH" : "MISMATCH"); - } - } src0_cur = s ? (const char *) s : (const char *) src0->data + cur_a * nb02; } else { - if (getenv("LLAMA_EXPERT_DEBUG")) { - static int once = 0; - if (!once) { - once = 1; - fprintf(stderr, "coldop: HOOK NULL, reading tensor data (ghost)\n"); - } - } src0_cur = (const char *) src0->data + cur_a * nb02; } const void * wdata = (src1->type == vec_dot_type) ? src1->data : params->wdata; diff --git a/src/llama-context.cpp b/src/llama-context.cpp index ce86c5276f1..a3581482ddd 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -1442,19 +1442,10 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll if (expert_heatmap && expert_hotstore && expert_hotstore->is_filled) { expert_hotstore->read_counts(*expert_heatmap, ubatch.n_tokens); } - if (expert_heatmap && expert_hotstore) { - if (!expert_hotstore->is_filled) { - // fill happens pre-graph on the first ubatch (see above) - } else { - expert_hotstore->maybe_resync(*expert_heatmap, ubatch.n_tokens > 1); - // the post-resync sync is removed (default): the resync's store - // writes on the default stream race the graph's stream - if (getenv("LLAMA_EXPERT_SYNC_RESYNC")) { - synchronize(); - } - if (ubatch.n_tokens == 1 && getenv("LLAMA_EXPERT_HITRATE")) { - expert_hotstore->log_hit_rate(res->moe_sel_experts); - } + if (expert_heatmap && expert_hotstore && expert_hotstore->is_filled) { + expert_hotstore->maybe_resync(*expert_heatmap, ubatch.n_tokens > 1); + if (ubatch.n_tokens == 1 && getenv("LLAMA_EXPERT_HITRATE")) { + expert_hotstore->log_hit_rate(res->moe_sel_experts); } } diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index bea10675b16..79eac14efcd 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -1,9 +1,6 @@ #include "llama-expert-heatmap.h" #include "llama-impl.h" -#include "ggml.h" -#include "ggml-backend.h" - #include #include #include @@ -22,18 +19,6 @@ llama_expert_heatmap::llama_expert_heatmap( heat(n_layers * n_experts, 0.0f) { } -void llama_expert_heatmap::update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens, float multiplier) { - float * layer_heat = heat.data() + layer_idx * n_experts; - - for (int t = 0; t < n_tokens; t++) { - for (int e = 0; e < n_expert_used; e++) { - int32_t id = expert_ids[t * n_expert_used + e]; - if (id >= 0 && id < n_experts) { - layer_heat[id] += 1.0f * multiplier; - } - } - } -} void llama_expert_heatmap::update_counts(const std::vector & per_layer, int n_tokens) { // batched decay: apply decay_rate^2 every two updates instead of // decay_rate every update (identical long-run weighting, half the work) @@ -67,56 +52,6 @@ void llama_expert_heatmap::update_counts(const std::vector & pe } } -void llama_expert_heatmap::update_from_graph(const std::vector> & moe_sel_experts) { - if (moe_sel_experts.empty()) { - return; - } - - // batch the decay: apply decay_rate^2 every two updates instead of - // decay_rate every update (identical long-run weighting, half the work) - ++update_counter; - if (update_counter % 2 == 0) { - const float rate = decay_rate * decay_rate; - for (int i = 0; i < n_layers * n_experts; i++) { - heat[i] *= rate; - } - } - - int64_t n_tokens = 0; - float multiplier = 1.0f; - // weight the first few decode tokens 15x so the initial hot store fill is - // driven by generation routing rather than the prompt-processing ubatches - if (moe_sel_experts.front().second->ne[1] == 1) { - generated_tokens_count++; - if (generated_tokens_count <= 3) { - multiplier = 15.0f; - } - } - for (const auto & [il, tensor] : moe_sel_experts) { - n_tokens = tensor->ne[1]; - - if (!tensor->data) { - continue; - } - - std::vector expert_ids(tensor->ne[0] * n_tokens); - ggml_backend_tensor_get(tensor, expert_ids.data(), 0, expert_ids.size() * sizeof(int32_t)); - - update(il, expert_ids.data(), tensor->ne[0], n_tokens, multiplier); - } - - tokens_total += n_tokens; - if (log_period > 0 && tokens_total / log_period > (tokens_total - n_tokens) / log_period) { - log(); - } -} - -void llama_expert_heatmap::decay_all() { - for (int i = 0; i < n_layers * n_experts; i++) { - heat[i] *= decay_rate; - } -} - void llama_expert_heatmap::log() const { LLAMA_LOG("=== Expert heatmap (tokens %" PRId64 ") ===\n", tokens_total); diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index d7ced8e402c..cefb967cb46 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -2,7 +2,6 @@ #include #include -#include struct ggml_tensor; @@ -22,12 +21,9 @@ struct llama_expert_heatmap { int log_period = 100, int hot_s = 0); - void update(int layer_idx, const int32_t * expert_ids, int n_expert_used, int n_tokens, float multiplier = 1.0f); - void update_from_graph(const std::vector> & moe_sel_experts); // cold-op counts path: per-layer tallies of the selected experts (host // memory). advances tokens_total; the first-3-token boost lives in get_score. void update_counts(const std::vector & per_layer, int n_tokens); - void decay_all(); void log() const; float get_score(int layer_idx, int expert_id) const; diff --git a/src/llama-expert-preload.cpp b/src/llama-expert-preload.cpp index d9a48218162..a9911ef60c6 100644 --- a/src/llama-expert-preload.cpp +++ b/src/llama-expert-preload.cpp @@ -250,10 +250,6 @@ bool write_cold(size_t idx, const uint8_t * data, size_t nbytes) { e.src->name, g_cpu_buf[dst], g_cpu_buf[dst+1], g_cpu_buf[dst+2], g_cpu_buf[dst+3]); } ggml_mmid_cold_set_slice_fn(preload_slice_cb); - ggml_mmid_cold_set_hash_fn( - [](const struct ggml_tensor * src0, int expert) -> uint64_t { - return expected_hash(src0, expert); - }); return true; } From ab875d2bcf64581a40e268506d1c0c28705ba0ee Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 9 Aug 2026 11:54:37 +0300 Subject: [PATCH 42/61] common: warn when -ehs -1 cannot autofit expert slots --- common/common.cpp | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/common/common.cpp b/common/common.cpp index b53e1b56717..4bcba8e6e59 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1261,8 +1261,17 @@ common_init_result::common_init_result(common_params & params, bool model_only) break; } } + } else { + LOG_WRN("%s: --expert-hot-s -1 autofit found no free VRAM for expert slots; expert cache is OFF\n", + __func__); } } + } else if (params.expert_hot_s == -1) { + // autofit only runs inside --fit; without it -1 is meaningless + params.expert_hot_s = 0; + cparams.expert_hot_s = params.expert_hot_s; + LOG_WRN("%s: --expert-hot-s -1 requires --fit (disabled by -fit off or explicit -ngl/-ncmoe); expert cache is OFF\n", + __func__); } llama_model * model = llama_model_load_from_file(params.model.path.c_str(), mparams); From 1550f1156e41f0de1b94782741a15498e271b335 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 9 Aug 2026 12:27:03 +0300 Subject: [PATCH 43/61] expert tier: rework mmap page hints into a pin manager --- src/CMakeLists.txt | 1 + src/llama-context.cpp | 33 +++++- src/llama-expert-heatmap.cpp | 26 +++++ src/llama-expert-heatmap.h | 3 + src/llama-expert-hotstore.cpp | 43 +------- src/llama-expert-hotstore.h | 9 +- src/llama-expert-pin.cpp | 184 ++++++++++++++++++++++++++++++++++ src/llama-expert-pin.h | 34 +++++++ 8 files changed, 290 insertions(+), 43 deletions(-) create mode 100644 src/llama-expert-pin.cpp create mode 100644 src/llama-expert-pin.h diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt index 40a6359f80b..af8abf5a8f4 100644 --- a/src/CMakeLists.txt +++ b/src/CMakeLists.txt @@ -19,6 +19,7 @@ add_library(llama llama-cparams.cpp llama-expert-heatmap.cpp llama-expert-hotstore.cpp + llama-expert-pin.cpp llama-expert-preload.cpp llama-expert-tier.cpp llama-grammar.cpp diff --git a/src/llama-context.cpp b/src/llama-context.cpp index a3581482ddd..aa7b7b0dc9f 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -1,5 +1,6 @@ #include "llama-context.h" +#include "llama-expert-pin.h" #include "llama-expert-preload.h" #include "ggml.h" @@ -464,8 +465,11 @@ llama_context::llama_context( } } + // heatmap exists for the tier, the heat log, or standalone pinning + // (LLAMA_EXPERT_PIN without the hot store) if (hparams.n_expert > 0 && !cparams.warmup && - (params.expert_heat_log_period != 0 || params.expert_hot_s != 0)) { + (params.expert_heat_log_period != 0 || params.expert_hot_s != 0 || + llama_expert_pin::active())) { expert_heatmap = std::make_unique( hparams.n_layer(), hparams.n_expert, params.expert_heat_decay, @@ -1449,6 +1453,33 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll } } + // standalone pin mode (no hot store): feed the heatmap from the graph + // readback and warm the top cold experts on mmap + if (expert_heatmap && !expert_hotstore && llama_expert_pin::active()) { + synchronize(); + for (const auto & [il, tensor] : res->moe_sel_experts) { + if (!tensor || !tensor->data) { + continue; + } + const int n_ids = (int) tensor->ne[0]; + const int n_tokens = (int) tensor->ne[1]; + std::vector ids((size_t) n_ids * n_tokens); + ggml_backend_tensor_get(tensor, ids.data(), 0, ids.size() * sizeof(int32_t)); + expert_heatmap->update_ids(il, ids.data(), n_ids, n_tokens); + } + } + + // mmap page hints for the expert tier (hot store active: GPU-aware sets; + // standalone: everything is cold, warm the top fraction) + if (expert_heatmap && llama_expert_pin::active()) { + llama_expert_hotstore * hs = expert_hotstore.get(); + llama_expert_pin::maybe_run(&model, expert_heatmap.get(), + [](void * ud, int il, int e) -> bool { + return ud != nullptr && static_cast(ud)->is_resident(il, e); + }, + hs); + } + ret = GGML_STATUS_SUCCESS; return res; diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 79eac14efcd..7bf72c854f9 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -52,6 +52,32 @@ void llama_expert_heatmap::update_counts(const std::vector & pe } } +void llama_expert_heatmap::update_ids(int layer_idx, const int32_t * expert_ids, int n_ids, int n_tokens) { + if (layer_idx < 0 || layer_idx >= n_layers || !expert_ids) { + return; + } + ++update_counter; + if (update_counter % 2 == 0) { + const float rate = decay_rate * decay_rate; + for (int i = 0; i < n_layers * n_experts; i++) { + heat[i] *= rate; + } + } + if (n_tokens == 1) { + generated_tokens_count++; + } + float * layer_heat = &heat[layer_idx * n_experts]; + for (int t = 0; t < n_tokens; t++) { + for (int e = 0; e < n_ids; e++) { + const int32_t id = expert_ids[t * n_ids + e]; + if (id >= 0 && id < n_experts) { + layer_heat[id] += 1.0f; + } + } + } + tokens_total += n_tokens; +} + void llama_expert_heatmap::log() const { LLAMA_LOG("=== Expert heatmap (tokens %" PRId64 ") ===\n", tokens_total); diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index cefb967cb46..abe8f9b3071 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -24,6 +24,9 @@ struct llama_expert_heatmap { // cold-op counts path: per-layer tallies of the selected experts (host // memory). advances tokens_total; the first-3-token boost lives in get_score. void update_counts(const std::vector & per_layer, int n_tokens); + + // standalone path (no cold op): per-expert increment from graph readback + void update_ids(int layer_idx, const int32_t * expert_ids, int n_ids, int n_tokens); void log() const; float get_score(int layer_idx, int expert_id) const; diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 6e7aa800bca..5e44000fb30 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -16,35 +16,8 @@ #ifdef _WIN32 #include -#else -#include -#include #endif -// drop the physical pages backing [ptr, ptr+len) that are fully inside the -// range (inward-rounded to page boundaries) so neighbors are never clobbered. -// on mmap'd tensors the pages re-fault from the file; on anonymous memory they -// are discarded (the tier never reads them again while GPU-resident). -static void release_pages(void * ptr, size_t len) { -#ifdef _WIN32 - SYSTEM_INFO si; - GetSystemInfo(&si); - const size_t page = si.dwPageSize; -#else - const long page = sysconf(_SC_PAGESIZE); -#endif - const uintptr_t base = (uintptr_t) ptr; - const uintptr_t start = (base + (uintptr_t) page - 1) & ~((uintptr_t) page - 1); - const uintptr_t end = (base + len) & ~((uintptr_t) page - 1); - if (start < end) { -#ifdef _WIN32 - VirtualFree((LPVOID) start, end - start, MEM_RESET); -#else - madvise((void *) start, end - start, MADV_DONTNEED); -#endif - } -} - // FNV-1a of the first min(n, 1024) bytes - matches the launch hash sampling static uint64_t hash_slice_at(const uint8_t * p, size_t n) { const size_t m = std::min(n, (size_t) 1024); @@ -393,17 +366,7 @@ bool llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { const int pidx = llama_expert_preload::index_of(e->src); if (preloaded) { // the startup slices were streamed into the store at load - // (write_entry), so the GPU store is already sound; reclaim the - // model's host pages for the startup experts (no-mmap). - const char * src = e->src->data ? (const char *) ggml_get_data(e->src) : nullptr; - if (src) { - for (int p = 0; p < hot_s; p++) { - const int ex = ste[p]; - if (ex >= 0) { - release_pages((void *) (src + (size_t) ex * slot), slot); - } - } - } + // (write_entry), so the GPU store is already sound. continue; } const char * src = e->src->data ? (const char *) ggml_get_data(e->src) : nullptr; @@ -420,8 +383,8 @@ bool llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { continue; } ggml_backend_tensor_set(e->dst[g], src + (size_t) ex * slot, (size_t) (p - slot_start[g]) * slot, slot); - // real reclaim: the expert now lives on the GPU, drop its RAM pages - release_pages((void *) (src + (size_t) ex * slot), slot); + // page hints are handled by llama_expert_pin (mmap only); + // DONTNEED here would refault from disk on eviction } } // startup batch is trusted on the GPU (filled from the file, hash-checked); diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index f9ae823f6c0..fd0836226ac 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -64,11 +64,16 @@ struct llama_expert_hotstore { ggml_backend_buffer_ptr buf_cpu; // true once the first copy of the top-S experts landed (once per session) - bool is_filled = false; - // true when the store buffer was streamed by the loader (startup batch + bool is_filled = false; // true when the store buffer was streamed by the loader (startup batch // already resident), so the fill does not copy again bool preloaded = false; + // true when expert e of layer il is GPU-counted (output comes from the store) + bool is_resident(int il, int e) const { + return il >= 0 && il < (int) gpu_routed.size() && + e >= 0 && e < (int) gpu_routed[il].size() && gpu_routed[il][e] != 0; + } + // re-sync cadence in tokens; 0 disables periodic re-sync int sync_period = 0; // tokens_total at the last sync (fill or re-sync) for boundary-cross check diff --git a/src/llama-expert-pin.cpp b/src/llama-expert-pin.cpp new file mode 100644 index 00000000000..26f24a079bf --- /dev/null +++ b/src/llama-expert-pin.cpp @@ -0,0 +1,184 @@ +#include "llama-expert-pin.h" + +#include "llama-expert-heatmap.h" +#include "llama-impl.h" +#include "llama-model.h" + +#include "ggml.h" +#include "ggml-backend.h" + +#include +#include +#include +#include +#include + +#if !defined(_WIN32) +#include +#include +#else +#include +#endif + +namespace llama_expert_pin { + +static void madvise_range(const void * p, size_t len, bool keep) { +#if !defined(_WIN32) + static const long page = sysconf(_SC_PAGESIZE); + const uintptr_t a = (uintptr_t) p & ~(uintptr_t) (page - 1); + const uintptr_t b = ((uintptr_t) p + len + page - 1) & ~(uintptr_t) (page - 1); + if (b > a) { + madvise((void *) a, b - a, keep ? MADV_WILLNEED : MADV_DONTNEED); + } +#else + (void) p; (void) len; (void) keep; +#endif +} + +// only hint file-backed (mmap) host tensors; anonymous buffers must never be +// DONTNEED'd (would zero them). a host tensor without a data pointer has no +// pages to hint. +static bool hintable(const ggml_tensor * w) { + if (!w || !w->data) { + return false; + } + const ggml_backend_buffer_t buf = w->view_src ? w->view_src->buffer : w->buffer; + return buf != nullptr && ggml_backend_buffer_is_host(buf); +} + +static const config g_config = [] { + config c; + if (const char * e = getenv("LLAMA_EXPERT_PIN_PERIOD")) { + c.period = std::max(1, atoi(e)); + } + if (const char * e = getenv("LLAMA_EXPERT_PIN_START")) { + c.start_tokens = std::max(0, atoi(e)); + } + if (const char * e = getenv("LLAMA_EXPERT_PIN_DONTNEED_GPU")) { + c.dontneed_gpu = (float) atof(e); + } + if (const char * e = getenv("LLAMA_EXPERT_PIN_WILLNEED_GPU")) { + c.willneed_gpu = (float) atof(e); + } + if (const char * e = getenv("LLAMA_EXPERT_PIN_WILLNEED_COLD")) { + c.willneed_cold = (float) atof(e); + } + return c; +}(); + +const config & get_config() { + return g_config; +} + +bool active() { + static const bool v = getenv("LLAMA_EXPERT_PIN") != nullptr; + return v; +} + +// exps tensors per layer, e.g. blk.0.ffn_gate_exps.weight +static const std::regex g_re_exps("blk\\.(\\d+)\\.ffn_(up|down|gate|gate_up)_(ch|)exps\\.weight"); + +static void hint_expert(const ggml_tensor * w, int expert, bool keep) { + if (!hintable(w) || expert < 0 || expert >= (int) w->ne[2]) { + return; + } + const size_t plane = ggml_nbytes(w) / (size_t) w->ne[2]; + madvise_range((const char *) w->data + (size_t) expert * plane, plane, keep); +} + +static void hint_experts(const llama_model * model, + const llama_expert_heatmap & heatmap, + bool (*is_gpu_resident)(void * ud, int il, int e), + void * ud) { + const int n_layers = heatmap.n_layers; + const int n_experts = heatmap.n_experts; + + // group the exps tensors by layer + std::vector> per_layer(n_layers); + for (const auto & [name, tensor] : llama_internal_get_tensor_map(model)) { + std::smatch m; + if (std::regex_search(name, m, g_re_exps)) { + const int il = std::stoi(m[1].str()); + if (il >= 0 && il < n_layers) { + per_layer[il].push_back(tensor); + } + } + } + + std::vector idx(n_experts); + std::vector score(n_experts); + + for (int il = 0; il < n_layers; il++) { + if (per_layer[il].empty()) { + continue; + } + for (int e = 0; e < n_experts; e++) { + score[e] = heatmap.get_score(il, e); + idx[e] = e; + } + + // partition by residency, sort each by score + std::vector gpu, cold; + gpu.reserve(n_experts); + cold.reserve(n_experts); + for (int e = 0; e < n_experts; e++) { + if (is_gpu_resident && is_gpu_resident(ud, il, e)) { + gpu.push_back(e); + } else { + cold.push_back(e); + } + } + auto by_score = [&](int a, int b) { return score[a] > score[b]; }; + + // GPU residents: drop the top fraction, warm the bottom fraction + if (!gpu.empty()) { + std::sort(gpu.begin(), gpu.end(), by_score); + const int n_drop = std::min((int) gpu.size(), + (int) (g_config.dontneed_gpu * (float) gpu.size())); + const int n_warm = std::min((int) gpu.size(), + (int) (g_config.willneed_gpu * (float) gpu.size())); + for (int i = 0; i < n_drop; i++) { + for (const ggml_tensor * w : per_layer[il]) { + hint_expert(w, gpu[i], false); + } + } + for (int i = (int) gpu.size() - n_warm; i < (int) gpu.size(); i++) { + for (const ggml_tensor * w : per_layer[il]) { + hint_expert(w, gpu[i], true); + } + } + } + + // cold: warm the top fraction (most likely promoted next) + if (!cold.empty()) { + std::sort(cold.begin(), cold.end(), by_score); + const int n_warm = std::min((int) cold.size(), + (int) (g_config.willneed_cold * (float) cold.size())); + for (int i = 0; i < n_warm; i++) { + for (const ggml_tensor * w : per_layer[il]) { + hint_expert(w, cold[i], true); + } + } + } + } +} + +void maybe_run(const llama_model * model, + const llama_expert_heatmap * heatmap, + bool (*is_gpu_resident)(void * ud, int il, int e), + void * ud) { + if (!model || !heatmap) { + return; + } + static int64_t last_run = -1; + if (heatmap->tokens_total < g_config.start_tokens) { + return; + } + if (last_run >= 0 && heatmap->tokens_total - last_run < g_config.period) { + return; + } + last_run = heatmap->tokens_total; + hint_experts(model, *heatmap, is_gpu_resident, ud); +} + +} diff --git a/src/llama-expert-pin.h b/src/llama-expert-pin.h new file mode 100644 index 00000000000..aa7c899a42d --- /dev/null +++ b/src/llama-expert-pin.h @@ -0,0 +1,34 @@ +#pragma once + +#include + +struct llama_expert_heatmap; +struct llama_model; + +// mmap page hints for the expert tier. replaces the unconditional MADV_DONTNEED +// on GPU-bound experts: a periodic pass drops the hottest GPU experts' pages +// and warms the ones most likely to be needed next. +namespace llama_expert_pin { + + // dials, all env-overridable with these defaults + struct config { + int period = 32; // tokens between passes + int start_tokens = 128; // first pass at this many tokens + float dontneed_gpu = 0.20f; // top fraction of GPU experts to drop + float willneed_gpu = 0.20f; // bottom fraction of GPU experts to warm + float willneed_cold = 0.40f; // top fraction of cold experts to warm + }; + + const config & get_config(); + + // true when pinning is enabled (LLAMA_EXPERT_PIN set) + bool active(); + + // periodic madvise pass. heatmap feeds the rankings; is_gpu_resident + // (ud, il, e) marks store residents, nullptr = standalone (all cold). + void maybe_run(const llama_model * model, + const llama_expert_heatmap * heatmap, + bool (*is_gpu_resident)(void * ud, int il, int e), + void * ud); + +} From ef1af4b87b017ced02fa4d861dbd75859bcb27b2 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 9 Aug 2026 13:22:13 +0300 Subject: [PATCH 44/61] expert tier: pin flag, drop cache force, log heatmap at generation end --- common/arg.cpp | 15 +- common/common.cpp | 8 +- common/common.h | 4 +- counter.md | 42 ++ include/llama.h | 5 +- manuallog3.md | 755 ++++++++++++++++++++++++++++++++ src/llama-context.cpp | 35 +- src/llama-context.h | 3 + src/llama-expert-heatmap.cpp | 36 +- src/llama-expert-heatmap.h | 3 + src/llama-expert-hotstore.cpp | 15 +- src/llama-expert-hotstore.h | 4 +- src/llama-expert-pin.cpp | 26 +- src/llama-expert-pin.h | 15 +- src/llama-expert-preload.cpp | 12 - src/llama-expert-preload.h | 2 - tools/server/server-context.cpp | 2 + 17 files changed, 898 insertions(+), 84 deletions(-) create mode 100644 counter.md create mode 100644 manuallog3.md diff --git a/common/arg.cpp b/common/arg.cpp index 8615dfa13be..102a79bc1d1 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2706,7 +2706,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex ).set_env("LLAMA_ARG_EXPERT_HEAT_DECAY")); add_opt(common_arg( {"--expert-heat-log-period"}, "N", - "expert heatmap log interval in updates (default: 0, 0 = off)", + "print the expert heatmap at generation end (default: 0, 0 = off)", [](common_params & params, int value) { params.expert_heat_log_period = value; } @@ -2741,14 +2741,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex } ).set_env("LLAMA_ARG_EXPERT_HOT_S")); add_opt(common_arg( - {"--ecf", "--expert-cache-force"}, - {}, - "enable the expert cache (hot store) on non-CUDA backends (testing/emergency only)", - [](common_params & params, bool value) { - params.expert_cache_force = value; - llama_expert_preload::set_force(value); + {"--expert-pin"}, "N", + "fraction (percent) of cold experts to keep pinned in RAM via madvise, " + "0 = off, -1 = auto (hot store sets 40, else 0)", + [](common_params & params, int value) { + params.expert_pin_pct = value; } - )); + ).set_env("LLAMA_ARG_EXPERT_PIN")); add_opt(common_arg( {"--expert-no-evict"}, {}, diff --git a/common/common.cpp b/common/common.cpp index 4bcba8e6e59..af8d2db2ebc 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1274,6 +1274,12 @@ common_init_result::common_init_result(common_params & params, bool model_only) __func__); } + // --expert-pin -1 auto: 40 with the hot store, 0 without + if (params.expert_pin_pct == -1) { + params.expert_pin_pct = params.expert_hot_s != 0 ? 40 : 0; + cparams.expert_pin_pct = params.expert_pin_pct; + } + llama_model * model = llama_model_load_from_file(params.model.path.c_str(), mparams); if (model == NULL) { return; @@ -1700,7 +1706,7 @@ struct llama_context_params common_context_params_to_llama(const common_params & cparams.expert_sync_period = params.expert_sync_period; cparams.expert_hyst = params.expert_hyst; cparams.expert_dwell = params.expert_dwell; - cparams.expert_cache_force = params.expert_cache_force; + cparams.expert_pin_pct = params.expert_pin_pct; return cparams; } diff --git a/common/common.h b/common/common.h index 2874b019a3b..085afd66c24 100644 --- a/common/common.h +++ b/common/common.h @@ -525,12 +525,12 @@ struct common_params { int32_t control_vector_layer_end = -1; // layer range for control vector float expert_heat_decay = 0.999f; // multiplicative decay per update - int expert_heat_log_period = 0; // log period in updates (0 = off) + int expert_heat_log_period = 0; // print heatmap at generation end (0 = off) int expert_hot_s = 0; // top-S expert slots (0 = disabled) int expert_sync_period = 1; // hot store re-sync cadence in tokens float expert_hyst = 1.3f; // hysteresis ratio: only swap when cold >= hyst x hot int expert_dwell = 0; // minimum updates a resident slot must keep before a swap - bool expert_cache_force = false; // bypass the CUDA-only hot store guard + int expert_pin_pct = -1; // percent of cold experts to keep pinned (madvise); -1 = auto bool offline = false; int32_t ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used. diff --git a/counter.md b/counter.md new file mode 100644 index 00000000000..f668a91730b --- /dev/null +++ b/counter.md @@ -0,0 +1,42 @@ +# counter + +Times the user's input produced a materially better decision than my default. +Update only when the user asks. + +## Count: 17 + +## Examples (2026-08-06 session) + +1. **Rotation + cooldown=0 test** - I concluded the corruption was AMD-specific; the user's test ("removing the cooldown should instantly corrupt the rtx?") proved it is Vulkan-wide and duplicate-id driven. + +2. **"It's not the model"** - I attributed a failure to model randomness; the user's 200-run knowledge + the CUDA IQ2 test proved it is the tier/Vulkan. + +3. **Sentinel + mask must stay** - I claimed copy-on-read eliminates them; the user asked "is the sentinel not still necessary?" and was right (alignment + Vulkan safety). + +4. **-no-cnv invalidates corruption tests** - EOS "failures" were ambiguous without conversation mode; I had judged corruption from run counts. + +5. **--fit-target 64 was missing** - the correct fit flag changed the measured config. + +6. **-ehs -1 autofit** - the valid config revealed the tier is ~61 tok/s (faster than my invalid S=96 numbers). + +7. **Native+lazy+madvise instead of the custom pool** - "use llama's native rampool and send a release... load them in vram from disk" replaced two committed pool phases with a simpler, better design. + +8. **"RAM allocation is not actually instant"** - caught that the pool's thousands of per-slice mallocs are slow vs one native allocation. + +9. **Hash is of the memory bytes, not the output** - "I said generate a hash that can only be generated from the memory" - avoided a float-tolerance mess. + +10. **"Try 1024"** - shrinking the hash sample from 16KB to 1KB recovered ~4 tok/s. + +11. **Copy-at-init doubles VRAM** - "will we lose the ability to use the 3gb for actual slots?" - caught the transient double-buffer that would OOM an 8GB card. + +12. **Uniform first-S startup** - the user chose it over my heatmap-seeded idea. + +13. **32+8 memory-fits constraint** - "we crash and oom if the model cant fit in the ram + gpu" - shaped the startup as memory distribution, not just warming. + +14. **"Are you sure there is no other way?"** - led to lifting the gate and discovering the real n_tokens>1 blocker was a mask shape assert, not the predicted kernel crash. + +15. **Kernel speed loss unacceptable** - pushed to the count+rank kernel fix (v3 reference) over batch-split. + +16. **Deferred release** - madvise after verification, less CPU overhead. + +17. **Streaming to GPU instead of second disk read** - "move the layers into the gpu in 128mb chunks" - better than my re-read fallback. diff --git a/include/llama.h b/include/llama.h index 934f26ed221..b6d62da9f2b 100644 --- a/include/llama.h +++ b/include/llama.h @@ -409,7 +409,7 @@ extern "C" { int expert_sync_period; // hot store re-sync cadence in tokens float expert_hyst; // hysteresis ratio for slot swaps int expert_dwell; // min updates a resident slot keeps before swap - bool expert_cache_force; // bypass the CUDA-only hot store guard + int expert_pin_pct; // percent of cold experts to keep pinned (madvise); -1 = auto // a source/target/parent context // can be utilized in various ways, for example by sharing results or llama_memory between 2 contexts @@ -577,6 +577,9 @@ extern "C" { LLAMA_API llama_memory_t llama_get_memory (const struct llama_context * ctx); LLAMA_API enum llama_pooling_type llama_pooling_type(const struct llama_context * ctx); // TODO: rename to llama_get_pooling_type + // print the expert heatmap (no-op when the tier is not active) + LLAMA_API void llama_print_expert_heatmap(const struct llama_context * ctx); + LLAMA_API const struct llama_vocab * llama_model_get_vocab(const struct llama_model * model); LLAMA_API enum llama_rope_type llama_model_rope_type(const struct llama_model * model); diff --git a/manuallog3.md b/manuallog3.md new file mode 100644 index 00000000000..a9ec39a1796 --- /dev/null +++ b/manuallog3.md @@ -0,0 +1,755 @@ +# manuallog: Project6 - Expert-Granular MoE Tiering (GPU Hot Store) + +> Session log + design/state reference for the agent working in +> `/run/media/miltos/Linuxaddon/AI_Workspace/Opencode/Project6/repo2`. +> Read AGENTS.md first for the authoritative rule set and current build/test +> commands. This file is the long-form reference: state, architecture, why past +> decisions failed, and the launch/benchmark etiquette. ASCII only. +> Last updated: 2026-08-05 (section 14 CLEANED: corruption root cause = 3-node +> cold path; fix = port fused MOE_COLD op. Section 14.7 is the current truth). + +## 0. One-line status (2026-08-05) + +Single-stream MoE decode accelerated ~2.5x via an expert-granular GPU hot +store (S=96 slots) + a dedicated `MUL_MAT_ID_COLD` CPU op. Verified at ~40 +tok/s on Qwen3.6-35B-A3B IQ2_M (vs ~16 stock -cmoe) on CUDA. Multi-slot +server batches freeze the hot store (committed). **VULKAN SUPPORT DROPPED** +(2026-08-05): after a full investigation session, all tier implementations +(repo2, v2, v3.bak, v5) corrupt on Vulkan - there is no known-good Vulkan +tier to mirror. Working tree is clean at commit 1a850ec17. +MULTI-SLOT (2C gate, n_tokens>1) IS DROPPED FOR NOW: the mmid count+rank +CUDA port remains reverted, and -np>1 server batches fall back to stock. +CUDA single-stream is the supported tier path. See section 12 for eliminated +theories and the one remaining (unconfirmed) Vulkan lead. + +## 1. Project context & constraints + +- **Repo**: `Project6/repo2` (a fork of llama.cpp, merge-request targeted). + Keep the upstream diff minimal and reviewable. Read `repo2/AGENTS.md` too. +- **Goal (SCOPE - do not overextend)**: MANUAL expert-granular GPU hot store + for MoE. User sets `--expert-hot-s N` (0 = disabled). We: + 1. Find expert weight tensors per layer, compute bytes/slot. + 2. Allocate N GPU slot buffers at context init (VRAM committed at init). + 3. After the heatmap warms, copy the top-N hottest expert weight slices + from CPU to the GPU hot store (one-shot first fill). + 4. Periodically re-sync the GPU slots to mirror the current top-N + (plain top-N mirror on a token cadence, NO hysteresis gate / NO dwell). + 5. Hook the MoE ffn graph so hot experts compute from the GPU hot store, + cold experts from a dedicated CPU op, summed per routed expert. +- **Strict constraint - Rule 6 new-file isolation**: all new logic lives in + new .cpp/.h/.c files. Edits to upstream files stay minimal: single-line + hooks, struct-member or CLI-flag additions, or (where unavoidable) dropping + `static` to share a helper. The cold kernel is the only exception allowed + and it now lives in its OWN file (see Architecture). + +### Out of scope / NOT in scope +- Hysteresis ratio gate + dwell (Trick 5/6): DEFERRED. (v3.bak/v5 DO use + hysteresis + dwell internally, but repo2 deliberately keeps it simple.) +- Cross-session warm start (Trick 21): repo2 fresh heatmap each session. + (v3.bak/v5 have a `.tier` sidecar warm seed - see section 6.J.) +- Prompt harvesting / MOE_COUNT op / TMAX gate (Trick 11, 24). +- Perf tuning tricks (9/10/15) beyond what shipped. +- mmid.cu count+rank CUDA port: ATTEMPTED and REVERTED (see 6.H) - it made + multi-slot output fully corrupt. The 2C gate stays. + +If the user asks for any of the above, treat it as a new phase with its own +scope discussion. oldtricks.md is a REFERENCE for in-scope tricks, not a +feature list. + +## 2. Environment & paths (ABSOLUTE) + +- Project root: `/run/media/miltos/Linuxaddon/AI_Workspace/Opencode/Project6` +- Active source: `Project6/repo2` +- Build dir (CUDA): `Project6/build` (`-DGGML_CUDA=ON -DGGML_CUDA_FA=ON -DCMAKE_BUILD_TYPE=Release`) +- Build dir (Vulkan): `Project6/build_vulkan` (`-DGGML_VULKAN=ON -DGGML_CUDA=OFF`) +- Reference / pre-fix tree: `Project5/repo2` +- Colibri original: `Project1/folder2/llama.cpp` +- **wackMall family (CRITICAL REFERENCES for the Vulkan question)**: + - `Project3/llama-wackMall_v3.bak` - "the one that does not complicate + things". Tier is auto-enabled (no CLI flag), auto-fit S, native 2D LUT, + mask on CPU buffer, discards w_s on tiered path. WORKS on Vulkan. + - `Project3/llama-wackMall_v5` - v3 + more features (RAM pool, sidecar, + autofit ALWAYS ON, hysteresis env vars). WORKS on Vulkan, faster than v3 + (IQ2 22.35 vs 18.65 tok/s on this machine). + - Both have `build_vulkan/` dirs created 2026-08-04 for this investigation. +- Models: `/run/media/miltos/Boost drive/Models/` + - Qwen3.6-35B-A3B IQ2_M (`Qwen3.6-35B-A3B-abliterated-MAX.i1-IQ2_M.gguf`): + 40 MoE layers (0-39, ALL MoE), n_expert=256, n_expert_used=8. Has per-expert + scale tensors (`*.scale` in GGUF) - relevant to the scale bug. + - Qwen3.6-35B-A3B Q5_K_P (`.../BoostHome/Models/Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive-Q5_K_P.gguf`): + bigger quant, per-expert scale too. Has a `.tier` sidecar (v5 warm seed). + - Non-MoE guard: Bonsai-27B-Q1_0 (3.8GB) - heatmap+hotstore stay inert. + +## 3. Architecture (current, accurate) + +### 3.1 Files we touched (in repo2) +``` +src/llama-expert-heatmap.{h,cpp} - per-layer expert usage tracking + log +src/llama-expert-hotstore.{h,cpp} - GPU hot store: alloc, copy_top_s, resync, LUTs +src/llama-expert-tier.{h,cpp} - in-graph dual-path build hook +ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.{c,h} - the MUL_MAT_ID_COLD kernel + shared mmid helpers +common/arg.cpp - --expert-hot-s / -las / --expert-heat-* flags +common/common.{h,cpp} - param plumbing +include/llama.h - context_params fields +src/llama-context.cpp - hotstore/heatmap init + post-compute hook +src/llama-graph.{cpp,h} - moe_sel_experts capture + tier dispatch hook +ggml/include/ggml.h - GGML_OP_MUL_MAT_ID_COLD enum + ctor decl +ggml/src/ggml.c - op name/symbol + constructor + OP_COUNT 102 +ggml/src/ggml-cpu/ggml-cpu.c - 3 switch hooks (forward/n_tasks/work_size) +ggml/src/ggml-cpu/CMakeLists.txt - new source added +``` + +### 3.2 Data flow +1. At context construction (gated: `hparams.n_expert > 0 && !warmup && + hot_s != 0`), build heatmap + hotstore. Hotstore picks the first non-CPU + backend's default buffer type for the GPU hot store. +2. After each ubatch's graph compute (process_ubatch), if heatmap is set, + `synchronize()` then `update_from_graph(res->moe_sel_experts)` reads the + selected-experts tensors back and bumps per-(layer,expert) heat. +3. First fill: `copy_top_s` copies the top-N hottest expert weight slices + CPU->GPU, builds hot_lut/cold_mask per layer, registers each expert + weight tensor with the tier hook. +4. Cadence re-sync: `maybe_resync` mirrors the current top-N into the slots. + NEW (committed 5c5020d80): when the ubatch has n_tokens>1 (multi-slot + server batch), `maybe_resync` is called with multi_slot=true and SKIPS + swapping - the hot store is frozen/static for the batch. +5. At graph build (`build_lora_mm_id`, called by build_moe_ffn), if `w` is + registered with the tier, `llama_expert_tier_build` constructs the dual path: + - hot: remap real ids -> slot ids via hot_lut (sentinel S for cold), + `ggml_mul_mat_id(dst_hot, cur, ids_hot)` on GPU. + - cold: `ggml_mul_mat_id_cold(w, cur, ids, cold_mask)` on CPU - skips + hot experts (cold_mask==0), computes only cold-selected rows. + - result = `add(hot, cold)`. + Returns nullptr -> caller falls back to stock `ggml_mul_mat_id`. + NOTE: the per-expert w_s scale was REMOVED from this path (see 3.5). + +### 3.3 The MUL_MAT_ID_COLD op +- Declared in `ggml.h` after `GGML_OP_GLU`; constructor `ggml_mul_mat_id_cold` + takes `(ctx, as, b, ids, cold_mask)` - 5 sources. +- `cold_mask` is f32[n_experts], 1.0f=cold/compute, 0.0f=hot/skip; the kernel + reads it as int32 zero-check. +- CPU-only. CUDA never sees it. The hot path uses stock `ggml_mul_mat_id`. +- Lives in `ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c`. Uses the SAME + chunking helper as stock mul_mat_id (`ggml_compute_forward_mul_mat_id_one_chunk`), + exposed via `ggml-cpu-mul-mat-id-cold.h`. Reads type info via the public + `ggml_get_type_traits_cpu()` accessor. + +### 3.4 Working-tree changes (REVERTED 2026-08-05 - Vulkan attempt dropped) +Two candidate Vulkan fixes (Option A: removed the in-graph `w_s` scale block; +LUT native 2D) were applied and tested but were INSUFFICIENT to fix Vulkan +corruption, and the Vulkan path is now dropped entirely. They have been +REVERTED; the working tree is clean at 1a850ec17. See section 12. + +### 3.5 v3.bak reference architecture (what "works") +- Tier auto-enabled (no CLI flag; unconditional init), auto-fit S from free VRAM. +- `s.lut` native 2D `ggml_new_tensor_2d(g_ctx_gpu, I32, 1, n_expert)` on GPU. +- `s.mask` `ggml_new_tensor_1d(g_ctx_cpu, I32, n_expert)` on CPU (i32, 1=cold). + IMPORTANT: mask is on a CPU buffer - read directly by the CPU cold op. +- `s.w_hot` 3D on g_ctx_gpu (no_alloc ctx + alloc_ctx_tensors_from_buft, WEIGHTS usage). +- `build_mul_mat_id`: same remap -> get_rows(lut) -> ids_hot -> mul_mat_id(w_hot) + -> mul_mat_id_cold(w, ids, mask, ptrs) -> add. Discards w_s. +- Cold op takes an extra `s.ptrs` (i64 host weight addresses for RAM pool). +- Gate: `ids->ne[1] > g_tmax` (g_tmax default 16 in v3, 1 in v5). +- v5 adds: RAM pool (SR slots), sidecar warm seed, LLAMA_EXPERT_DECAY (default + 1.0) / LLAMA_EXPERT_HYSTERESIS (default 1.5) env vars, dwell>=32, autofit + ALWAYS ON, LLAMA_EXPERT_S/HOT/ADAPT env vars. + +## 4. Build & test (authoritative; AGENTS.md is the source of truth) + +### Configure from clean (CUDA) +```sh +cd /run/media/miltos/Linuxaddon/AI_Workspace/Opencode/Project6 +mkdir -p build && cd build +cmake ../repo2 -DGGML_CUDA=ON -DGGML_CUDA_FA=ON -DCMAKE_BUILD_TYPE=Release +``` +### Configure from clean (Vulkan) +```sh +mkdir -p build_vulkan && cd build_vulkan +cmake ../repo2 -DGGML_VULKAN=ON -DGGML_CUDA=OFF -DCMAKE_BUILD_TYPE=Release +``` +### Build (incremental) +```sh +cd /run/media/miltos/Linuxaddon/AI_Workspace/Opencode/Project6/build +cmake --build . -j$(nproc) --target llama-completion llama-server +# Vulkan: +cd /run/media/miltos/Linuxaddon/AI_Workspace/Opencode/Project6/build_vulkan +cmake --build . -j$(nproc) --target llama-completion +``` +### Device selection (Vulkan - IMPORTANT, differs from vulkaninfo) +`./bin/llama-completion --list-devices` is authoritative. In llama.cpp's +enumeration order on this machine: +- Vulkan0 = NVIDIA GeForce RTX 3070 Laptop GPU (the FAST one) +- Vulkan1 = AMD Radeon RX 570 (RADV POLARIS10) +This is OPPOSITE to `vulkaninfo` (which shows AMD as GPU0). Use +`GGML_VK_VISIBLE_DEVICES=0` for the RTX, `=1` for the AMD. A default run +picks Vulkan0 = RTX. +### PASS/FAIL test (CUDA single-stream, the headline case) +```sh +cd /run/media/miltos/Linuxaddon/AI_Workspace/Opencode/Project6/build +ulimit -c 0 +./bin/llama-completion \ + -m "/run/media/miltos/Boost drive/Models/Qwen3.6-35B-A3B-abliterated-MAX.i1-IQ2_M.gguf" \ + -ngl 99 -cmoe -c 8000 -ctk q8_0 -ctv q8_0 -b 256 -ub 256 -t 6 \ + --kv-offload --flash-attn on -fit off --temp 0 -no-cnv \ + --expert-hot-s 96 \ + -p "Write a comprehensive technical guide to setting up a home Linux server" \ + -n 256 60 ms/token (stock ~16 tok/s), +crash, or incoherent output. +### NOTE ON --no-mmap (REMOVED PERMANENTLY, 2026-08-04) +Do NOT pass `--no-mmap` to test commands anymore. The user said it "hurts us" +permanently. Reason observed: with --no-mmap each server reads the FULL model +into RAM; two servers = ~23GB, maxed 31GB RAM + 17GB swap (looked like a leak, +was not - killing the servers freed all of it instantly). Drop it. + +## 5. Launch & benchmark etiquette (READ BEFORE ANY TEST) + +1. **Check for concurrent builds/tests first** (`ps -eo pid,pmem,comm --sort=-pmem | head`). + RAM/CPU pressure causes OOMs and spurious timeouts. Wait for it. +2. **Minimum -n 128** for generation tests. -n 16 masks bugs and is noisy. + For the wackMall/v5 caching tier use -n 256+ (it has not warmed up until then). +3. **Non-interactive**: pass -no-cnv and redirect stdin from /dev/null + (`< /dev/null`) so the test exits on its own. +4. **-st exits cleanly** on llama-cli (single-turn). Keep `timeout 60` as a + hard safety net for llama-completion (it has no -st; it exits after -n). +5. **Do NOT change user-specified flags** without asking. -ngl 99 -cmoe etc. +6. **Never use decay 0.9 for "diagnostic" tests** unless explicitly told. +7. **Use LLAMA_LOG, not LLAMA_LOG_INFO**, for any line you must see. +8. **Use the grep tool narrow**: scope `path` to a dir or a file. +9. **Quote model paths** with spaces. +10. **Do NOT pass -ngl to the CPU-only build**. +11. **Per backend build dirs**: build/ = CUDA, build_vulkan/ = Vulkan. Do not + confuse binaries. +12. **Launching a server without softlocking the harness**: do NOT use + `pkill -f llama-server` (kills your own shell). Use `pkill -x llama-server`. + To launch detached WITHOUT the harness killing it on timeout: use + `setsid --fork ./bin/llama-server ... log 2>&1 < /dev/null` + then poll /health in a SEPARATE command. The earlier nohup+disown+same-cmd + poll softlocks the harness (the timeout then SIGTERMs the process group). +13. **Commit style**: user's name (Miltos22), lowercase, no period, no + Co-authored-by/Assisted-by tags. Draft the message WITH the user before + committing. Local commits only, no push, no PR. +14. **No git mutations** (commit/push/amend/rebase) unless explicitly asked. + The user explicitly asked for the -las commit amend twice. +15. **push needs a token**: `git push https://miltos22:TOKEN@github.com/...` + (username/password auth is rejected by GitHub). The remote is the user's + fork `miltos22/llama.cpp-wackMall-merge-request.git`. Only push when asked. + +## 6. Debugging history - WHY past decisions didn't work + +### A. The `ggml_backend_tensor_get` signature trap +5 args vs real 4: `ggml_backend_tensor_get(tensor, data, offset, size)`. + +### B. OOM on CPU-only inference +35B fully on CPU (-ngl 0) triggers kernel OOM killer during PP graph alloc. +Fix: reduce -c. Watch RAM before builds/tests. + +### C. LLAMA_LOG_INFO is invisible (CRITICAL QUIRK) +LLAMA_LOG_INFO -> LOG_LEVEL_TRACE(4) filtered by INFO(3). Use LLAMA_LOG (0). + +### D. "Hysteresis" naming confusion +Heatmap accumulation rate vs swap-policy ratio gate (Trick 6). repo2 uses pure +additive counting + decay only; no ratio gate / dwell (deferred). + +### E. CLI float lambda +`common_arg` lambdas only accept `int` and `std::string`. Use std::stof. + +### F. Fabricated test data - NEVER LIE ABOUT OUTPUT +NEVER invent log lines or test output. AGENTS.md Rule 1: evidence or it did +not happen. + +### G. GPU tensor readback bug (the big one) +Async CUDA + recycled scratch buffers -> garbage expert ids. Fix: +`synchronize()` before readback AND `ggml_set_output(selected_experts)`. + +### H. The 4-step cold chain REGRESSION -> MUL_MAT_ID_COLD +Original chain: 5-node remap x 4 x 3 matrices x 40 layers = ~3,500 extra +graph nodes + dummy expert-0 rows. 1.3 tok/s. Ported GGML_OP_MUL_MAT_ID_COLD +(colibri Trick 7 Path A): single skip-hot CPU op. 40 tok/s. +Then moved the kernel to its own file (`d1cdf1b35`, pushed via sync-fork). + +### I. The cold kernel from_float NULL segfault +`type_traits_cpu[type].from_float` is NULL for IQ2_M. Fix: fetch from +`type_traits_cpu[vec_dot_type].from_float` (matches stock mul_mat_id). + +### J. The "self-contained new-file kernel" rewrite attempt +The working version REUSES stock chunking helpers; a fresh self-contained +rewrite segfaulted (bug I). Do not re-attempt without a new decision. + +### K. **mmid.cu count+rank port ATTEMPTED AND REVERTED (2026-08-04)** +Goal: lift the 2C gate (n_tokens==1) so the tier works at n_tokens>1 +(multi-slot server). Ported the colibri count+rank fix into BOTH the generic +and templated paths of repo2's mmid.cu (kept write_inverse), sized shared +memory for the worst case (n_tokens*n_expert_used), and REMOVED the gate +`if (cur->ne[2] > 1) return nullptr;` in tier.cpp. +RESULT: **fully corrupt multi-slot output** - worse than before (before = slow +but correct stock fallback; after = garbage). User: "the slots thing does not +work for multiple ones, it is actually worse than before." +REVERTED both files to committed state (git checkout). The 2C gate stays. +The user decided to instead FREEZE the hot store during multi-slot batches +(see 3.2, committed 5c5020d80). The mmid count+rank fix may be revisited only +as a separate deliberate effort; the corrupt result suggests our sentinel +duplicate handling interacts badly with the CUDA MMQ path beyond what colibri's +fix covers (or the port had a subtle bug). + +### L. Freeze-exchange analysis (and why it was chosen) +Earlier analysis said freezing does NOT fix multi-slot speed (the gate is the +cause, not resync churn). But the mmid port made things CORRUPT, so the user +chose freeze + keep the gate: multi-slot falls back to stock (correct, slow) +and the hot store stops swapping during multi-slot batches. Committed as +`5c5020d80`. Tested: multi-slot -np 8 coherent (stock speed ~2.45 t/s/slot), +single-stream 38-41 tok/s no regression. This is the current committed state. + +### M. Emoji-loop degenerate output is NOT the tier +--ignore-eos + temp-0 + this Qwen3 model drifts into repetition loops. +Isolated: happens with tier ON and OFF; only --ignore-eos triggers it. +Do not blame the tier; check --ignore-eos first. + +### N. The earlier "random server crash" was a self-inflicted kill +`pkill -f llama-server` killed the launching shell. Use `pkill -x`. + +### O. Plant_static and log_hit_rate are diagnostic, not core +Diagnostic helpers, not part of the core feature path. + +### P. **Vulkan device ordering trap (2026-08-04)** +`vulkaninfo` shows AMD as GPU0, NVIDIA as GPU1. But llama.cpp's OWN +`--list-devices` shows Vulkan0 = NVIDIA RTX 3070, Vulkan1 = AMD RX 570. +A test with GGML_VK_VISIBLE_DEVICES=1 silently ran on the AMD (9.94 tok/s, +"it still used the 570"). Correct: GGML_VK_VISIBLE_DEVICES=0 = RTX. + +### Q. **RAM was NOT leaking - it was --no-mmap (2026-08-04)** +Two --no-mmap servers held 2x 11.6GB model in RAM -> 30Gi used, 17Gi swap, +user thought it was a leak. Killing them freed 23GB instantly. Also: removing +`-c` from a run let context default huge and eat RAM alongside the v5 RAM pool +(18Gi). Always keep `-c` on multi-GB model tests. + +### R. **repo2 tier corrupts on Vulkan; v3.bak/v5 are coherent (2026-08-04)** +This is the OPEN issue. Full detail in section 9. + +### S. **v5 "autofit always on" gotcha (2026-08-04)** +v3.bak/v5 enable the tier UNCONDITIONALLY (no CLI flag needed) and autofit S +from free VRAM. So EVERY v3/v5 run is tiered - there is no "stock" v3/v5 run +to compare against without disabling the tier. My early "v5 stock-ish" 23.52 +tok/s number was tiered too (run-to-run variance / tuning churn). + +### T. **v5 cold first-run is slow (2026-08-04)** +v5 Q5 Vulkan first run 2.96 tok/s (init churn: RAM pool, sidecar build). +Warm run (2nd, sidecar present) 11.72 tok/s. First-run numbers are meaningless +for v5; use warm runs. Also the `.tier` sidecar file is a warm seed - deleting +it forces cold start. User asked to delete sidecar + LLAMA_EXPERT_DECAY=0.999 +LLAMA_EXPERT_HYSTERESIS=1.3 + no -cmoe/-ngl/-t for a "clean" v5 test: result +was coherent, 1.61 tok/s with RAM pool 18Gi (slow but works). + +## 7. CLI flags (repo2) + +| Flag | Type | Default | Env | Purpose | +|------|------|---------|-----|---------| +| `-las`, `--expert-hot-s N` | int | 0 | `LLAMA_ARG_EXPERT_HOT_S` | top-S expert slots for GPU hot store (0=disabled). -las added this session (pushed) | +| `--expert-heat-decay F` | float | 0.99 | `LLAMA_ARG_EXPERT_HEAT_DECAY` | multiplicative decay per update | +| `--expert-heat-log-period N` | int | 100 | `LLAMA_ARG_EXPERT_HEAT_LOG_PERIOD` | log + re-sync cadence in updates | + +There is NO `LLAMA_EXPERT_S` env fallback - removed earlier, CLI only. +(v3.bak/v5 DO use LLAMA_EXPERT_S / LLAMA_EXPERT_DECAY / LLAMA_EXPERT_HYSTERESIS +/ LLAMA_EXPERT_ADAPT / LLAMA_EXPERT_HOT - but those are THEIR flags.) + +## 8. Commits & roadmap + +### Commits on this branch (origin/master has them up to 6e75753ab) +- `fcaac3d75` expert heatmap: decay-tracked usage counters per layer +- `610802380` expert heatmap: add top-S ranking, log top-8 per layer +- `21537c16f` expert heatmap: add --expert-hot-s flag for GPU hot store slot count +- `b27d2f59e` expert heatmap: fix GPU tensor readback via ggml_set_output and synchronize +- `413e65dde` expert heatmap: move readback logic into heatmap module +- `3fd577828` Merge remote-tracking branch 'origin/master' +- `23ff80ec3` expert hotstore: add per-layer expert slot sizing +- `289c41ef5` expert hotstore: allocate GPU hot store buffers for S slots +- `284215c04` expert hotstore: reduced cross contamination when expert args off +- `8e955700f` expert heatmap: count updates in tokens not layers +- `08e657d41` expert heatmap: fix decay and log trigger +- `1aefbbe58` expert hotstore: copy top-S experts to GPU after first ubatch +- `cee1740bb` expert hotstore: re-sync hot slots on cadence (stable slots) +- `a3c442540` expert hotstore: add sentinel slot for zero-contribution routing +- `904090276` expert hotstore: per-layer LUTs and masks for in-graph routing +- `8d1a68e5b` Merge remote-tracking branch 'origin/master' +- `3c9616b3a` expert tier: hook GPU hot store into graph with MUL_MAT_ID_COLD cold op +- `d1cdf1b35` ggml-cpu: move MUL_MAT_ID_COLD kernel to its own file +- `8687ee2b6` common: added -las short flag for expert hot store slots (alias of --expert-hot-s) [PUSHED] +- `6e75753ab` Merge branch 'ggml-org:master' into master [on origin/master - created by GitHub "Sync fork" button, upstream pulled in; local fast-forwarded after tar backup] +- `5c5020d80` expert hotstore: freeze swapping during multi-slot batches [LOCAL, NOT pushed, 1 ahead] +- `1a850ec17` llama : gate expert hot store to CUDA only, with force override [LOCAL, NOT pushed, 2 ahead] - CUDA-only guard + LLAMA_EXPERT_HOT_FORCE + +### Working tree (CLEAN as of 2026-08-05) +- Clean at `1a850ec17`. The Option A (scale removed) + LUT 2D Vulkan-fix + changes were reverted, and the CUDA-only guard commit is in. Nothing + uncommitted. + +### DEFERRED / NOT DONE +- Step 3f: auto-S via native fit (`--expert-hot-s -1`). NOT DONE in repo2. +- Hysteresis ratio gate + dwell (Trick 5/6): deferred in repo2. +- mmid.cu count+rank CUDA port: ATTEMPTED, CORRUPT, REVERTED. Do not re-approach without a new decision. +- Per-backend gate (option B): let Vulkan/Metal enable tier at n_tokens>1 - irrelevant now (gate is by design after the mmid failure). +- Fused MoE cold (GELU/gate_up): not ported. + +## 9. KNOWN LIMITATIONS + THE OPEN VULKAN ISSUE + +### 9.1 The 2C gate (n_tokens==1) - MULTI-SLOT DROPPED FOR NOW +Tier only engages at single-token decode. Multi-slot server batches fall back +to stock. This is now BY DESIGN after the mmid port failed (see 6.K/6.L). +DECISION (2026-08-05): multi-slot (n_tokens>1) tiered support is DROPPED FOR +NOW. The mmid.cu count+rank port remains reverted; do not re-approach without +an explicit new decision. -np>1 server batches use stock CPU MoE speed. +Single-stream CUDA is the supported tier path. + +### 9.2 ~~OPEN: repo2 tier corrupts on Vulkan~~ RESOLVED BY DROPPING VULKAN (2026-08-05) +Historical record only. The Vulkan tier path is DROPPED and the CUDA-only +guard (1a850ec17) prevents accidental use. Facts below are preserved for +reference; see section 12 for the eliminated theories and the sole remaining +lead. FACTS (all verified 2026-08-04): +- repo2 tier + Vulkan (RTX) + IQ2_M or Q5_K_P => `` loop / garbage. +- repo2 tier + CUDA + same models => fully coherent. +- v3.bak tier + Vulkan + same models => coherent (IQ2 18.65, Q5 5.29 tok/s). +- v5 tier + Vulkan + same models => coherent (IQ2 22.35, Q5 warm 11.72). +- repo2 stock (tier disabled) + Vulkan => coherent. +- repo2 tier + Vulkan + `-ngl 0` => still `` loop (rules out GPU->CPU + cur sync for the cold op). +- repo2 tier + Vulkan + S=1 => coherent (but ends early, not a full test). +- v3.bak tier + Vulkan + `-ngl 0` => coherent (the decisive A/B: same model, + same flags, same Vulkan backend, v3 works / repo2 loops). + +ROOT CAUSE STATUS: two candidate fixes applied but NOT sufficient: +1. Scale removed (Option A) - fixed binary garbage, still loops. +2. LUT native 2D - still loops. +Both were structurally necessary to match v3.bak but the corruption persists. + +NEXT LEAD (2026-08-04, highest priority to investigate): +**cold_mask buffer placement.** v3.bak allocates the cold `mask` on a CPU +buffer (`ggml_new_tensor_1d(g_ctx_cpu, I32, n_expert)`). repo2 allocates +`cold_mask` in the SAME ggml context as dst_hot/hot_lut, which is allocated +with the GPU buft - so `cold_mask` lives on the GPU buffer. The CPU cold op +reads `mask->data` DIRECTLY (`const int32_t * cold_mask = (const int32_t *) +mask->data;`). On Vulkan, a GPU-buffer tensor's `->data` is NOT host-readable +=> garbage mask => wrong skip/compute decisions => degenerate output. On CUDA +it apparently works (host-mapped or scheduler copies). THE FIX would be to +allocate cold_mask on a CPU/host buffer (like v3.bak), or read the mask via a +host-accessible path. VERIFY THIS FIRST in the next session. +Secondary candidates if the mask fix is not sufficient: +- The `ggml_mul_mat_id` hot call at n_tokens==1 uses the Vulkan VEC-id path + (`mul_mat_vec_id`); upstream `ggml_vk_get_dequantize_mul_mat_vec_id` omits + GGML_TYPE_IQ2_M from its supported list (has IQ2_XXS/XS/S but not IQ2_M). + v3.bak runs IQ2_M on the same backend, so likely not the blocker, but worth + confirming repo2 does not take a different dispatch. +- `ggml_mul_mat_id_cold` signature differs: v3 takes `(mask, ptrs)`, repo2 + takes `(cold_mask)` only. The ptrs arg is a RAM-pool optimization, likely + irrelevant to correctness. +- The `dst_hot` buffer content after `ggml_backend_tensor_set` copies on + Vulkan - verify by dumping dst_hot vs source on both backends. + +### 9.3 Hotstore segfault without -cmoe +repo2 tier requires the MoE expert weights to stay on CPU (needs `-cmoe` or +`-ncmoe`). Running `--expert-hot-s 96` WITHOUT -cmoe segfaulted on Vulkan +(2026-08-04): the hotstore copy reads `w->data` as a host pointer, but +without -cmoe the experts are GPU-offloaded. This is a latent bug - the tier +should reject or handle non-CPU experts. Not the Vulkan corruption (CUDA needs +-cmoe too and works). + +### 9.4 IQ2_M missing from Vulkan mul_mat_vec_id supported list +Upstream `ggml_vk_get_dequantize_mul_mat_vec_id` lists IQ2_XXS/XS/S but not +IQ2_M. Not the primary suspect (v3.bak runs IQ2_M cleanly on the same backend). + +### 9.5 Server -np>1 = stock speed +Multi-slot decode batches (n_tokens>1) fall back to stock CPU MoE via the +gate - ~20 tok/s aggregate regardless of S. Single-stream is where the +40 tok/s lives. This is by design after the mmid failure. + +### 9.6 Hot store competes for VRAM +8GB VRAM + 11GB IQ2_M model + S=96 hotstore barely coexist. Q5_K_P needs S<=48 +(96 slots would be 9424 MiB, exceeds 8GB). Larger GPU = more headroom. + +### 9.7 Stale comments / minor +- `ggml.h` cold_mask comment calls it "i32" but the tensor is f32 (read as int32). +- `ggml-rpc.h:14` static_assert 101 vs ggml.c 102 (harmless, RPC off). +- `llama-expert-tier.h` header comment describes the OLD dual-mul_mat_id design + (cold_lut/hot_mask) - stale, code is correct. Low priority. +- v3.bak/v5 ggml-vulkan.cpp matches upstream - their Vulkan success is NOT a + backend patch; it is their tier code. + +## 10. Reference docs + +- `oldtricks.md` - 25 tricks from colibri/wackMall. In scope: Trick 13 + (WEIGHTS usage tag), Trick 18 (non-owning ggml contexts / no_alloc batch), + Trick 23 (create-then-allocate), Trick 7 Path A (MUL_MAT_ID_COLD, ported). + Others OUT OF SCOPE unless re-discussed. +- wackMall references: `Project3/llama-wackMall_v3.bak` (simple, works on + Vulkan) and `Project3/llama-wackMall_v5` (feature-rich, faster, works on + Vulkan). Their tier files are the reference for the Vulkan fix. +- Colibri mmid.cu count+rank diff (the "revisit later" reference): the change + to `mm_ids_helper` replacing `iex_used` (one hit) with `cnt` + inclusive + warp scan `rank` + `n_hit`, so every duplicate sentinel hit gets its own + compact row. `Project1/folder2/llama.cpp/ggml/src/ggml-cuda/mmid.cu`. + NOTE: attempted in repo2 2026-08-04 and produced corrupt output - see 6.K. +- `Project6/repo2/AGENTS.md` - llama.cpp contributor rules. + +## 11. Vulkan benchmark table (2026-08-04, all RTX 3070 unless noted) + +| Build | Model | Flags | Result | tok/s | +|-------|-------|-------|--------|-------| +| repo2 CUDA | IQ2 | -cmoe -ngl99 S96 | coherent | 26.2-41 | +| repo2 Vulkan | IQ2 | -cmoe -ngl99 S96 | GARBAGE-> loop | 14-16 | +| repo2 Vulkan | Q5 | -cmoe -ngl99 S48 | GARBAGE | 5.24 | +| repo2 Vulkan | IQ2 | -cmoe -ngl0 S96 | loop | 4.66 | +| repo2 Vulkan | IQ2 | -cmoe -ngl0 S1 | coherent (short) | 5.9 | +| v3.bak Vulkan | IQ2 | -cmoe -ngl99 autoS | coherent | 16.4-18.7 | +| v3.bak Vulkan | Q5 | -cmoe -ngl99 autoS=51 | coherent | 5.29 | +| v3.bak Vulkan | IQ2 | -ngl0 autoS | coherent | 4.35 | +| v5 Vulkan | IQ2 | -cmoe -ngl99 autoS | coherent | 13.96-22.35 | +| v5 Vulkan | Q5 | -cmoe -ngl99 autoS=51 warm | coherent | 11.72 | +| v5 Vulkan | Q5 | cold first run | coherent | 2.96 | +| v5 Vulkan | Q5 | decay.999 hyst1.3 no-cmoe c8000 n256 | coherent (slow, RAM pool 18Gi) | 3.92 | +| v5 Vulkan | IQ2 | AMD RX570 (=1) | coherent | 9.94 | + +Takeaways: v3/v5 coherent on Vulkan; repo2 not. v5 faster than v3 (IQ2 22 vs 19, +Q5 11.7 vs 5.3). v3/v5 autofit S; repo2 manual S. The v3/v5 `.tier` sidecar is +a warm seed (seed coverage 84.6% warm vs 0% cold). + +## 12. VULKAN DECISION - DROPPED (2026-08-05) + +The Vulkan tier attempt is DROPPED after a full session of investigation. +CUDA tier (40 tok/s, coherent) remains the supported path. This section +records the eliminated theories and remaining leads so future sessions do not +re-litigate. + +### ELIMINATED THEORIES (do not re-test without new evidence) + +1. **IQ2_M unsupported type theory - DEAD.** The model file is named + "i1-IQ2_M" but the ACTUAL expert tensor types are `iq2_s` (gate/up, 82MiB) + and `iq3_s` (down, 110MiB), verified from loader logs. GGML_TYPE_IQ2_M does + NOT exist in this tree's ggml.h enum (lines 400-430). IQ2_S/IQ3_S ARE in + both the Vulkan dmmv getter and supports_op lists. So the hot node runs the + vec-id path fine (no abort, exit 0). Type was never the problem. +2. **supports_op probe as a discriminator - DEAD.** CUDA's MUL_MAT_ID + supports_op also lacks whatever (its list ends at IQ2_XXS/XS/S, IQ3_*, IQ4_*, + BF16) yet CUDA works. A supports_op probe would disable the working CUDA + path too. +3. **Mask buffer placement / dtype - DEAD.** cold_mask being F32-on-GPU (repo2) + vs I32-on-CPU (v3) is irrelevant: the scheduler copies the mask to CPU + correctly (seen as CPU#leaf_1012#0 in dumps) and the F32 zero-check is + equivalent to I32. +4. **tensor_set / buffer_clear asyncness - DEAD.** Both ggml_vk_buffer_write_2d + and ggml_vk_buffer_memset are synchronous (host-visible memcpy or + transfer+fence-wait). No race. +5. **IQ2_M missing from Vulkan vec-id pipeline - DEAD.** Irrelevant since the + type is actually IQ2_S/IQ3_S, and v3/v5 also lack IQ2_M in that getter yet + (see #6) none of them are actually coherent on Vulkan anyway. +6. **"v3/v5 work on Vulkan" - FALSE PREMISE, DEAD.** Directly tested 2026-08-05: + v2 (Project1/llama-wackMall_v2, its OWN vulkan build), v3.bak, and v5 ALL + corrupt on Vulkan with the tiered IQ2 config (same `` loop) including + with `-ngl 99 -cmoe`. The manuallog's earlier "coherent on Vulkan" rows for + v3/v5 do not reproduce under these exact commands and were likely measured + under different conditions (Q5 model, or runs that terminated early). + Conclusion: there is NO known-good Vulkan tier implementation to mirror. +7. **Per-matrix cold+ADD on Vulkan vs fused cold - DEAD.** v2/v3 share + byte-identical build_mul_mat_id + begin/end_moe_cold + ggml_moe_cold fused + cold, and v2 corrupts while the "fix" claim for v3 is void (both corrupt). + The v2-vs-v3 code diff is exclusively the prefetch/predict/poolB feature, + which is inactive by default; replacing v2's 3 differing files with v3's + changed nothing (still corrupt). So the graph structure is NOT the cause. +8. **Scheduler "1.wgt" weights-rule difference - DEAD.** The rule is + identical across repo2/v3/v5. All assign the hot node to Vulkan. + +### REMAINING LEAD (unconfirmed, low priority since Vulkan is dropped) + +The tiered hot node (`mul_mat_id(dst_hot[S+1 planes], cur, ids_hot)` with +slot indices 0..S incl. the zeroed sentinel plane) runs on Vulkan's vec-id +path and corrupts on ALL implementations (repo2/v2/v3/v5). Stock Vulkan (tier +off, MoE on CPU) is coherent. So the bug is in how Vulkan's `mul_mat_id` +handles the slot-indexed S+1-plane hot tensor with the sentinel plane, NOT in +repo2's tier code. Candidate mechanisms, unverified: + - coopmat2 path on Ampere (RTX 3070) mishandling the slot tensor + - vec-id shader plane indexing with a zeroed sentinel plane + - row_ids/result-tile shared memory sizing for S+1 planes +If Vulkan support is ever re-attempted, start here with a minimal standalone +repro (mul_mat_id on a 3-plane slot tensor vs the full tensor) before touching +the tier. + +### ACTIONS TAKEN +- Reverted uncommitted Vulkan fix attempts (Option A scale removal + LUT 2D) + in tier.cpp/hotstore.cpp -> working tree back to clean committed state + (5c5020d80). CUDA path untouched and verified. +- Added CUDA-only guard in llama-context.cpp (2026-08-05): the hotstore now + only allocates into a backend whose device name starts with "CUDA". On Vulkan + (bugged) it logs a WARN and skips -> tier off -> coherent stock output. + On CPU the existing non-CPU check already skips. LLAMA_EXPERT_HOT_FORCE=1 + overrides the guard (re-enables the tier on any non-CUDA GPU for testing/ + emergency only). Verified: Vulkan skips+coherent, CUDA enables+coherent + (re-sync swapped 2471), Vulkan+HOT_FORCE engages tier. COMMITTED as + `1a850ec17`. HEAD is now 1a850ec17 (2 ahead of origin, nothing uncommitted). + +## 13. Next actions (for the next session) + +State as of 2026-08-05: ALL WORK COMMITTED. Working tree clean, 5 commits +ahead of origin. Feature set complete for this pass: +- Auto-S via fit (`--expert-hot-s -1`) - DONE (f201ef52a) +- Hysteresis gate (--expert-hyst, default 1.3) - DONE (ca624bc06) +- decay default 0.999 - DONE (ca624bc06) +- --expert-dwell exists (default 0 = off) - DONE but OFF by default + +Committed this session (oldest->newest): +- `1a850ec17` llama : gate expert hot store to CUDA only, with force override +- `b18c4266c` common: expert hot store manual slots activate --cmoe +- `f201ef52a` common: autofit expert hot store slots via --expert-hot-s -1 +- `ca624bc06` expert hot store: hysteresis gate for slot swaps + +Verified on Qwen3.6-35B-A3B IQ2_M (255-run decode): stock autofit 33.25 +tok/s, autofit tier (S=133) 41 tok/s, hyst gate on 34.6-35.1 tok/s +(hyst=1.3 dwell=0: 35.1, 2600 swaps vs 2985 no-gate). Dwell default 0 +(user decision: not worth the speed cost). Dwell aging counts real tokens +and initial fill is eligible (else first sync defers -> speed crash). + +## 14. CPU OVERHEAD + CORRUPTION INVESTIGATION (2026-08-05) - CLEANED REFERENCE + +This section is the authoritative record. It is CHRONOLOGICAL and marks +superseded conclusions explicitly. The final truth (14.7) is the current +state. All measurements on CUDA build, Qwen3.6-35B-A3B IQ2_M, -c 8000, +--temp 0, --fit-target as noted, unless stated. Corruption judgements are +DIRECT READS of full output (see AGENTS.md rule 10), never grep counts. + +### 14.1 Phase A - the "5-10% CPU overhead" (t6) is CLOSED as a non-issue + +The user-reported +5-10% CPU vs stock was investigated thoroughly and +proved to be a 256-token short-run artifact of the tier's initial +convergence burst, not a real overhead. + +Key measurements (n=256 burst vs n=1024/4096 real): +- -t 6, n=256: ours 178.6 ms CPU/token vs stock 160.6 = +11%. Real per + token, but ONLY during the first ~100-token convergence burst. +- -t 6, n=4096 (VALID, fresh hotset): dynamic 60.87 tok/s / 98.1 ms + CPU/token vs static 58.45 / 101.3. Dynamic is FASTER and uses LESS CPU + than a frozen set. Both crush stock (34 tok/s, 160.6 ms/token). +- Verdict: dynamic tier at real lengths = ~1.8x faster and ~39% less CPU + per token than stock. CLOSED. Benchmark at -n 1024+ only. + +Superseded intermediate claims (for history only): 14.9 "ROOT CAUSE = +heatmap bookkeeping" was WRONG (conflated readback+resync+fill quality; +controlled test showed readback only ~1.8 ms/token); 14.11 "swap moves +~20ms/token" was the 256-burst artifact; 14.7 PASSIVE / 14.8 GGML_OPENMP=OFF +were dead ends (spin is load-bearing; native pool identical cost). + +### 14.2 Phase B - the -t 12 collapse is REAL and structural + +The real remaining issue is -t 12 (ours 11-19 tok/s vs stock 25). Isolated: +- Not heatmap (static also collapses), not swaps (0 in static), not + convergence (n=1024), not cold-gpu. It is the tier graph at 12 threads. +- Energy (perf power/energy-pkg, t12, n=1024): stock 3604 J / 3.48 J/tok + vs ours 5435 J / 5.25 J/tok. Ours does 51% MORE real work, not spin. +- Root cause: repo2 emits 3 separate MUL_MAT_ID_COLD CPU nodes per MoE + layer (gate, up, down) + 3 mul + 1 add = ~120 CPU nodes/token, each with + a full ggml_barrier (ggml-cpu.c:3116). v3/v5 use ONE fused GGML_OP_MOE_COLD + node per layer computing the whole chain under ONE barrier (~40 + nodes/token, 3x fewer barriers). + +### 14.3 Phase C - corruption discovered, mechanism LOCALIZED + +While tuning repo2's swap cadence for the t12 fix, output CORRUPTION was +found (mid-word splits: "Here 's", "summar izing", "Back ups", "/ usr", +"x 8 6 _ 6 4"). This VOIDED the tuning speed gains (they were measured on +corrupt output). + +Localization (direct read of interleaved stdout): a resync marker lands +BETWEEN the halves of a generated word: + ...using a **De=== re-sync swapped X ===bian-based** system... +The model emitted "De", a resync fired, then "bian" - the expert's weights +changed between two tokens of one word. Cadence sensitivity: cadence-1 = +pervasive, cadence-2 = intermittent, cadence-20 = rare (1/~700 words), +cadence-100 = unobserved. Resyncs cluster in the initial convergence burst. + +GRAPHLOG experiment (ggml_cuda_graph_compute instrumentation): the corrupt +token is produced in DIRECT mode (no CUDA graph active yet) exactly at a +resync marker. This RULED OUT the CUDA-graph-replay theory. + +### 14.4 Phase D - candidate fixes (ALL SUPERSEDED by 14.7) + +Multiple fixes reduced corruption frequency but NONE reached zero: +1. host-mask (cold_mask on host/CPU buffer) - closed a cross-stream race + on the mask write but corruption persisted. +2. post-resync ggml_backend_sched_synchronize - orders LUT copies but not + the logical hot/cold flip. +3. active-expert guard (don't evict experts routed this token) - helped + only partially (protects THIS token, not the word's prefix). +4. PP-priming (fill at first decode) - reasonable perf idea, not a fix. +5. rate-limit bursts (suppress swaps N tokens after a big resync) - capped + the burst but residual corruption remained. +6. word-boundary gating (Enhancement B: only resync when the just-sampled + token is ENTIRELY whitespace/punct, no cap) - reduced to rare, NOT zero. +7. atomic-pair LUT+mask write ordering - helped, not zero. +8. CUDA set_tensor device-wide sync (option 1) - helped, not zero. + +None achieved the required ZERO. All are superseded by 14.7. + +### 14.5 Phase E - static store is 100% clean (the control) + +LLAMA_EXPERT_STATIC_FILE (planted fixed set, heatmap+resync OFF, 0 swaps): +t6, n=1024, 30.36 tok/s, 755 words DIRECT READ = COMPLETELY CLEAN. Zero +mid-word splits. PROVES: zero swaps = zero corruption. The swap itself is +the sole corruption source. (Autofit S is nondeterministic and can OOM +graph capture; pin S manually when testing.) + +### 14.6 Phase F - v3 aggressive-repin: fused op is STRUCTURALLY immune + +To discriminate "v3 clean because swaps are RARE" (frequency) vs "v3 clean +because fused op is EXACT" (structural): forced v3's repin gate to be +aggressive (dwell 0, ratio 0.3 instead of 32/1.5). Repins = 10,280 +(massive). t6, n=1024, cold start, 57.56 tok/s. DIRECT READ of 656 words: +COMPLETELY CLEAN. "iptables", "systemd-resolved", "/etc/netplan/ +01-netcfg.yaml", "SSH: 22" all correct. ZERO artifacts at ~10 swaps/token. + +CONCLUSION: frequency theory WRONG. The fused single-node MOE_COLD op is +structurally immune to the mid-word corruption regardless of swap rate. +repo2's 3-node separate path is the corruption source. + +### 14.7 FINAL TRUTH (current state) - port the fused op + +The fix is to PORT v3/v5's fused GGML_OP_MOE_COLD op into repo2: +- One graph node computes the entire cold MoE chain (gate->silu/gelu-> + up->down) under ONE threadpool barrier, with a fixed intermediate + quantization contract (act_q) that matches what the hot path produces, + so hot<->cold flips are numerically identical (no divergence to corrupt). +- Repo2's 3-node separate MUL_MAT_ID_COLD path is the REGRESSION. +- Porting it fixes BOTH the -t 12 collapse (3x fewer barriers) AND the + corruption (structural immunity). Genuine cadence-1/2 becomes possible. +- v3 tree reverted to original gate after the experiment (git diff clean). + +FILES for the port (see AGENTS.md "Files you may touch" + approved +llama-graph.cpp): +- ggml/include/ggml.h: GGML_OP_MOE_COLD enum + ggml_moe_cold() decl +- ggml/src/ggml.c: op name, constructor, shape inference +- ggml/src/ggml-cpu/ggml-cpu.c: ggml_compute_forward_moe_cold kernel + + dispatch registration (~250 lines, the core) +- src/llama-expert-tier.h/.cpp: begin_moe_cold / end_moe_cold + g_hot_only +- src/llama-graph.cpp (APPROVED): cold_ok gate + begin/end calls in + build_moe_ffn (v5 lines 1974/2111) +- src/llama-context.cpp: wire the fused update path + +## 15. Current state and next actions (for the next session) + +STATE (2026-08-05): working tree has UNCOMMITTED experimental changes from +the corruption investigation (host-mask, word-boundary gating, rate-limit, +PP-priming, atomic-pair, active-guard, device-sync in ggml-cuda.cu, +graphlog instrumentation, diagnostic env hooks). These are all SUPERSEDED +by the fused-op port decision (14.7) and should be DISCARDED before +porting (git checkout -- the dirty files) to keep the port diff clean. + +COMMITTED (unpushed, keep): +- `5425deb6b` sentinel autofit S-1 fix +- `919168e1e` MSVC Interlocked fallback in cold op + +OPEN THREADS: +1. ACTIVE: port the fused GGML_OP_MOE_COLD op (14.7). Clean base first. +2. Decide whether to push the 2 committed commits (needs token). +3. v3 tree is untouched (reverted); v3/v5 remain reference trees for the + fused op implementation. +4. SYCL backend port of the tier exists (user's agent); the CUDA-only + guard (strncmp "CUDA") is more restrictive than the backend-agnostic + code requires - consider an allowlist if shipping multi-backend. diff --git a/src/llama-context.cpp b/src/llama-context.cpp index aa7b7b0dc9f..88544eec2c8 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -467,6 +467,7 @@ llama_context::llama_context( // heatmap exists for the tier, the heat log, or standalone pinning // (LLAMA_EXPERT_PIN without the hot store) + llama_expert_pin::set_pct(params.expert_pin_pct); if (hparams.n_expert > 0 && !cparams.warmup && (params.expert_heat_log_period != 0 || params.expert_hot_s != 0 || llama_expert_pin::active())) { @@ -484,9 +485,7 @@ llama_context::llama_context( params.expert_hot_s, sync_period, params.expert_hyst, params.expert_dwell); // enable the GPU hot store on any GPU backend (CUDA, Vulkan, ROCm, - // SYCL, Metal, ...). --expert-cache-force overrides the guard. - const bool force = params.expert_cache_force || getenv("LLAMA_EXPERT_CACHE_FORCE") != nullptr; - llama_expert_preload::set_force(force); + // SYCL, Metal, ...). bool cache_enabled = false; std::vector gpu_bufts; for (auto & backend : backends) { @@ -501,8 +500,8 @@ llama_context::llama_context( cache_enabled = expert_hotstore->allocate(gpu_bufts, model.tensor_split(), (int) gpu_bufts.size()); } // launch hint: cache did not engage, usually no GPU accelerator - if (!cache_enabled && !force) { - LLAMA_LOG_WARN("%s: expert cache is OFF: %d slots requested but no GPU backend in use (use --ecf to force it on)\n", + if (!cache_enabled) { + LLAMA_LOG_WARN("%s: expert cache is OFF: %d slots requested but no GPU backend in use\n", __func__, params.expert_hot_s); } expert_hotstore->log(); @@ -1441,9 +1440,9 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll return nullptr; } - // the cold op tallied the selected experts into host counts during the - // compute; feed them into the heatmap directly (no D2H readback, no sync) - if (expert_heatmap && expert_hotstore && expert_hotstore->is_filled) { + // cold-op counts feed the heatmap directly (no D2H readback, no sync). + // decode only: prefill routing is uniform and would dilute the ranking. + if (expert_heatmap && expert_hotstore && expert_hotstore->is_filled && ubatch.n_tokens == 1) { expert_hotstore->read_counts(*expert_heatmap, ubatch.n_tokens); } if (expert_heatmap && expert_hotstore && expert_hotstore->is_filled) { @@ -1454,8 +1453,9 @@ llm_graph_result * llama_context::process_ubatch(const llama_ubatch & ubatch, ll } // standalone pin mode (no hot store): feed the heatmap from the graph - // readback and warm the top cold experts on mmap - if (expert_heatmap && !expert_hotstore && llama_expert_pin::active()) { + // readback. decode only (see above). + if (expert_heatmap && !expert_hotstore && llama_expert_pin::active() && ubatch.n_tokens == 1) { + expert_heatmap->tick(1); synchronize(); for (const auto & [il, tensor] : res->moe_sel_experts) { if (!tensor || !tensor->data) { @@ -2461,6 +2461,19 @@ uint32_t llama_context::graph_max_nodes(uint32_t n_tokens) const { return res; } +void llama_context::print_expert_heatmap() const { + // --expert-heat-log-period: print at generation end (0 = off) + if (expert_heatmap && expert_heatmap->log_period != 0) { + expert_heatmap->log(); + } +} + +void llama_print_expert_heatmap(const struct llama_context * ctx) { + if (ctx) { + ctx->print_expert_heatmap(); + } +} + llm_graph_result * llama_context::get_gf_res_reserve() const { return static_cast(gf_res_reserve.get()); } @@ -3618,7 +3631,7 @@ llama_context_params llama_context_default_params() { /*.expert_sync_period =*/ 1, /*.expert_hyst =*/ 1.3f, /*.expert_dwell =*/ 0, - /*.expert_cache_force =*/ false, + /*.expert_pin_pct =*/ -1, /*.ctx_other =*/ nullptr, }; diff --git a/src/llama-context.h b/src/llama-context.h index a56ea564724..5fceb3aabad 100644 --- a/src/llama-context.h +++ b/src/llama-context.h @@ -243,6 +243,9 @@ struct llama_context { public: uint32_t graph_max_nodes(uint32_t n_tokens) const; + // print the expert heatmap (no-op when not active) + void print_expert_heatmap() const; + // can reuse the llm_graph_result instance of the context (for example to update a memory module) llm_graph_result * get_gf_res_reserve() const; diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 7bf72c854f9..40a779def37 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -20,19 +20,7 @@ llama_expert_heatmap::llama_expert_heatmap( } void llama_expert_heatmap::update_counts(const std::vector & per_layer, int n_tokens) { - // batched decay: apply decay_rate^2 every two updates instead of - // decay_rate every update (identical long-run weighting, half the work) - ++update_counter; - if (update_counter % 2 == 0) { - const float rate = decay_rate * decay_rate; - for (int i = 0; i < n_layers * n_experts; i++) { - heat[i] *= rate; - } - } - - if (n_tokens == 1) { - generated_tokens_count++; - } + tick(n_tokens); for (int il = 0; il < n_layers && il < (int) per_layer.size(); il++) { const int32_t * cnt = per_layer[il]; if (!cnt) { @@ -45,17 +33,11 @@ void llama_expert_heatmap::update_counts(const std::vector & pe } } } - - tokens_total += n_tokens; - if (log_period > 0 && tokens_total / log_period > (tokens_total - n_tokens) / log_period) { - log(); - } } -void llama_expert_heatmap::update_ids(int layer_idx, const int32_t * expert_ids, int n_ids, int n_tokens) { - if (layer_idx < 0 || layer_idx >= n_layers || !expert_ids) { - return; - } +void llama_expert_heatmap::tick(int n_tokens) { + // batched decay: apply decay_rate^2 every two updates instead of + // decay_rate every update (identical long-run weighting, half the work) ++update_counter; if (update_counter % 2 == 0) { const float rate = decay_rate * decay_rate; @@ -66,6 +48,13 @@ void llama_expert_heatmap::update_ids(int layer_idx, const int32_t * expert_ids, if (n_tokens == 1) { generated_tokens_count++; } + tokens_total += n_tokens; +} + +void llama_expert_heatmap::update_ids(int layer_idx, const int32_t * expert_ids, int n_ids, int n_tokens) { + if (layer_idx < 0 || layer_idx >= n_layers || !expert_ids) { + return; + } float * layer_heat = &heat[layer_idx * n_experts]; for (int t = 0; t < n_tokens; t++) { for (int e = 0; e < n_ids; e++) { @@ -75,11 +64,10 @@ void llama_expert_heatmap::update_ids(int layer_idx, const int32_t * expert_ids, } } } - tokens_total += n_tokens; } void llama_expert_heatmap::log() const { - LLAMA_LOG("=== Expert heatmap (tokens %" PRId64 ") ===\n", tokens_total); + LLAMA_LOG("expert_heatmap: tokens %" PRId64 "\n", tokens_total); for (int l = 0; l < n_layers; l++) { const float * layer_heat = heat.data() + l * n_experts; diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index abe8f9b3071..84b9900a7e7 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -27,6 +27,9 @@ struct llama_expert_heatmap { // standalone path (no cold op): per-expert increment from graph readback void update_ids(int layer_idx, const int32_t * expert_ids, int n_ids, int n_tokens); + + // once per ubatch: decay + token counters + void tick(int n_tokens); void log() const; float get_score(int layer_idx, int expert_id) const; diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 5e44000fb30..84fbe06de9e 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -399,12 +399,12 @@ bool llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { last_sync_tokens = heatmap.tokens_total; is_filled = true; update_luts(); - fprintf(stderr, "=== Expert hot store: startup batch moved to GPU ===\n"); + fprintf(stderr, "hotstore: startup batch moved to GPU\n"); return true; } -// --ecf mode: pa4-style direct swap (1 per layer per token). copy the new -// expert to a free or gate-cleared slot, verify the GPU copy, route +// LLAMA_EXPERT_FULL_SYNC: direct swap (1 per layer per token). copy the +// new expert to a free or gate-cleared slot, verify the GPU copy, route // immediately. no handshake pacing queues - the verify is the safety net. bool llama_expert_hotstore::resync_full_mirror(const llama_expert_heatmap & heatmap, int budget) { if (!is_filled || hot_s <= 0 || buf_dev.empty()) { @@ -532,9 +532,6 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { if (!is_filled || hot_s <= 0 || buf_dev.empty()) { return false; } - if (llama_expert_preload::get_force()) { - return resync_full_mirror(heatmap); // --ecf: full store mirror every token - } if (getenv("LLAMA_EXPERT_DEBUG")) { fprintf(stderr, "hotstore: resync tok=%lld\n", (long long) heatmap.tokens_total); } @@ -845,7 +842,7 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { if (changed > 0) { update_luts(dirty); if (getenv("LLAMA_EXPERT_DEBUG")) { - fprintf(stderr, "=== Expert hot store: re-sync changed %d slots ===\n", changed); + fprintf(stderr, "hotstore: re-sync changed %d slots\n", changed); } } return changed > 0; @@ -981,7 +978,7 @@ void llama_expert_hotstore::log_hit_rate(const std::vector 0) { - fprintf(stderr, "=== expert hot hit rate: %zu/%zu = %.1f%% ===\n", hits, total, 100.0f * (float) hits / (float) total); + fprintf(stderr, "hotstore: hit rate %zu/%zu = %.1f%%\n", hits, total, 100.0f * (float) hits / (float) total); } } @@ -1035,7 +1032,7 @@ float llama_expert_hotstore::target_hit_rate() const { } void llama_expert_hotstore::log() const { - fprintf(stderr, "=== Expert hotstore sizing (S=%d) ===\n", hot_s); + fprintf(stderr, "hotstore: sizing (S=%d)\n", hot_s); const bool debug = getenv("LLAMA_EXPERT_DEBUG") != nullptr; size_t total = 0; for (int il = 0; il < n_layers; il++) { total += bytes_per_slot[il]; diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index fd0836226ac..9ea32330ff5 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -159,8 +159,8 @@ llama_expert_hotstore(const llama_model * model, int n_layers, // returns true if any slot changed (caller should synchronize the GPU). bool resync_top_s(const llama_expert_heatmap & heatmap); - // --ecf mode: mirror the entire store to the top-S every token (direct - // swaps, hash-verified, copy-on-read). no pacing queues. + // LLAMA_EXPERT_FULL_SYNC: mirror the store to the top-S every token + // (direct swaps, hash-verified, copy-on-read). no pacing queues. bool resync_full_mirror(const llama_expert_heatmap & heatmap, int budget = 1); // cadence-gated wrapper: re-sync only if tokens_total crossed sync_period; diff --git a/src/llama-expert-pin.cpp b/src/llama-expert-pin.cpp index 26f24a079bf..8f013f5d608 100644 --- a/src/llama-expert-pin.cpp +++ b/src/llama-expert-pin.cpp @@ -35,9 +35,8 @@ static void madvise_range(const void * p, size_t len, bool keep) { #endif } -// only hint file-backed (mmap) host tensors; anonymous buffers must never be -// DONTNEED'd (would zero them). a host tensor without a data pointer has no -// pages to hint. +// only hint file-backed (mmap) host tensors; DONTNEED on anonymous buffers +// would zero them. no data pointer = no pages to hint. static bool hintable(const ggml_tensor * w) { if (!w || !w->data) { return false; @@ -70,9 +69,18 @@ const config & get_config() { return g_config; } +static int g_pct = -1; + +void set_pct(int pct) { + g_pct = pct; +} + +int get_pct() { + return g_pct; +} + bool active() { - static const bool v = getenv("LLAMA_EXPERT_PIN") != nullptr; - return v; + return getenv("LLAMA_EXPERT_PIN") != nullptr || g_pct > 0; } // exps tensors per layer, e.g. blk.0.ffn_gate_exps.weight @@ -152,8 +160,14 @@ static void hint_experts(const llama_model * model, // cold: warm the top fraction (most likely promoted next) if (!cold.empty()) { std::sort(cold.begin(), cold.end(), by_score); + float cold_pct = g_config.willneed_cold; + if (const char * e = getenv("LLAMA_EXPERT_PIN_WILLNEED_COLD")) { + cold_pct = (float) atof(e); + } else if (g_pct > 0) { + cold_pct = (float) g_pct / 100.0f; + } const int n_warm = std::min((int) cold.size(), - (int) (g_config.willneed_cold * (float) cold.size())); + (int) (cold_pct * (float) cold.size())); for (int i = 0; i < n_warm; i++) { for (const ggml_tensor * w : per_layer[il]) { hint_expert(w, cold[i], true); diff --git a/src/llama-expert-pin.h b/src/llama-expert-pin.h index aa7c899a42d..3df0a5116d5 100644 --- a/src/llama-expert-pin.h +++ b/src/llama-expert-pin.h @@ -5,9 +5,8 @@ struct llama_expert_heatmap; struct llama_model; -// mmap page hints for the expert tier. replaces the unconditional MADV_DONTNEED -// on GPU-bound experts: a periodic pass drops the hottest GPU experts' pages -// and warms the ones most likely to be needed next. +// mmap page hints for the expert tier. periodic madvise pass: drop the hottest +// GPU experts' pages, warm the ones most likely needed next. namespace llama_expert_pin { // dials, all env-overridable with these defaults @@ -21,11 +20,15 @@ namespace llama_expert_pin { const config & get_config(); - // true when pinning is enabled (LLAMA_EXPERT_PIN set) + // resolved pin fraction from --expert-pin (percent, -1 = unset) + void set_pct(int pct); + int get_pct(); + + // true when pinning is enabled (LLAMA_EXPERT_PIN set or pct > 0) bool active(); - // periodic madvise pass. heatmap feeds the rankings; is_gpu_resident - // (ud, il, e) marks store residents, nullptr = standalone (all cold). + // periodic madvise pass. is_gpu_resident marks store residents, + // nullptr = standalone (all cold) void maybe_run(const llama_model * model, const llama_expert_heatmap * heatmap, bool (*is_gpu_resident)(void * ud, int il, int e), diff --git a/src/llama-expert-preload.cpp b/src/llama-expert-preload.cpp index a9911ef60c6..4414f7a20e7 100644 --- a/src/llama-expert-preload.cpp +++ b/src/llama-expert-preload.cpp @@ -80,17 +80,8 @@ int get_slots() { return g_slots; } -bool g_force = false; bool g_no_evict = false; -void set_force(bool force) { - g_force = force; -} - -bool get_force() { - return g_force; -} - void set_no_evict(bool no_evict) { g_no_evict = no_evict; } @@ -103,9 +94,6 @@ bool tier_will_engage() { if (g_slots <= 0) { return false; } - if (g_force || getenv("LLAMA_EXPERT_CACHE_FORCE") != nullptr) { - return true; - } for (size_t i = 0; i < ggml_backend_dev_count(); i++) { const ggml_backend_dev_t dev = ggml_backend_dev_get(i); if (dev && ggml_backend_dev_type(dev) == GGML_BACKEND_DEVICE_TYPE_GPU) { diff --git a/src/llama-expert-preload.h b/src/llama-expert-preload.h index db089d630ce..4c43008dea9 100644 --- a/src/llama-expert-preload.h +++ b/src/llama-expert-preload.h @@ -22,8 +22,6 @@ namespace llama_expert_preload { void set_slots(int s); int get_slots(); void set_model_path(const char * path); // for the debug disk hash - void set_force(bool force); // --ecf / LLAMA_EXPERT_CACHE_FORCE - bool get_force(); // full-sync-every-token mode void set_no_evict(bool no_evict); // --expert-no-evict bool get_no_evict(); diff --git a/tools/server/server-context.cpp b/tools/server/server-context.cpp index 38d2e5c7a05..78482be9e92 100644 --- a/tools/server/server-context.cpp +++ b/tools/server/server-context.cpp @@ -3170,6 +3170,7 @@ struct server_context_impl { SLT_WRN(slot, "%s", "empty prompt - releasing slot\n"); slot.print_timings(); + llama_print_expert_heatmap(slot.ctx_tgt); send_final_response(slot); slot.release(); @@ -3853,6 +3854,7 @@ struct server_context_impl { if (!process_token(result, slot)) { // release slot because of stop condition slot.print_timings(); + llama_print_expert_heatmap(slot.ctx_tgt); send_final_response(slot); metrics.on_prediction(slot); slot.release(); From a435e6c8f0e0c29d8b7c5f22edbcc26fac5e481f Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 9 Aug 2026 15:12:38 +0300 Subject: [PATCH 45/61] expert tier: add --expert-copy, fix adaptive cadence --- common/arg.cpp | 9 +++++++++ common/common.cpp | 1 + common/common.h | 1 + include/llama.h | 1 + src/llama-context.cpp | 3 ++- src/llama-expert-hotstore.cpp | 21 ++++++++++++--------- src/llama-expert-hotstore.h | 3 ++- 7 files changed, 28 insertions(+), 11 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index 102a79bc1d1..0d44a72cb16 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2756,6 +2756,15 @@ common_params_context common_params_parser_init(common_params & params, llama_ex llama_expert_preload::set_no_evict(value); } )); + add_opt(common_arg( + {"--expert-copy"}, + {}, + "copy experts to the GPU store (keep the RAM copy). default: move " + "(GPU store replaces the RAM copy; frees RAM)", + [](common_params & params, bool value) { + params.expert_copy = value; + } + ).set_env("LLAMA_ARG_EXPERT_COPY")); GGML_ASSERT(params.n_gpu_layers < 0); // string_format would need to be extended for a default >= 0 add_opt(common_arg( {"-ngl", "--gpu-layers", "--n-gpu-layers"}, "N", diff --git a/common/common.cpp b/common/common.cpp index af8d2db2ebc..d6aea6a43fa 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1707,6 +1707,7 @@ struct llama_context_params common_context_params_to_llama(const common_params & cparams.expert_hyst = params.expert_hyst; cparams.expert_dwell = params.expert_dwell; cparams.expert_pin_pct = params.expert_pin_pct; + cparams.expert_copy = params.expert_copy; return cparams; } diff --git a/common/common.h b/common/common.h index 085afd66c24..c58d063e0fa 100644 --- a/common/common.h +++ b/common/common.h @@ -531,6 +531,7 @@ struct common_params { float expert_hyst = 1.3f; // hysteresis ratio: only swap when cold >= hyst x hot int expert_dwell = 0; // minimum updates a resident slot must keep before a swap int expert_pin_pct = -1; // percent of cold experts to keep pinned (madvise); -1 = auto + bool expert_copy = false; // copy experts to GPU (keep RAM copy); default move bool offline = false; int32_t ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used. diff --git a/include/llama.h b/include/llama.h index b6d62da9f2b..f8a119980ee 100644 --- a/include/llama.h +++ b/include/llama.h @@ -410,6 +410,7 @@ extern "C" { float expert_hyst; // hysteresis ratio for slot swaps int expert_dwell; // min updates a resident slot keeps before swap int expert_pin_pct; // percent of cold experts to keep pinned (madvise); -1 = auto + bool expert_copy; // copy experts to GPU (keep RAM copy); default move // a source/target/parent context // can be utilized in various ways, for example by sharing results or llama_memory between 2 contexts diff --git a/src/llama-context.cpp b/src/llama-context.cpp index 88544eec2c8..29898aaab57 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -483,7 +483,7 @@ llama_context::llama_context( expert_hotstore = std::make_unique( &model, hparams.n_layer(), hparams.n_expert, params.expert_hot_s, sync_period, - params.expert_hyst, params.expert_dwell); + params.expert_hyst, params.expert_dwell, params.expert_copy); // enable the GPU hot store on any GPU backend (CUDA, Vulkan, ROCm, // SYCL, Metal, ...). bool cache_enabled = false; @@ -3632,6 +3632,7 @@ llama_context_params llama_context_default_params() { /*.expert_hyst =*/ 1.3f, /*.expert_dwell =*/ 0, /*.expert_pin_pct =*/ -1, + /*.expert_copy =*/ false, /*.ctx_other =*/ nullptr, }; diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 84fbe06de9e..778d62f6701 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -68,14 +68,15 @@ static const std::regex g_re_exps_weight("blk\\.(\\d+)\\.ffn_(up|down|gate|gate_ llama_expert_hotstore::llama_expert_hotstore( const llama_model * model, int n_layers, int n_experts, int hot_s, int sync_period, - float hyst, int dwell) : + float hyst, int dwell, bool copy_mode) : n_layers(n_layers), n_experts(n_experts), hot_s(hot_s), bytes_per_slot(n_layers, 0), sync_period(sync_period), hyst(hyst), - dwell(dwell) { + dwell(dwell), + copy_mode(copy_mode) { if (n_layers <= 0) { return; } @@ -696,10 +697,13 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { for (auto it = pin.begin(); it != pin.end();) { if (it->verified && --it->countdown <= 0) { rout[it->expert] = 1; // the GPU output counts now - for (entry * ent : entries_by_layer[il]) { - const int pidx = llama_expert_preload::index_of(ent->src); - if (pidx >= 0) { - llama_expert_preload::free_cpu_slice(pidx, it->expert); + if (!copy_mode) { + // move: the expert now lives on the GPU, free its RAM copy + for (entry * ent : entries_by_layer[il]) { + const int pidx = llama_expert_preload::index_of(ent->src); + if (pidx >= 0) { + llama_expert_preload::free_cpu_slice(pidx, it->expert); + } } } dirty[il] = 1; @@ -855,10 +859,9 @@ bool llama_expert_hotstore::maybe_resync(const llama_expert_heatmap & heatmap, b } // continuous adaptive cadence: the sync period grows with the hit rate // relative to the target. floor of 10 tokens (never resync more often), - // growing up to 32 as the hit rate climbs far above the target. no hard - // disable thresholds - the period just keeps growing. + // stretching to 32 as the hit rate climbs toward 6x the target. float ratio = hit_rate_valid ? hit_rate / target_hit_rate() : 0.0f; - const int eff_period = std::max(10, std::min(32, 1 + (int) (4.0f * ratio))); + const int eff_period = std::max(10, std::min(32, 10 + (int) (22.0f * (ratio - 1.0f) / 5.0f))); if (heatmap.tokens_total / eff_period > last_sync_tokens / eff_period) { if (getenv("LLAMA_EXPERT_FULL_SYNC")) { // test: mirror the whole store to the top-S on each sync instead of diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index 9ea32330ff5..a97db31fc99 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -97,6 +97,7 @@ struct llama_expert_hotstore { // expert scores >= hyst * the incumbent AND the slot has dwelled long enough float hyst = 0.0f; // 0 = gate off (swap freely) int dwell = 0; // minimum syncs a resident must keep; 0 = off + bool copy_mode = false; // keep the RAM copy of promoted experts (copy), else move // max concurrent transfers in flight per layer, per direction (eviction // queue + promotion queue). higher = faster store adaptation, at the cost // of more slots temporarily in transition (not counted). @@ -137,7 +138,7 @@ struct llama_expert_hotstore { llama_expert_hotstore(const llama_model * model, int n_layers, int n_experts, int hot_s, int sync_period = 0, - float hyst = 0.0f, int dwell = 0); + float hyst = 0.0f, int dwell = 0, bool copy_mode = false); ~llama_expert_hotstore(); From 27a4e50e3c897148ad5d12f3d1cf4363c09a4dce Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 9 Aug 2026 17:12:18 +0300 Subject: [PATCH 46/61] expert tier: d2d promote/demote, heatmap sidecar, frozen store --- common/arg.cpp | 8 +++++ common/common.cpp | 2 ++ common/common.h | 1 + include/llama.h | 4 +++ src/llama-context.cpp | 22 +++++++++++++ src/llama-context.h | 4 +++ src/llama-expert-heatmap.cpp | 47 ++++++++++++++++++++++++++- src/llama-expert-heatmap.h | 6 ++++ src/llama-expert-hotstore.cpp | 60 +++++++++++++++++++++++++++++++++++ src/llama-expert-hotstore.h | 2 ++ 10 files changed, 155 insertions(+), 1 deletion(-) diff --git a/common/arg.cpp b/common/arg.cpp index 0d44a72cb16..9cb170e6d89 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2765,6 +2765,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex params.expert_copy = value; } ).set_env("LLAMA_ARG_EXPERT_COPY")); + add_opt(common_arg( + {"--expert-sidecar"}, + {}, + "load the expert heatmap sidecar (.tier) at start, save it at exit", + [](common_params & params, bool value) { + params.expert_sidecar = value; + } + ).set_env("LLAMA_ARG_EXPERT_SIDECAR")); GGML_ASSERT(params.n_gpu_layers < 0); // string_format would need to be extended for a default >= 0 add_opt(common_arg( {"-ngl", "--gpu-layers", "--n-gpu-layers"}, "N", diff --git a/common/common.cpp b/common/common.cpp index d6aea6a43fa..659cbaa86c0 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1708,6 +1708,8 @@ struct llama_context_params common_context_params_to_llama(const common_params & cparams.expert_dwell = params.expert_dwell; cparams.expert_pin_pct = params.expert_pin_pct; cparams.expert_copy = params.expert_copy; + cparams.expert_sidecar = params.expert_sidecar; + cparams.model_path = params.model.path.c_str(); return cparams; } diff --git a/common/common.h b/common/common.h index c58d063e0fa..c60b839edbd 100644 --- a/common/common.h +++ b/common/common.h @@ -532,6 +532,7 @@ struct common_params { int expert_dwell = 0; // minimum updates a resident slot must keep before a swap int expert_pin_pct = -1; // percent of cold experts to keep pinned (madvise); -1 = auto bool expert_copy = false; // copy experts to GPU (keep RAM copy); default move + bool expert_sidecar = false; // load/save the expert heatmap sidecar (.tier) bool offline = false; int32_t ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used. diff --git a/include/llama.h b/include/llama.h index f8a119980ee..537471f9570 100644 --- a/include/llama.h +++ b/include/llama.h @@ -403,6 +403,9 @@ extern "C" { struct llama_sampler_seq_config * samplers; size_t n_samplers; + // model file path; used for the expert heatmap sidecar (.tier) + const char * model_path; + float expert_heat_decay; // expert heatmap decay per update int expert_heat_log_period; // expert heatmap log interval int expert_hot_s; // number of top-S expert slots for GPU hot store @@ -411,6 +414,7 @@ extern "C" { int expert_dwell; // min updates a resident slot keeps before swap int expert_pin_pct; // percent of cold experts to keep pinned (madvise); -1 = auto bool expert_copy; // copy experts to GPU (keep RAM copy); default move + bool expert_sidecar; // load/save the expert heatmap sidecar (.tier) // a source/target/parent context // can be utilized in various ways, for example by sharing results or llama_memory between 2 contexts diff --git a/src/llama-context.cpp b/src/llama-context.cpp index 29898aaab57..b15bc91dd09 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -478,6 +478,18 @@ llama_context::llama_context( params.expert_hot_s); } + // expert sidecar: restore the heatmap from .tier if present; freeze + // store adaptation so the run measures the pre-warmed store + expert_sidecar_enabled = params.expert_sidecar; + expert_sidecar_path = std::string(params.model_path ? params.model_path : "") + ".tier"; + bool sidecar_loaded = false; + if (expert_heatmap && params.expert_sidecar) { + const std::string sc = expert_sidecar_path; + if (expert_heatmap->load(sc.c_str())) { + sidecar_loaded = true; + } + } + if (hparams.n_expert > 0 && !cparams.warmup && params.expert_hot_s != 0) { const int sync_period = params.expert_sync_period; expert_hotstore = std::make_unique( @@ -507,6 +519,10 @@ llama_context::llama_context( expert_hotstore->log(); } + if (sidecar_loaded && expert_hotstore) { + expert_hotstore->frozen = true; + } + // Initialize the full vocabulary token ids for backend samplers. { const int n_vocab = model.vocab.n_tokens(); @@ -519,6 +535,10 @@ llama_context::llama_context( } llama_context::~llama_context() { + if (expert_heatmap && expert_sidecar_enabled && !cparams.warmup) { + const std::string sc = expert_sidecar_path; + expert_heatmap->save(sc.c_str()); + } // wait for any pending asynchronous copies into the output buffers before they are freed synchronize(); @@ -3625,6 +3645,7 @@ llama_context_params llama_context_default_params() { /*.kv_unified =*/ false, /*.sampler =*/ nullptr, /*.n_sampler =*/ 0, + /*.model_path =*/ nullptr, /*.expert_heat_decay =*/ 0.999f, /*.expert_heat_log_period =*/ 0, /*.expert_hot_s =*/ 0, @@ -3633,6 +3654,7 @@ llama_context_params llama_context_default_params() { /*.expert_dwell =*/ 0, /*.expert_pin_pct =*/ -1, /*.expert_copy =*/ false, + /*.expert_sidecar =*/ false, /*.ctx_other =*/ nullptr, }; diff --git a/src/llama-context.h b/src/llama-context.h index 5fceb3aabad..94ae88018d8 100644 --- a/src/llama-context.h +++ b/src/llama-context.h @@ -375,6 +375,10 @@ struct llama_context { std::unique_ptr expert_heatmap; std::unique_ptr expert_hotstore; + // expert sidecar: .tier path and flag, kept for the destructor save + bool expert_sidecar_enabled = false; + std::string expert_sidecar_path; + // host buffer for the model output (logits and embeddings) ggml_backend_buffer_ptr buf_output; diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 40a779def37..8caf77426dd 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -3,8 +3,9 @@ #include #include -#include #include +#include +#include llama_expert_heatmap::llama_expert_heatmap( int n_layers, int n_experts, @@ -132,3 +133,47 @@ std::vector llama_expert_heatmap::get_top_s(int layer_idx, int s) const { result.assign(indices.begin(), indices.begin() + k); return result; } + +bool llama_expert_heatmap::save(const char * path) const { + FILE * f = fopen(path, "wb"); + if (!f) { + return false; + } + const char magic[4] = {'H', 'M', 'S', 'D'}; + const int32_t nl = n_layers, ne = n_experts, uc = update_counter; + const int64_t tt = tokens_total, gc = generated_tokens_count; + bool ok = fwrite(magic, 1, 4, f) == 4 && + fwrite(&nl, sizeof(nl), 1, f) == 1 && + fwrite(&ne, sizeof(ne), 1, f) == 1 && + fwrite(&tt, sizeof(tt), 1, f) == 1 && + fwrite(&gc, sizeof(gc), 1, f) == 1 && + fwrite(&uc, sizeof(uc), 1, f) == 1 && + fwrite(heat.data(), sizeof(float), heat.size(), f) == heat.size(); + fclose(f); + return ok; +} + +bool llama_expert_heatmap::load(const char * path) { + FILE * f = fopen(path, "rb"); + if (!f) { + return false; + } + char magic[4] = {0}; + int32_t nl = 0, ne = 0, uc = 0; + int64_t tt = 0, gc = 0; + const bool ok = fread(magic, 1, 4, f) == 4 && memcmp(magic, "HMSD", 4) == 0 && + fread(&nl, sizeof(nl), 1, f) == 1 && nl == n_layers && + fread(&ne, sizeof(ne), 1, f) == 1 && ne == n_experts && + fread(&tt, sizeof(tt), 1, f) == 1 && + fread(&gc, sizeof(gc), 1, f) == 1 && + fread(&uc, sizeof(uc), 1, f) == 1 && + fread(heat.data(), sizeof(float), heat.size(), f) == heat.size(); + fclose(f); + if (!ok) { + return false; + } + tokens_total = tt; + generated_tokens_count = gc; + update_counter = uc; + return true; +} diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index 84b9900a7e7..d4e28cde8fe 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -34,4 +34,10 @@ struct llama_expert_heatmap { float get_score(int layer_idx, int expert_id) const; std::vector get_top_s(int layer_idx, int s) const; + + // persist the heat to a sidecar file (binary) and restore it on a later + // run. load() returns false when the file is missing or incompatible + // (different n_layers/n_experts). + bool save(const char * path) const; + bool load(const char * path); }; diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 778d62f6701..75d28b98bd4 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -790,6 +790,63 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { } } // boundary gate + // ---- promote/demote (D2D): the top expert on a worse device that + // beats the better device's coldest resident by hysteresis, with + // the better slot dwelled, swaps through the staging buffer. + // synchronous copies + inline verify (copy_top_s style); both + // slots stay routed, only their device changes. + for (int g = 0; g + 1 < n_devices; g++) { + float worst_bound = INFINITY; + int worst_slot = -1; + for (int p = slot_start[g]; p < slot_end[g]; p++) { + if (ste[p] < 0) { + continue; + } + const float s = heatmap.get_score(il, ste[p]); + if (s < worst_bound) { + worst_bound = s; + worst_slot = p; + } + } + if (worst_slot < 0 || dc[worst_slot] < dwell) { + continue; + } + int best_slot = -1; + float best_score = -INFINITY; + for (int p = slot_start[g+1]; p < slot_end[g+1]; p++) { + if (ste[p] < 0) { + continue; + } + const float s = heatmap.get_score(il, ste[p]); + if (s > best_score) { + best_score = s; + best_slot = p; + } + } + if (best_slot < 0 || best_score < hyst * worst_bound) { + continue; + } + const int e_demote = ste[worst_slot]; + const int e_promote = ste[best_slot]; + for (entry * ent : entries_by_layer[il]) { + const size_t eslot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; + const size_t off_w = (size_t) (worst_slot - slot_start[g]) * eslot; + const size_t off_b = (size_t) (best_slot - slot_start[g+1]) * eslot; + std::vector s1(eslot), s2(eslot); + ggml_backend_tensor_get(ent->dst[g], s1.data(), off_w, eslot); // demote + ggml_backend_tensor_get(ent->dst[g+1], s2.data(), off_b, eslot); // promote + ggml_backend_tensor_set(ent->dst[g+1], s1.data(), off_b, eslot); + ggml_backend_tensor_set(ent->dst[g], s2.data(), off_w, eslot); + } + ste[worst_slot] = e_promote; + ste[best_slot] = e_demote; + dc[worst_slot] = -elapsed; + dc[best_slot] = -elapsed; + dirty[il] = 1; + changed++; + break; // one D2D swap per layer per tick + } + // ---- move-in (1/token, gated): fill a free slot with the hottest CPU // expert that should be on the GPU. check the free slot first (the // common blocker), then the move-in queue (rarer), then evaluate. @@ -857,6 +914,9 @@ bool llama_expert_hotstore::maybe_resync(const llama_expert_heatmap & heatmap, b if (multi_slot || heatmap.tokens_total <= 0) { return false; } + if (frozen) { + return false; + } // continuous adaptive cadence: the sync period grows with the hit rate // relative to the target. floor of 10 tokens (never resync more often), // stretching to 32 as the hit rate climbs toward 6x the target. diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index a97db31fc99..a318d19708d 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -98,6 +98,7 @@ struct llama_expert_hotstore { float hyst = 0.0f; // 0 = gate off (swap freely) int dwell = 0; // minimum syncs a resident must keep; 0 = off bool copy_mode = false; // keep the RAM copy of promoted experts (copy), else move + bool frozen = false; // sidecar loaded: store is pre-warmed, skip adaptation // max concurrent transfers in flight per layer, per direction (eviction // queue + promotion queue). higher = faster store adaptation, at the cost // of more slots temporarily in transition (not counted). @@ -160,6 +161,7 @@ llama_expert_hotstore(const llama_model * model, int n_layers, // returns true if any slot changed (caller should synchronize the GPU). bool resync_top_s(const llama_expert_heatmap & heatmap); + // LLAMA_EXPERT_FULL_SYNC: mirror the store to the top-S every token // (direct swaps, hash-verified, copy-on-read). no pacing queues. bool resync_full_mirror(const llama_expert_heatmap & heatmap, int budget = 1); From bfe48ad9ff0d24e8cf0587bf99d8de930dda693b Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 9 Aug 2026 19:18:18 +0300 Subject: [PATCH 47/61] expert tier: refine d2d swap gating and dwell units --- src/llama-expert-hotstore.cpp | 16 ++++++++++++---- 1 file changed, 12 insertions(+), 4 deletions(-) diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 75d28b98bd4..2c0db8300ec 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -808,8 +808,11 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { worst_slot = p; } } - if (worst_slot < 0 || dc[worst_slot] < dwell) { - continue; + if (worst_slot < 0 || worst_bound <= 0.0f) { + continue; // dead resident (no heat yet); eviction will clear it + } + if (dc[worst_slot] < dwell + 2) { + continue; // not aged enough since its last change } int best_slot = -1; float best_score = -INFINITY; @@ -840,10 +843,15 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { } ste[worst_slot] = e_promote; ste[best_slot] = e_demote; - dc[worst_slot] = -elapsed; - dc[best_slot] = -elapsed; + // dwell is in resyncs; the counter ages by elapsed tokens per resync + dc[worst_slot] = -elapsed * (dwell + 2); + dc[best_slot] = -elapsed * (dwell + 2); dirty[il] = 1; changed++; + if (getenv("LLAMA_EXPERT_DEBUG")) { + fprintf(stderr, "hotstore: d2d swap promote=%d demote=%d (dev %d -> %d) promote_s=%.2f worst=%.2f hyst=%.2f\n", + e_promote, e_demote, g+1, g, best_score, worst_bound, hyst * worst_bound); + } break; // one D2D swap per layer per tick } From 8e3407172ee38fe32494f0bcb63b53b7f90ffc78 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 9 Aug 2026 19:33:35 +0300 Subject: [PATCH 48/61] expert tier: autofit copy/move mode, d2d scratch vram offset --- common/fit.cpp | 4 +++- src/llama-expert-hotstore.cpp | 22 ++++++++++++++++++++++ 2 files changed, 25 insertions(+), 1 deletion(-) diff --git a/common/fit.cpp b/common/fit.cpp index 2390a102fec..6014975437d 100644 --- a/common/fit.cpp +++ b/common/fit.cpp @@ -813,7 +813,9 @@ static void common_params_fit_impl( // account for; subtract an 8 MiB per offloaded layer estimate so S // does not overshoot and OOM at graph capture. const int64_t vulkan_padding = is_vulkan ? int64_t(hp_ngl) * 8 * MiB : 0; - const int64_t moe_on_gpu = final_gpu_model - dense_model_gpu - vulkan_padding; + // D2D scratch: one largest-expert-slice buffer per device-pair + const int64_t d2d_scratch = nd > 1 ? int64_t(nd * nd) * (total_moe_bytes / (int64_t) hp_ngl / (int64_t) hp_nex) : 0; + const int64_t moe_on_gpu = final_gpu_model - dense_model_gpu - vulkan_padding - d2d_scratch; const int64_t s = moe_on_gpu > 0 ? int64_t(hp_nex) * moe_on_gpu / total_moe_bytes : 0; *n_expert_hot_s = s > 1 ? (int) (s - 1) : 0; } diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 2c0db8300ec..209bae7f1e3 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -13,6 +13,7 @@ #include #include #include +#include #ifdef _WIN32 #include @@ -104,6 +105,27 @@ llama_expert_hotstore::llama_expert_hotstore( entries_by_layer[e.layer_idx].push_back(&e); } + // auto copy/move: copy keeps the RAM copy of promoted experts (needs the + // full exps set resident); move frees it (RAM-tight). pick copy only when + // the exps comfortably fit in available RAM. + if (!copy_mode) { + int64_t exps_bytes = 0; + for (int il = 0; il < n_layers; il++) { + exps_bytes += bytes_per_slot[il]; + } + exps_bytes *= n_experts; // full exps set: per-slot bytes x experts per layer + const long page = sysconf(_SC_PAGESIZE); + const int64_t free_ram = (int64_t) sysconf(_SC_AVPHYS_PAGES) * page; + if (exps_bytes > 0 && free_ram > exps_bytes * 2) { + copy_mode = true; + fprintf(stderr, "hotstore: copy mode: exps (%d MiB) fit in RAM (%d MiB free)\n", + (int) (exps_bytes / (1024*1024)), (int) (free_ram / (1024*1024))); + } else if (exps_bytes > 0) { + fprintf(stderr, "hotstore: move mode: exps (%d MiB) need more RAM than free (%d MiB)\n", + (int) (exps_bytes / (1024*1024)), (int) (free_ram / (1024*1024))); + } + } + if (this->hot_s > 0) { slot_to_expert.assign(n_layers, std::vector(this->hot_s, -1)); dwell_count.assign(n_layers, std::vector(this->hot_s, 0)); From be76d2d02831bf542dad2fadc7d3eba4911af1e7 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 9 Aug 2026 20:05:54 +0300 Subject: [PATCH 49/61] expert tier: copy mode for mmap, host-pool d2d, autofit abort warning --- common/common.cpp | 5 +- common/fit.cpp | 4 +- src/llama-expert-hotstore.cpp | 94 ++++++++++++++++++++++++----------- 3 files changed, 69 insertions(+), 34 deletions(-) diff --git a/common/common.cpp b/common/common.cpp index 659cbaa86c0..133416feaf5 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1241,7 +1241,7 @@ common_init_result::common_init_result(common_params & params, bool model_only) COM_TRC("%s", "(for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on)\n"); int n_expert_hot_s = params.expert_hot_s; int * p_expert_hot_s = params.expert_hot_s == -1 ? &n_expert_hot_s : nullptr; - common_fit_params(params.model.path.c_str(), &mparams, &cparams, + const common_params_fit_status fit_status = common_fit_params(params.model.path.c_str(), &mparams, &cparams, params.tensor_split, params.tensor_buft_overrides.data(), params.fit_params_target.data(), @@ -1261,6 +1261,9 @@ common_init_result::common_init_result(common_params & params, bool model_only) break; } } + } else if (fit_status == COMMON_PARAMS_FIT_STATUS_FAILURE) { + LOG_WRN("%s: --expert-hot-s -1 autofit aborted (explicit -ngl/-ncmoe or fit error); expert cache is OFF\n", + __func__); } else { LOG_WRN("%s: --expert-hot-s -1 autofit found no free VRAM for expert slots; expert cache is OFF\n", __func__); diff --git a/common/fit.cpp b/common/fit.cpp index 6014975437d..2390a102fec 100644 --- a/common/fit.cpp +++ b/common/fit.cpp @@ -813,9 +813,7 @@ static void common_params_fit_impl( // account for; subtract an 8 MiB per offloaded layer estimate so S // does not overshoot and OOM at graph capture. const int64_t vulkan_padding = is_vulkan ? int64_t(hp_ngl) * 8 * MiB : 0; - // D2D scratch: one largest-expert-slice buffer per device-pair - const int64_t d2d_scratch = nd > 1 ? int64_t(nd * nd) * (total_moe_bytes / (int64_t) hp_ngl / (int64_t) hp_nex) : 0; - const int64_t moe_on_gpu = final_gpu_model - dense_model_gpu - vulkan_padding - d2d_scratch; + const int64_t moe_on_gpu = final_gpu_model - dense_model_gpu - vulkan_padding; const int64_t s = moe_on_gpu > 0 ? int64_t(hp_nex) * moe_on_gpu / total_moe_bytes : 0; *n_expert_hot_s = s > 1 ? (int) (s - 1) : 0; } diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 209bae7f1e3..4a5a099b51e 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -106,23 +106,46 @@ llama_expert_hotstore::llama_expert_hotstore( } // auto copy/move: copy keeps the RAM copy of promoted experts (needs the - // full exps set resident); move frees it (RAM-tight). pick copy only when - // the exps comfortably fit in available RAM. + // full exps set resident); move frees it (RAM-tight). mmap exps are + // file-backed page cache (kernel-reclaimable), so copy is always right + // there; the RAM check only matters on no-mmap (committed anonymous pool). if (!copy_mode) { - int64_t exps_bytes = 0; - for (int il = 0; il < n_layers; il++) { - exps_bytes += bytes_per_slot[il]; - } - exps_bytes *= n_experts; // full exps set: per-slot bytes x experts per layer - const long page = sysconf(_SC_PAGESIZE); - const int64_t free_ram = (int64_t) sysconf(_SC_AVPHYS_PAGES) * page; - if (exps_bytes > 0 && free_ram > exps_bytes * 2) { + const bool mmap_mode = !entries.empty() && llama_expert_preload::index_of(entries[0].src) < 0; + if (mmap_mode) { copy_mode = true; - fprintf(stderr, "hotstore: copy mode: exps (%d MiB) fit in RAM (%d MiB free)\n", - (int) (exps_bytes / (1024*1024)), (int) (free_ram / (1024*1024))); - } else if (exps_bytes > 0) { - fprintf(stderr, "hotstore: move mode: exps (%d MiB) need more RAM than free (%d MiB)\n", - (int) (exps_bytes / (1024*1024)), (int) (free_ram / (1024*1024))); + fprintf(stderr, "hotstore: copy mode (mmap: exps are file-backed page cache)\n"); + } else { + int64_t exps_bytes = 0; + for (int il = 0; il < n_layers; il++) { + exps_bytes += bytes_per_slot[il]; + } + exps_bytes *= n_experts; // full exps set: per-slot bytes x experts per layer + // available RAM: MemAvailable includes reclaimable page cache; + // _SC_AVPHYS_PAGES only counts truly-free pages and underreports + int64_t free_ram = 0; + FILE * f = fopen("/proc/meminfo", "r"); + if (f) { + char line[256]; + while (fgets(line, sizeof(line), f)) { + if (sscanf(line, "MemAvailable: %lld kB", &free_ram) == 1) { + free_ram *= 1024; + break; + } + } + fclose(f); + } + if (free_ram <= 0) { + const long page = sysconf(_SC_PAGESIZE); + free_ram = (int64_t) sysconf(_SC_AVPHYS_PAGES) * page; + } + if (exps_bytes > 0 && free_ram > exps_bytes * 2) { + copy_mode = true; + fprintf(stderr, "hotstore: copy mode: exps (%d MiB) fit in RAM (%d MiB free)\n", + (int) (exps_bytes / (1024*1024)), (int) (free_ram / (1024*1024))); + } else if (exps_bytes > 0) { + fprintf(stderr, "hotstore: move mode: exps (%d MiB) need more RAM than free (%d MiB)\n", + (int) (exps_bytes / (1024*1024)), (int) (free_ram / (1024*1024))); + } } } @@ -812,12 +835,9 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { } } // boundary gate - // ---- promote/demote (D2D): the top expert on a worse device that - // beats the better device's coldest resident by hysteresis, with - // the better slot dwelled, swaps through the staging buffer. - // synchronous copies + inline verify (copy_top_s style); both - // slots stay routed, only their device changes. - for (int g = 0; g + 1 < n_devices; g++) { + // ---- promote/demote (D2D): copy mode keeps RAM copies, so moves go + // through the host pool; D2D would double the bandwidth for nothing + for (int g = 0; g + 1 < n_devices && !copy_mode; g++) { float worst_bound = INFINITY; int worst_slot = -1; for (int p = slot_start[g]; p < slot_end[g]; p++) { @@ -854,14 +874,28 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { const int e_demote = ste[worst_slot]; const int e_promote = ste[best_slot]; for (entry * ent : entries_by_layer[il]) { + const int pidx = llama_expert_preload::index_of(ent->src); const size_t eslot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; const size_t off_w = (size_t) (worst_slot - slot_start[g]) * eslot; const size_t off_b = (size_t) (best_slot - slot_start[g+1]) * eslot; - std::vector s1(eslot), s2(eslot); - ggml_backend_tensor_get(ent->dst[g], s1.data(), off_w, eslot); // demote - ggml_backend_tensor_get(ent->dst[g+1], s2.data(), off_b, eslot); // promote - ggml_backend_tensor_set(ent->dst[g+1], s1.data(), off_b, eslot); - ggml_backend_tensor_set(ent->dst[g], s2.data(), off_w, eslot); + const uint8_t * src_demote = pidx >= 0 + ? llama_expert_preload::cpu_slice(pidx, e_demote) + : nullptr; + const uint8_t * src_promote = pidx >= 0 + ? llama_expert_preload::cpu_slice(pidx, e_promote) + : nullptr; + if (src_demote && src_promote) { + // no-mmap: both experts are already host-resident (the + // cold pool); write straight into the store, no GPU reads + ggml_backend_tensor_set(ent->dst[g+1], src_demote, off_b, eslot); + ggml_backend_tensor_set(ent->dst[g], src_promote, off_w, eslot); + } else { + std::vector s1(eslot), s2(eslot); + ggml_backend_tensor_get(ent->dst[g], s1.data(), off_w, eslot); // demote + ggml_backend_tensor_get(ent->dst[g+1], s2.data(), off_b, eslot); // promote + ggml_backend_tensor_set(ent->dst[g+1], s1.data(), off_b, eslot); + ggml_backend_tensor_set(ent->dst[g], s2.data(), off_w, eslot); + } } ste[worst_slot] = e_promote; ste[best_slot] = e_demote; @@ -947,11 +981,11 @@ bool llama_expert_hotstore::maybe_resync(const llama_expert_heatmap & heatmap, b if (frozen) { return false; } - // continuous adaptive cadence: the sync period grows with the hit rate - // relative to the target. floor of 10 tokens (never resync more often), - // stretching to 32 as the hit rate climbs toward 6x the target. + // adaptive cadence: floor 10 (5 in copy mode: host-pool moves are half + // the bandwidth), stretching to 32 as the hit rate climbs toward 6x target float ratio = hit_rate_valid ? hit_rate / target_hit_rate() : 0.0f; - const int eff_period = std::max(10, std::min(32, 10 + (int) (22.0f * (ratio - 1.0f) / 5.0f))); + const int floor = copy_mode ? 5 : 10; + const int eff_period = std::max(floor, std::min(32, floor + (int) (27.0f * (ratio - 1.0f) / 5.0f))); if (heatmap.tokens_total / eff_period > last_sync_tokens / eff_period) { if (getenv("LLAMA_EXPERT_FULL_SYNC")) { // test: mirror the whole store to the top-S on each sync instead of From 5097df0b160eafed61ab90e8b5ef29da6249da05 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Sun, 9 Aug 2026 20:11:10 +0300 Subject: [PATCH 50/61] expert tier: warm top 70% of cold experts by default --- src/llama-expert-pin.h | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/llama-expert-pin.h b/src/llama-expert-pin.h index 3df0a5116d5..77ced1ef342 100644 --- a/src/llama-expert-pin.h +++ b/src/llama-expert-pin.h @@ -15,7 +15,7 @@ namespace llama_expert_pin { int start_tokens = 128; // first pass at this many tokens float dontneed_gpu = 0.20f; // top fraction of GPU experts to drop float willneed_gpu = 0.20f; // bottom fraction of GPU experts to warm - float willneed_cold = 0.40f; // top fraction of cold experts to warm + float willneed_cold = 0.70f; // top fraction of cold experts to warm }; const config & get_config(); From 7c08c5944117336af6eb84f04d0bd97e0ee079c3 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 10 Aug 2026 01:32:04 +0300 Subject: [PATCH 51/61] sync with upstream --- .devops/rocm.Dockerfile | 1 - .github/workflows/build-cuda-ubuntu.yml | 1 - .github/workflows/build-cuda-windows.yml | 1 - .github/workflows/build-self-hosted.yml | 20 + .github/workflows/pr-draft-label.yml | 23 + .github/workflows/release.yml | 2 - ci/run.sh | 36 +- common/arg.cpp | 10 + common/common.h | 1 + conversion/__init__.py | 1 + conversion/deepseek.py | 7 + conversion/exaone.py | 4 +- docs/backend/SYCL.md | 42 + docs/ops.md | 12 +- docs/ops/SYCL.csv | 23541 +++++++++++++++- .../scripts/causal/convert-model.sh | 1 + .../scripts/embedding/convert-model.sh | 1 + examples/sycl/start-svr.sh | 21 +- examples/sycl/test.sh | 16 +- examples/sycl/win-start-svr.bat | 28 +- 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tools/ui/src/lib/enums/chat.enums.ts | 11 + tools/ui/src/lib/enums/index.ts | 4 +- .../lib/hooks/use-chat-form-pickers.svelte.ts | 355 + .../lib/hooks/use-debounced-search.svelte.ts | 67 + .../lib/hooks/use-models-selector.svelte.ts | 7 +- .../lib/hooks/use-picker-navigation.svelte.ts | 108 + .../lib/hooks/use-scroll-active-row.svelte.ts | 47 + tools/ui/src/lib/stores/models.svelte.ts | 23 +- tools/ui/src/lib/stores/settings.svelte.ts | 24 + tools/ui/src/lib/stores/tools.svelte.ts | 21 + tools/ui/src/lib/types/api.d.ts | 11 + tools/ui/src/lib/types/chat.d.ts | 26 +- tools/ui/src/lib/types/index.ts | 4 +- tools/ui/src/lib/types/mcp.d.ts | 1 + tools/ui/src/lib/types/settings.d.ts | 6 + tools/ui/src/lib/utils/code.ts | 50 + tools/ui/src/lib/utils/command-token.ts | 31 + .../lib/utils/contenteditable-tokenizer.ts | 890 + tools/ui/src/lib/utils/glob-search.ts | 151 + tools/ui/src/lib/utils/index.ts | 62 + tools/ui/src/lib/utils/mention-badge.ts | 86 + tools/ui/src/lib/utils/mention-token.ts | 73 + tools/ui/src/lib/utils/path-display.ts | 34 +- tools/ui/src/lib/utils/progress.ts | 6 +- tools/ui/src/lib/utils/source-history.ts | 48 + tools/ui/src/lib/utils/working-directory.ts | 50 +- tools/ui/src/routes/(chat)/+page.svelte | 25 +- .../src/routes/(chat)/chat/[id]/+page.svelte | 10 +- ...form-contenteditable-blocks.svelte.test.ts | 156 + ...t-form-contenteditable-undo.svelte.test.ts | 142 + .../chat-form-contenteditable.svelte.test.ts | 701 + .../chat-form-enter-code-block.svelte.test.ts | 112 + ...at-form-mention-picker-gate.svelte.test.ts | 64 + .../chat-form-slash-commands.svelte.test.ts | 122 + .../ChatFormContenteditableHarness.svelte | 27 + .../components/ChatFormPickersHarness.svelte | 51 + .../components/ChatFormTestWrapper.svelte | 12 + .../components/PickerListScrollHarness.svelte | 43 + .../client/picker-list-scroll.svelte.test.ts | 29 + ...settings-raw-text-migration.svelte.test.ts | 65 + tools/ui/tests/unit/code.test.ts | 37 +- tools/ui/tests/unit/command-token.test.ts | 51 + .../unit/contenteditable-tokenizer.test.ts | 205 + .../unit/contenteditable-word-jump.test.ts | 80 + .../tests/unit/glob-search-children.test.ts | 119 + tools/ui/tests/unit/mention-badge.test.ts | 174 + tools/ui/tests/unit/mention-token.test.ts | 64 + tools/ui/tests/unit/source-history.test.ts | 65 + tools/ui/tests/unit/working-directory.test.ts | 40 + 165 files changed, 33033 insertions(+), 2003 deletions(-) create mode 100644 .github/workflows/pr-draft-label.yml create mode 100644 ggml/src/ggml-sycl/dsv4-hc.cpp create mode 100644 ggml/src/ggml-sycl/dsv4-hc.hpp create mode 100644 ggml/src/ggml-sycl/lightning-indexer.cpp create mode 100644 ggml/src/ggml-sycl/lightning-indexer.hpp create mode 100644 tools/ui/src/lib/components/app/chat/ChatForm/ChatFormContenteditable.svelte create mode 100644 tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormCommandPicker.svelte create mode 100644 tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormMentionPicker.svelte delete mode 100644 tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPickerMcpResources.svelte create mode 100644 tools/ui/src/lib/components/app/content/MarkdownContent/plugins/rehype/file-badge.ts create mode 100644 tools/ui/src/lib/components/app/forms/HighlightedMatch.svelte create mode 100644 tools/ui/src/lib/constants/chat-commands.ts create mode 100644 tools/ui/src/lib/constants/mention-badge.ts create mode 100644 tools/ui/src/lib/hooks/use-chat-form-pickers.svelte.ts create mode 100644 tools/ui/src/lib/hooks/use-debounced-search.svelte.ts create mode 100644 tools/ui/src/lib/hooks/use-picker-navigation.svelte.ts create mode 100644 tools/ui/src/lib/hooks/use-scroll-active-row.svelte.ts create mode 100644 tools/ui/src/lib/utils/command-token.ts create mode 100644 tools/ui/src/lib/utils/contenteditable-tokenizer.ts create mode 100644 tools/ui/src/lib/utils/glob-search.ts create mode 100644 tools/ui/src/lib/utils/mention-badge.ts create mode 100644 tools/ui/src/lib/utils/mention-token.ts create mode 100644 tools/ui/src/lib/utils/source-history.ts create mode 100644 tools/ui/tests/client/chat-form-contenteditable-blocks.svelte.test.ts create mode 100644 tools/ui/tests/client/chat-form-contenteditable-undo.svelte.test.ts create mode 100644 tools/ui/tests/client/chat-form-contenteditable.svelte.test.ts create mode 100644 tools/ui/tests/client/chat-form-enter-code-block.svelte.test.ts create mode 100644 tools/ui/tests/client/chat-form-mention-picker-gate.svelte.test.ts create mode 100644 tools/ui/tests/client/chat-form-slash-commands.svelte.test.ts create mode 100644 tools/ui/tests/client/components/ChatFormContenteditableHarness.svelte create mode 100644 tools/ui/tests/client/components/ChatFormPickersHarness.svelte create mode 100644 tools/ui/tests/client/components/ChatFormTestWrapper.svelte create mode 100644 tools/ui/tests/client/components/PickerListScrollHarness.svelte create mode 100644 tools/ui/tests/client/picker-list-scroll.svelte.test.ts create mode 100644 tools/ui/tests/client/settings-raw-text-migration.svelte.test.ts create mode 100644 tools/ui/tests/unit/command-token.test.ts create mode 100644 tools/ui/tests/unit/contenteditable-tokenizer.test.ts create mode 100644 tools/ui/tests/unit/contenteditable-word-jump.test.ts create mode 100644 tools/ui/tests/unit/glob-search-children.test.ts create mode 100644 tools/ui/tests/unit/mention-badge.test.ts create mode 100644 tools/ui/tests/unit/mention-token.test.ts create mode 100644 tools/ui/tests/unit/source-history.test.ts diff --git a/.devops/rocm.Dockerfile b/.devops/rocm.Dockerfile index a8bc4e1fcd6..20f6ad63608 100644 --- a/.devops/rocm.Dockerfile +++ b/.devops/rocm.Dockerfile @@ -57,7 +57,6 @@ COPY --from=web /app/tools/ui/dist tools/ui/dist RUN HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -R)" \ cmake -S . -B build \ -DGGML_HIP=ON \ - -DGGML_HIP_ROCWMMA_FATTN=ON \ -DAMDGPU_TARGETS="$ROCM_DOCKER_ARCH" \ -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON \ -DCMAKE_BUILD_TYPE=Release -DLLAMA_BUILD_TESTS=OFF \ diff --git a/.github/workflows/build-cuda-ubuntu.yml b/.github/workflows/build-cuda-ubuntu.yml index 6271b22cbd2..2528b18573a 100644 --- a/.github/workflows/build-cuda-ubuntu.yml +++ b/.github/workflows/build-cuda-ubuntu.yml @@ -99,7 +99,6 @@ jobs: run: | cmake -B build -S . \ -DCMAKE_HIP_COMPILER="$(hipconfig -l)/clang" \ - -DGGML_HIP_ROCWMMA_FATTN=ON \ -DGPU_TARGETS="gfx1030" \ -DGGML_HIP=ON cmake --build build --config Release -j $(nproc) diff --git a/.github/workflows/build-cuda-windows.yml b/.github/workflows/build-cuda-windows.yml index e9e941421b6..367a3a8546c 100644 --- a/.github/workflows/build-cuda-windows.yml +++ b/.github/workflows/build-cuda-windows.yml @@ -150,7 +150,6 @@ jobs: -DLLAMA_BUILD_BORINGSSL=ON ` -DROCM_DIR="${env:HIP_PATH}" ` -DGGML_HIP=ON ` - -DGGML_HIP_ROCWMMA_FATTN=ON ` -DGPU_TARGETS="gfx1100" ` -DGGML_RPC=ON cmake --build build -j ${env:NUMBER_OF_PROCESSORS} diff --git a/.github/workflows/build-self-hosted.yml b/.github/workflows/build-self-hosted.yml index 441a897e502..0ef202193c7 100644 --- a/.github/workflows/build-self-hosted.yml +++ b/.github/workflows/build-self-hosted.yml @@ -71,6 +71,26 @@ jobs: nvidia-smi GG_BUILD_CUDA=1 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp + gpu-rocm: + runs-on: [self-hosted, Linux, AMD] + + steps: + - name: Clone + id: checkout + uses: actions/checkout@v6 + + - name: Test + id: ggml-ci + # HIP_LAUNCH_BLOCKING=1: workaround for an async-execution correctness + # issue on integrated RDNA3.5 (gfx1151) where batched inference returns + # incorrect output (perplexity ~88 vs ~9.4). Serializing kernel launches + # restores correctness. Remove once the underlying ROCm/HIP issue is fixed. + env: + HIP_LAUNCH_BLOCKING: "1" + run: | + rocminfo + GG_BUILD_ROCM=1 GG_BUILD_AMDGPU_TARGETS=gfx1151 bash ./ci/run.sh ~/results/llama.cpp ~/mnt/llama.cpp + gpu-vulkan-nvidia-cm: runs-on: [self-hosted, Linux, NVIDIA] diff --git a/.github/workflows/pr-draft-label.yml b/.github/workflows/pr-draft-label.yml new file mode 100644 index 00000000000..d2594c823d7 --- /dev/null +++ b/.github/workflows/pr-draft-label.yml @@ -0,0 +1,23 @@ +name: Convert PR to draft + +on: + pull_request_target: + types: [labeled] + +permissions: + pull-requests: write + issues: write + contents: write # required for "gh pr ready" command, see https://github.com/cli/cli/issues/8910 + +jobs: + convert-to-draft: + if: github.event.label.name == 'draft' && github.event.pull_request.draft == false + runs-on: ubuntu-slim + steps: + - name: Convert PR to draft + env: + GH_TOKEN: ${{ secrets.GITHUB_TOKEN }} + PR_URL: ${{ github.event.pull_request.html_url }} + run: | + gh pr ready --undo "$PR_URL" + gh pr edit "$PR_URL" --remove-label draft diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml index f587ed93c52..968d2d4b7e4 100644 --- a/.github/workflows/release.yml +++ b/.github/workflows/release.yml @@ -1229,7 +1229,6 @@ jobs: -DGPU_TARGETS="${{ matrix.gpu_targets }}" \ -DGGML_HIP=ON \ -DHIP_PLATFORM=amd \ - -DGGML_HIP_ROCWMMA_FATTN=ON \ -DHF_UI_VERSION=${{ needs.get-version.outputs.ui_version }} \ ${{ env.CMAKE_ARGS }} cmake --build build --config Release -j $(nproc) @@ -1353,7 +1352,6 @@ jobs: -DGGML_NATIVE=OFF ` -DGGML_CPU=OFF ` -DGPU_TARGETS="${{ matrix.gpu_targets }}" ` - -DGGML_HIP_ROCWMMA_FATTN=ON ` -DGGML_HIP=ON ` -DHF_UI_VERSION=${{ needs.get-version.outputs.ui_version }} ` -DLLAMA_BUILD_BORINGSSL=ON diff --git a/ci/run.sh b/ci/run.sh index e4a34ff0acd..f6c7eb0d5c7 100755 --- a/ci/run.sh +++ b/ci/run.sh @@ -10,6 +10,9 @@ # # with CUDA support # GG_BUILD_CUDA=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt # +# # with ROCm support +# GG_BUILD_ROCM=1 GG_BUILD_AMDGPU_TARGETS=gfx1151 bash ./ci/run.sh ./tmp/results ./tmp/mnt +# # # with SYCL support # GG_BUILD_SYCL=1 bash ./ci/run.sh ./tmp/results ./tmp/mnt # @@ -89,7 +92,7 @@ if [ ! -z ${GG_BUILD_CUDA} ]; then fi if [ ! -z ${GG_BUILD_ROCM} ]; then - CMAKE_EXTRA="${CMAKE_EXTRA} -DGGML_HIP=ON" + CMAKE_EXTRA="${CMAKE_EXTRA} -DCMAKE_HIP_COMPILER=$(hipconfig -l)/clang -DGGML_HIP=ON" if [ -z ${GG_BUILD_AMDGPU_TARGETS} ]; then echo "Missing GG_BUILD_AMDGPU_TARGETS, please set it to your GPU architecture (e.g. gfx90a, gfx1100, etc.)" exit 1 @@ -640,39 +643,52 @@ function gg_sum_rerank_tiny { function gg_check_build_requirements { if ! command -v git &> /dev/null; then - gg_printf 'git not found, please install' + gg_printf 'git not found, please install\n' + exit 1 fi if ! command -v git-lfs &> /dev/null; then - gg_printf 'git-lfs not found, please install' + gg_printf 'git-lfs not found, please install\n' + exit 1 + fi + + if ! git config --get filter.lfs.clean &> /dev/null; then + gg_printf 'git-lfs not initialized, please run `git lfs install`\n' + exit 1 fi if ! command -v wget &> /dev/null; then - gg_printf 'wget not found, please install' + gg_printf 'wget not found, please install\n' + exit 1 fi if ! command -v python3 &> /dev/null; then - gg_printf 'python3 not found, please install' + gg_printf 'python3 not found, please install\n' + exit 1 fi if ! command -v pip3 &> /dev/null; then - gg_printf 'pip3 not found, please install' + gg_printf 'pip3 not found, please install\n' + exit 1 fi if ! python3 -m ensurepip --help &> /dev/null; then - gg_printf 'ensurepip not found, please install python3-venv package' + gg_printf 'ensurepip not found, please install python3-venv package\n' + exit 1 fi if ! command -v cmake &> /dev/null; then - gg_printf 'cmake not found, please install' + gg_printf 'cmake not found, please install\n' + exit 1 fi if ! command -v ccache &> /dev/null; then - gg_printf 'ccache not found, please consider installing for faster builds' + gg_printf 'ccache not found, please consider installing for faster builds\n' fi if ! command -v ctest &> /dev/null; then - gg_printf 'ctest not found, please install' + gg_printf 'ctest not found, please install\n' + exit 1 fi } diff --git a/common/arg.cpp b/common/arg.cpp index 9cb170e6d89..67ec8a6550e 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -3402,6 +3402,16 @@ common_params_context common_params_parser_init(common_params & params, llama_ex params.server_tools = parse_csv_row(value); } ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_TOOLS")); + add_opt(common_arg( + {"--tools-runtime"}, "OPTION", + "experimental: run tools in a separate runtime environment (default: none, use host environment)\n" + "available options:\n" + " 'docker:': spin up a new Docker container and reuse it for all invocations, clean up on server exit\n" + " 'docker-container:': use an existing Docker container by ID, won't stop on server exit\n", + [](common_params & params, const std::string & value) { + params.server_tools_runtime = value; + } + ).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_TOOLS_RUNTIME")); add_opt(common_arg( {"--mcp-servers-config"}, "PATH", "experimental: path to JSON file with MCP server definitions (Cursor-compatible format) - do not enable in untrusted environments (default: none)\n" diff --git a/common/common.h b/common/common.h index c60b839edbd..d33ef2001ec 100644 --- a/common/common.h +++ b/common/common.h @@ -665,6 +665,7 @@ struct common_params { // enable built-in tools std::vector server_tools; + std::string server_tools_runtime; // MCP server configs (Cursor-compatible JSON) std::string mcp_servers_config; // path to JSON file with MCP server definitions diff --git a/conversion/__init__.py b/conversion/__init__.py index 06c2c50ad24..1f781a7903a 100644 --- a/conversion/__init__.py +++ b/conversion/__init__.py @@ -70,6 +70,7 @@ "Exaone4ForCausalLM": "exaone", "ExaoneForCausalLM": "exaone", "ExaoneMoEForCausalLM": "exaone", + "ExaoneMoeForCausalLM": "exaone", "FalconForCausalLM": "falcon", "FalconH1ForCausalLM": "falcon_h1", "FalconMambaForCausalLM": "mamba", diff --git a/conversion/deepseek.py b/conversion/deepseek.py index 3dca369cf9f..1846ca4010e 100644 --- a/conversion/deepseek.py +++ b/conversion/deepseek.py @@ -533,6 +533,13 @@ def __init__(self, *args, **kwargs): for key, value in raw_hparams.items(): self.hparams.setdefault(key, value) + # workaround for special rope_parameters (main/compress) in transformers 5.x + if self.rope_parameters.get("full_attention", self.rope_parameters).get("rope_type") is None: + if (rope_scaling := raw_hparams.get("rope_scaling")) is not None: + if "rope_type" not in rope_scaling and (rope_type := rope_scaling.get("type")) is not None: + rope_scaling["rope_type"] = rope_type + self.rope_parameters.update(**rope_scaling) + self.block_count = self.hparams["num_hidden_layers"] if self.mtp_only: self.block_count += self.hparams.get("num_nextn_predict_layers", 0) diff --git a/conversion/exaone.py b/conversion/exaone.py index bc4fb3f1b17..1cd2244dbc3 100644 --- a/conversion/exaone.py +++ b/conversion/exaone.py @@ -123,7 +123,9 @@ def generate_extra_tensors(self) -> Iterable[tuple[str, Tensor]]: yield (self.format_tensor_name(gguf.MODEL_TENSOR.ROPE_FREQS), torch.tensor(rope_factors, dtype=torch.float32)) -@ModelBase.register("ExaoneMoEForCausalLM") +# note: transformers >= 5.1 renamed the class to "ExaoneMoeForCausalLM" (lowercase 'e'), +# so accept both spellings - LG AI have updated the configs of already-released models +@ModelBase.register("ExaoneMoEForCausalLM", "ExaoneMoeForCausalLM") class ExaoneMoEModel(Exaone4Model): model_arch = gguf.MODEL_ARCH.EXAONE_MOE diff --git a/docs/backend/SYCL.md b/docs/backend/SYCL.md index 814e541e1a1..73f89a70632 100644 --- a/docs/backend/SYCL.md +++ b/docs/backend/SYCL.md @@ -449,6 +449,8 @@ Or use 1 SYCL GPUs: [0] with Max compute units:512 ``` +User can use the device management in [docs/multi-gpu.md](https://github.com/ggml-org/llama.cpp/blob/master/docs/multi-gpu.md), like parameter `--device SYCL0,SYCL1` to assign one or more devices. + ## Windows ### Install GPU driver @@ -763,6 +765,7 @@ Or use 1 SYCL GPUs: [0] with Max compute units:512 ``` +User can use the device management in [docs/multi-gpu.md](https://github.com/ggml-org/llama.cpp/blob/master/docs/multi-gpu.md), like parameter `--device SYCL0,SYCL1` to assign one or more devices. ## Environment Variable @@ -895,6 +898,45 @@ Pass these via `CXXFLAGS` or add a one-off `#define` to enable a flag on the spo set UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS=1 ``` +- When I set `SYCL_CACHE_PERSISTENT=1` in running time, I meet crash. + + `SYCL_CACHE_PERSISTENT=1` is not recommended by llama.cpp SYCL backend. + When cache is enabled, SYCL runtime will try to cache and reuse JIT-compiled binaries. + + We find some AI will tell user this cmd to speed up SYCL backend. It only speeds up the startup to skip the JIT process, instead of running speed. + + It will bring negative impact when the SYCL binary file is changed frequently in your running environment. The new & old codes mix will lead to crash. + + Compare to the benefit, it has brought more failed cases. + If you are not familiar with the SYCL compiler principle of JIT and AOT, please don't use it. + + To restore, you need to remove the local cache: `~/.cache/libsycl_cache/` and execute `unset SYCL_CACHE_PERSISTENT` in running time. + +- How to use iGPU and dGPU in same time? + + 1. Detect the devices in your running time. + ``` + source /opt/intel/oneapi/setvars.sh + ./build/bin/llama-server --list-devices + + or + ./build/bin/llama-cli --list-devices + ./build/bin/llama-bench --list-devices + ./build/bin/llama-completion --list-devices + + Available devices: + SYCL0: Intel(R) Arc(TM) A770 Graphics (15473 MiB, 15473 MiB free) + SYCL1: Intel(R) UHD Graphics 770 (59675 MiB, 44986 MiB free) + ``` + + The dGPU will be in the head of this list and iGPU will be the end. + If not all GPUs are listed, please check the env var: ONEAPI_DEVICE_SELECTOR and unset it. + + 2. Set the iGPU and dGPU + + Set the iGPU and dGPU by `./build/bin/llama-server --device SYCL0,SYCL1,SYCLxxx`. + + ### **GitHub contribution**: Please add the `[SYCL]` prefix/tag in issues/PRs titles to help the SYCL contributors to check/address them without delay. diff --git a/docs/ops.md b/docs/ops.md index 71bd72011ea..0c1ced9aa65 100644 --- a/docs/ops.md +++ b/docs/ops.md @@ -15,7 +15,7 @@ Legend: | Operation | BLAS | CANN | CPU | CUDA | ET | MTL | OpenCL | SYCL | Vulkan | WebGPU | ZenDNN | zDNN | |-----------|------|------|------|------|------|------|------|------|------|------|------|------| | ABS | ❌ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | -| ACC | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ❌ | 🟡 | ✅ | ❌ | ❌ | ❌ | +| ACC | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | | ADD | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | | ADD1 | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | | ADD_ID | ❌ | ❌ | ✅ | ✅ | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | @@ -41,9 +41,9 @@ Legend: | DIAG | ❌ | ❌ | ✅ | ✅ | 🟡 | ✅ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | | DIAG_MASK_INF | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ | | DIV | ❌ | ✅ | ✅ | ✅ | ❌ | 🟡 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | -| DSV4_HC_COMB | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | -| DSV4_HC_POST | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | -| DSV4_HC_PRE | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | +| DSV4_HC_COMB | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | +| DSV4_HC_POST | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | +| DSV4_HC_PRE | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | | DUP | ❌ | ✅ | ✅ | 🟡 | ❌ | 🟡 | 🟡 | ✅ | ✅ | ❌ | ❌ | ❌ | | ELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | | EXP | ❌ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | @@ -59,7 +59,7 @@ Legend: | GELU | ❌ | ✅ | ✅ | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ✅ | ✅ | ❌ | ❌ | | GELU_ERF | ❌ | ✅ | ✅ | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ✅ | ✅ | ❌ | ❌ | | GELU_QUICK | ❌ | ✅ | ✅ | 🟡 | 🟡 | ✅ | 🟡 | ✅ | ✅ | ✅ | ❌ | ❌ | -| GET_ROWS | ❌ | 🟡 | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | ✅ | ✅ | 🟡 | ❌ | ❌ | +| GET_ROWS | ❌ | 🟡 | ✅ | 🟡 | 🟡 | 🟡 | 🟡 | 🟡 | ✅ | 🟡 | ❌ | ❌ | | GET_ROWS_BACK | ❌ | ❌ | 🟡 | 🟡 | ❌ | ❌ | ❌ | ❌ | 🟡 | ❌ | ❌ | ❌ | | GROUP_NORM | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | | HARDSIGMOID | ❌ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | @@ -68,7 +68,7 @@ Legend: | IM2COL_3D | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | | L2_NORM | ❌ | ✅ | ✅ | ✅ | 🟡 | ✅ | ❌ | ✅ | ✅ | 🟡 | ❌ | ❌ | | LEAKY_RELU | ❌ | ✅ | ✅ | ✅ | ❌ | 🟡 | ❌ | ✅ | ✅ | ❌ | ❌ | ❌ | -| LIGHTNING_INDEXER | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | +| LIGHTNING_INDEXER | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | | LOG | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | ❌ | ✅ | ✅ | ✅ | ❌ | ❌ | | MEAN | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | | MUL | ❌ | ✅ | ✅ | ✅ | 🟡 | 🟡 | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | diff --git a/docs/ops/SYCL.csv b/docs/ops/SYCL.csv index b563e76a876..b5a95c69ab7 100644 --- a/docs/ops/SYCL.csv +++ b/docs/ops/SYCL.csv @@ -167,6 +167,18 @@ "SYCL0","ROUND","type=f32,ne_a=[5,7,11,13],v=1","support","1","yes","SYCL" "SYCL0","TRUNC","type=f32,ne_a=[128,2,2,2],v=1","support","1","yes","SYCL" "SYCL0","TRUNC","type=f32,ne_a=[5,7,11,13],v=1","support","1","yes","SYCL" +"SYCL0","DSV4_HC_COMB","n_tokens=1,n_iter=1,eps=0.000001","support","1","yes","SYCL" +"SYCL0","DSV4_HC_COMB","n_tokens=17,n_iter=4,eps=0.000001","support","1","yes","SYCL" +"SYCL0","DSV4_HC_COMB","n_tokens=257,n_iter=8,eps=0.000001","support","1","yes","SYCL" +"SYCL0","DSV4_HC_COMB","n_tokens=17,n_iter=20,eps=0.000001","support","1","yes","SYCL" +"SYCL0","DSV4_HC_PRE","n_embd=1,n_tokens=1","support","1","yes","SYCL" +"SYCL0","DSV4_HC_PRE","n_embd=31,n_tokens=17","support","1","yes","SYCL" +"SYCL0","DSV4_HC_PRE","n_embd=128,n_tokens=257","support","1","yes","SYCL" +"SYCL0","DSV4_HC_PRE","n_embd=4096,n_tokens=21","support","1","yes","SYCL" +"SYCL0","DSV4_HC_POST","n_embd=1,n_tokens=1","support","1","yes","SYCL" +"SYCL0","DSV4_HC_POST","n_embd=31,n_tokens=17","support","1","yes","SYCL" +"SYCL0","DSV4_HC_POST","n_embd=128,n_tokens=257","support","1","yes","SYCL" +"SYCL0","DSV4_HC_POST","n_embd=4096,n_tokens=21","support","1","yes","SYCL" "SYCL0","REGLU","type=f16,ne_a=[128,2,2,2],v=0,swapped=0","support","1","yes","SYCL" "SYCL0","REGLU","type=f16,ne_a=[5,7,11,13],v=0,swapped=0","support","1","yes","SYCL" "SYCL0","REGLU","type=f16,ne_a=[128,2,2,2],v=0,swapped=1","support","1","yes","SYCL" @@ -338,6 +350,10 @@ "SYCL0","GET_ROWS","type=q1_0,n=256,m=5,r=4,be1=1,be2=1,v=1","support","1","yes","SYCL" "SYCL0","GET_ROWS","type=q1_0,n=256,m=5,r=4,be1=7,be2=1,v=0","support","1","yes","SYCL" "SYCL0","GET_ROWS","type=q1_0,n=256,m=5,r=4,be1=7,be2=1,v=1","support","1","yes","SYCL" +"SYCL0","GET_ROWS","type=q2_0,n=256,m=5,r=4,be1=1,be2=1,v=0","support","0","no","SYCL" +"SYCL0","GET_ROWS","type=q2_0,n=256,m=5,r=4,be1=1,be2=1,v=1","support","0","no","SYCL" +"SYCL0","GET_ROWS","type=q2_0,n=256,m=5,r=4,be1=7,be2=1,v=0","support","0","no","SYCL" +"SYCL0","GET_ROWS","type=q2_0,n=256,m=5,r=4,be1=7,be2=1,v=1","support","0","no","SYCL" "SYCL0","GET_ROWS","type=mxfp4,n=256,m=5,r=4,be1=1,be2=1,v=0","support","1","yes","SYCL" "SYCL0","GET_ROWS","type=mxfp4,n=256,m=5,r=4,be1=1,be2=1,v=1","support","1","yes","SYCL" "SYCL0","GET_ROWS","type=mxfp4,n=256,m=5,r=4,be1=7,be2=1,v=0","support","1","yes","SYCL" @@ -426,6 +442,8 @@ "SYCL0","GET_ROWS_BACK","type=q8_0,n=256,m=5,r=4,b=1,v=1","support","0","no","SYCL" "SYCL0","GET_ROWS_BACK","type=q1_0,n=256,m=5,r=4,b=1,v=0","support","0","no","SYCL" "SYCL0","GET_ROWS_BACK","type=q1_0,n=256,m=5,r=4,b=1,v=1","support","0","no","SYCL" +"SYCL0","GET_ROWS_BACK","type=q2_0,n=256,m=5,r=4,b=1,v=0","support","0","no","SYCL" +"SYCL0","GET_ROWS_BACK","type=q2_0,n=256,m=5,r=4,b=1,v=1","support","0","no","SYCL" "SYCL0","GET_ROWS_BACK","type=mxfp4,n=256,m=5,r=4,b=1,v=0","support","0","no","SYCL" "SYCL0","GET_ROWS_BACK","type=mxfp4,n=256,m=5,r=4,b=1,v=1","support","0","no","SYCL" "SYCL0","GET_ROWS_BACK","type=nvfp4,n=256,m=5,r=4,b=1,v=0","support","0","no","SYCL" @@ -460,333 +478,685 @@ "SYCL0","GET_ROWS_BACK","type=iq4_xs,n=256,m=5,r=4,b=1,v=1","support","0","no","SYCL" "SYCL0","GET_ROWS_BACK","type=i32,n=256,m=5,r=4,b=1,v=0","support","0","no","SYCL" "SYCL0","GET_ROWS_BACK","type=i32,n=256,m=5,r=4,b=1,v=1","support","0","no","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[1,8,1,3],nr23=[1,1],r=2,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i32,ne=[1,8,1,3],nr23=[1,1],r=2,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=q8_0,type_idx=i32,ne=[256,5,1,3],nr23=[1,1],r=1,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[256,5,1,3],nr23=[1,1],r=1,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[256,11,1,1],nr23=[2,3],r=7,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[3,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[31,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[33,5,1,1],nr23=[2,3],r=1,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[256,5,1,3],nr23=[1,1],r=1,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[256,11,1,1],nr23=[2,3],r=7,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[3,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[31,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[33,5,1,1],nr23=[2,3],r=1,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[256,5,7,3],nr23=[1,1],r=1,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[256,11,1,7],nr23=[2,3],r=7,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[3,3,7,1],nr23=[2,3],r=2,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[31,3,7,1],nr23=[2,3],r=2,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[33,5,1,7],nr23=[2,3],r=1,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[256,5,7,3],nr23=[1,1],r=1,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[256,11,1,7],nr23=[2,3],r=7,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[3,3,7,1],nr23=[2,3],r=2,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[31,3,7,1],nr23=[2,3],r=2,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f32,type_idx=i64,ne=[33,5,1,7],nr23=[2,3],r=1,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f16,type_idx=i64,ne=[256,5,1,3],nr23=[1,1],r=1,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f16,type_idx=i64,ne=[256,11,1,1],nr23=[2,3],r=7,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f16,type_idx=i64,ne=[3,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f16,type_idx=i64,ne=[31,3,1,1],nr23=[2,3],r=2,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f16,type_idx=i64,ne=[33,5,1,1],nr23=[2,3],r=1,v=0","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f16,type_idx=i64,ne=[256,5,1,3],nr23=[1,1],r=1,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f16,type_idx=i64,ne=[256,11,1,1],nr23=[2,3],r=7,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f16,type_idx=i64,ne=[3,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f16,type_idx=i64,ne=[31,3,1,1],nr23=[2,3],r=2,v=1","support","1","yes","SYCL" -"SYCL0","SET_ROWS","type=f16,type_idx=i64,ne=[33,5,1,1],nr23=[2,3],r=1,v=1","support","1","yes","SYCL" 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"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=1,s0=2,p0=0","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=1,s0=2,p0=0","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=1,s0=2,p0=1","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=1,s0=2,p0=1","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=1,s0=2,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=1,s0=2,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=1,s0=2,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=1,s0=2,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=1,s0=2,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=1,s0=2,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=1,s0=2,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=1,s0=3,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=1,s0=3,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=1,s0=3,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=1,s0=3,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=1,s0=3,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=1,s0=3,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=1,s0=3,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=1,s0=3,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=1,s0=3,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=1,s0=3,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=1,s0=3,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=1,s0=3,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=2,s0=1,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=2,s0=1,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=2,s0=1,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=2,s0=1,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=2,s0=1,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=2,s0=1,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=2,s0=1,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=2,s0=1,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=2,s0=1,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=2,s0=1,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=2,s0=1,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=2,s0=1,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=2,s0=2,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=2,s0=2,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=2,s0=2,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=2,s0=2,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=2,s0=2,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=2,s0=2,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=2,s0=2,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=2,s0=2,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=2,s0=2,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=2,s0=2,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=2,s0=2,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=2,s0=2,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=2,s0=3,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=2,s0=3,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=2,s0=3,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=2,s0=3,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=2,s0=3,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=2,s0=3,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=2,s0=3,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=2,s0=3,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=2,s0=3,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=2,s0=3,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=2,s0=3,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=2,s0=3,p0=3","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=3,s0=1,p0=0","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=3,s0=1,p0=0","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=3,s0=1,p0=0","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=3,s0=1,p0=1","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=3,s0=1,p0=1","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=3,s0=1,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=3,s0=1,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=3,s0=1,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=3,s0=1,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=3,s0=1,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=3,s0=1,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=3,s0=1,p0=3","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=3,s0=2,p0=0","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=3,s0=2,p0=0","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=3,s0=2,p0=0","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=3,s0=2,p0=1","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=3,s0=2,p0=1","support","1","yes","SYCL" "SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=3,s0=2,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=3,s0=2,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=3,s0=2,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=3,s0=2,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=3,s0=2,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=3,s0=2,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=3,s0=2,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=3,s0=3,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=3,s0=3,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=3,s0=3,p0=0","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=3,s0=3,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=3,s0=3,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=3,s0=3,p0=1","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=3,s0=3,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=3,s0=3,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=3,s0=3,p0=2","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[10,3,2,1],k0=3,s0=3,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[11,1,3,2],k0=3,s0=3,p0=3","support","1","yes","SYCL" +"SYCL0","POOL_1D","pool_type=max,type_input=f32,ne_input=[128,2,1,3],k0=3,s0=3,p0=3","support","1","yes","SYCL" "SYCL0","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[3000,128,1,1],ne_kernel=[3,128,1280,1],s0=1,s1=0,p0=1,p1=0,d0=1,d1=0,is_2D=0","support","1","yes","SYCL" "SYCL0","IM2COL","type_input=f32,type_kernel=f16,dst_type=f32,ne_input=[3000,128,1,1],ne_kernel=[3,128,1280,1],s0=1,s1=0,p0=1,p1=0,d0=1,d1=0,is_2D=0","support","1","yes","SYCL" "SYCL0","IM2COL","type_input=f32,type_kernel=f16,dst_type=f16,ne_input=[3000,128,1,1],ne_kernel=[3,128,1280,1],s0=1,s1=0,p0=1,p1=0,d0=1,d1=0,is_2D=0","support","1","yes","SYCL" @@ -976,6 +1514,7 @@ "SYCL0","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,2,2,1],ne_kernel=[3,2,2,1],s0=3,s1=0,p0=3,p1=0,d0=1,d1=0,is_2D=0","support","1","yes","SYCL" "SYCL0","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,2,2,1],ne_kernel=[3,2,2,1],s0=3,s1=0,p0=3,p1=0,d0=3,d1=0,is_2D=0","support","1","yes","SYCL" "SYCL0","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[10,10,3,1],ne_kernel=[3,3,3,1],s0=1,s1=1,p0=1,p1=1,d0=1,d1=1,is_2D=1","support","1","yes","SYCL" +"SYCL0","IM2COL","type_input=f32,type_kernel=f32,dst_type=f16,ne_input=[10,10,3,1],ne_kernel=[3,3,3,1],s0=1,s1=1,p0=1,p1=1,d0=1,d1=1,is_2D=1","support","1","yes","SYCL" "SYCL0","IM2COL","type_input=f32,type_kernel=f16,dst_type=f32,ne_input=[10,10,3,1],ne_kernel=[3,3,3,1],s0=1,s1=1,p0=1,p1=1,d0=1,d1=1,is_2D=1","support","1","yes","SYCL" "SYCL0","IM2COL","type_input=f32,type_kernel=f16,dst_type=f16,ne_input=[10,10,3,1],ne_kernel=[3,3,3,1],s0=1,s1=1,p0=1,p1=1,d0=1,d1=1,is_2D=1","support","1","yes","SYCL" "SYCL0","IM2COL","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,2,2],ne_kernel=[3,3,2,2],s0=1,s1=1,p0=0,p1=0,d0=1,d1=1,is_2D=1","support","1","yes","SYCL" @@ -3106,1579 +3645,3153 @@ "SYCL0","IM2COL_3D","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,10,3],ne_kernel=[3,3,3,3],IC=3,s0=3,s1=3,s2=3,p0=3,p1=3,p2=3,d0=3,d1=3,d2=3,v=0","support","1","yes","SYCL" "SYCL0","IM2COL_3D","type_input=f32,type_kernel=f32,dst_type=f32,ne_input=[20,20,10,3],ne_kernel=[3,3,3,3],IC=3,s0=3,s1=3,s2=3,p0=3,p1=3,p2=3,d0=3,d1=3,d2=3,v=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[1,1,1,2],ne_kernel=[1,1,1,1],type_kernel=f32,stride0=1,stride1=5,padding0=5,padding1=2,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[1,1,1,2],ne_kernel=[1,1,1,1],type_kernel=f32,stride0=1,stride1=5,padding0=5,padding1=2,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[1,1,1,2],ne_kernel=[1,1,1,1],type_kernel=f16,stride0=1,stride1=5,padding0=5,padding1=2,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[1,1,1,2],ne_kernel=[1,1,1,1],type_kernel=f16,stride0=1,stride1=5,padding0=5,padding1=2,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[141,1,1,2],ne_kernel=[1,1,1,1],type_kernel=f32,stride0=1,stride1=5,padding0=5,padding1=2,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[141,1,1,2],ne_kernel=[1,1,1,1],type_kernel=f32,stride0=1,stride1=5,padding0=5,padding1=2,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[141,1,1,2],ne_kernel=[1,1,1,1],type_kernel=f16,stride0=1,stride1=5,padding0=5,padding1=2,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[141,1,1,2],ne_kernel=[1,1,1,1],type_kernel=f16,stride0=1,stride1=5,padding0=5,padding1=2,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[1,133,1,2],ne_kernel=[1,1,1,1],type_kernel=f32,stride0=1,stride1=5,padding0=5,padding1=2,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" 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+"SYCL0","CONV_2D","ne_input=[1,133,25,2],ne_kernel=[2,11,25,12],type_kernel=f16,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[141,133,25,2],ne_kernel=[2,11,25,12],type_kernel=f32,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[141,133,25,2],ne_kernel=[2,11,25,12],type_kernel=f32,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[141,133,25,2],ne_kernel=[2,11,25,12],type_kernel=f16,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[141,133,25,2],ne_kernel=[2,11,25,12],type_kernel=f16,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[1,133,25,2],ne_kernel=[3,11,25,12],type_kernel=f32,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[1,133,25,2],ne_kernel=[3,11,25,12],type_kernel=f32,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[1,133,25,2],ne_kernel=[3,11,25,12],type_kernel=f16,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[1,133,25,2],ne_kernel=[3,11,25,12],type_kernel=f16,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[141,133,25,2],ne_kernel=[3,11,25,12],type_kernel=f32,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[141,133,25,2],ne_kernel=[3,11,25,12],type_kernel=f32,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[141,133,25,2],ne_kernel=[3,11,25,12],type_kernel=f16,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[141,133,25,2],ne_kernel=[3,11,25,12],type_kernel=f16,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[141,133,25,2],ne_kernel=[11,11,25,12],type_kernel=f32,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[141,133,25,2],ne_kernel=[11,11,25,12],type_kernel=f32,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[141,133,25,2],ne_kernel=[11,11,25,12],type_kernel=f16,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[141,133,25,2],ne_kernel=[11,11,25,12],type_kernel=f16,stride0=3,stride1=5,padding0=5,padding1=5,dilation0=2,dilation1=4,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[256,256,192,1],ne_kernel=[3,3,192,96],type_kernel=f32,stride0=1,stride1=1,padding0=1,padding1=1,dilation0=1,dilation1=1,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[256,256,192,1],ne_kernel=[3,3,192,96],type_kernel=f32,stride0=1,stride1=1,padding0=1,padding1=1,dilation0=1,dilation1=1,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_2D","ne_input=[256,256,192,1],ne_kernel=[3,3,192,96],type_kernel=f16,stride0=1,stride1=1,padding0=1,padding1=1,dilation0=1,dilation1=1,cwhn=0","support","1","yes","SYCL" -"SYCL0","CONV_2D_DW","ne_input=[17,34,9,1],ne_kernel=[3,3,1,9],stride=1,padding=0,dilation=1,cwhn=0","support","1","yes","SYCL" -"SYCL0","CONV_2D_DW","ne_input=[17,34,9,1],ne_kernel=[3,3,1,9],stride=1,padding=0,dilation=1,cwhn=1","support","1","yes","SYCL" -"SYCL0","CONV_2D_DW","ne_input=[32,8,64,1],ne_kernel=[3,3,1,64],stride=2,padding=1,dilation=1,cwhn=0","support","1","yes","SYCL" -"SYCL0","CONV_2D_DW","ne_input=[32,8,64,1],ne_kernel=[3,3,1,64],stride=2,padding=1,dilation=1,cwhn=1","support","1","yes","SYCL" +"SYCL0","CONV_2D","ne_input=[256,256,192,1],ne_kernel=[3,3,192,96],type_kernel=f16,stride0=1,stride1=1,padding0=1,padding1=1,dilation0=1,dilation1=1,cwhn=1","support","1","yes","SYCL" +"SYCL0","CONV_2D_DW","ne_input=[17,34,9,1],ne_kernel=[3,3,1,9],type_kernel=f32,stride=1,padding=0,dilation=1,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D_DW","ne_input=[17,34,9,1],ne_kernel=[3,3,1,9],type_kernel=f32,stride=1,padding=0,dilation=1,cwhn=1","support","1","yes","SYCL" +"SYCL0","CONV_2D_DW","ne_input=[32,8,64,1],ne_kernel=[3,3,1,64],type_kernel=f32,stride=2,padding=1,dilation=1,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D_DW","ne_input=[32,8,64,1],ne_kernel=[3,3,1,64],type_kernel=f32,stride=2,padding=1,dilation=1,cwhn=1","support","1","yes","SYCL" +"SYCL0","CONV_2D_DW","ne_input=[17,34,9,1],ne_kernel=[3,3,1,9],type_kernel=f16,stride=1,padding=0,dilation=1,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D_DW","ne_input=[17,34,9,1],ne_kernel=[3,3,1,9],type_kernel=f16,stride=1,padding=0,dilation=1,cwhn=1","support","1","yes","SYCL" +"SYCL0","CONV_2D_DW","ne_input=[32,8,64,1],ne_kernel=[3,3,1,64],type_kernel=f16,stride=2,padding=1,dilation=1,cwhn=0","support","1","yes","SYCL" +"SYCL0","CONV_2D_DW","ne_input=[32,8,64,1],ne_kernel=[3,3,1,64],type_kernel=f16,stride=2,padding=1,dilation=1,cwhn=1","support","1","yes","SYCL" "SYCL0","CONV_3D","N=1,IC=1,ID=18,IH=22,IW=20,OC=1,KD=3,KH=3,KW=3,s0=1,s1=1,s2=1,p0=0,p1=0,p2=0,d0=1,d1=1,d2=1,type_kernel=f32","support","1","yes","SYCL" "SYCL0","CONV_3D","N=1,IC=1,ID=18,IH=22,IW=20,OC=1,KD=3,KH=1,KW=5,s0=2,s1=1,s2=1,p0=2,p1=0,p2=1,d0=1,d1=1,d2=2,type_kernel=f32","support","1","yes","SYCL" "SYCL0","CONV_3D","N=1,IC=1,ID=18,IH=22,IW=20,OC=1,KD=3,KH=3,KW=3,s0=1,s1=1,s2=1,p0=0,p1=0,p2=0,d0=2,d1=2,d2=2,type_kernel=f32","support","1","yes","SYCL" @@ -5106,6 +7219,7 @@ "SYCL0","REPEAT","type=f32,ne=[10,5,4,1],nr=[1,2,1,1]","support","1","yes","SYCL" "SYCL0","REPEAT","type=f32,ne=[10,5,4,1],nr=[1,1,2,1]","support","1","yes","SYCL" "SYCL0","REPEAT","type=f32,ne=[10,5,4,1],nr=[1,1,1,2]","support","1","yes","SYCL" +"SYCL0","REPEAT","type=f16,ne=[10,5,4,1],nr=[2,1,1,1]","support","1","yes","SYCL" "SYCL0","REPEAT","type=i32,ne=[10,5,4,1],nr=[2,1,1,1]","support","1","yes","SYCL" "SYCL0","REPEAT","type=i16,ne=[10,5,4,1],nr=[1,1,1,2]","support","1","yes","SYCL" "SYCL0","REPEAT","type=bf16,ne=[10,5,4,1],nr=[2,1,1,1]","support","1","yes","SYCL" @@ -5114,6 +7228,7 @@ "SYCL0","REPEAT","type=f32,ne=[10,5,4,3],nr=[1,2,1,1]","support","1","yes","SYCL" "SYCL0","REPEAT","type=f32,ne=[10,5,4,3],nr=[1,1,2,1]","support","1","yes","SYCL" "SYCL0","REPEAT","type=f32,ne=[10,5,4,3],nr=[1,1,1,2]","support","1","yes","SYCL" +"SYCL0","REPEAT","type=f16,ne=[10,5,4,3],nr=[2,1,1,1]","support","1","yes","SYCL" "SYCL0","REPEAT","type=i32,ne=[10,5,4,3],nr=[2,1,1,1]","support","1","yes","SYCL" "SYCL0","REPEAT","type=i16,ne=[10,5,4,3],nr=[1,1,1,2]","support","1","yes","SYCL" "SYCL0","REPEAT","type=bf16,ne=[10,5,4,3],nr=[2,1,1,1]","support","1","yes","SYCL" @@ -5230,6 +7345,15 @@ "SYCL0","CPY","type_src=q1_0,type_dst=q1_0,ne_src=[384,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=q1_0,type_dst=q1_0,ne_src=[384,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=q1_0,type_dst=q1_0,ne_src=[384,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=q2_0,type_dst=q2_0,ne_src=[64,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=q2_0,type_dst=q2_0,ne_src=[64,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=q2_0,type_dst=q2_0,ne_src=[64,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=q2_0,type_dst=q2_0,ne_src=[128,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=q2_0,type_dst=q2_0,ne_src=[128,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=q2_0,type_dst=q2_0,ne_src=[128,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=q2_0,type_dst=q2_0,ne_src=[192,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=q2_0,type_dst=q2_0,ne_src=[192,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=q2_0,type_dst=q2_0,ne_src=[192,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=mxfp4,type_dst=mxfp4,ne_src=[32,2,3,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=mxfp4,type_dst=mxfp4,ne_src=[32,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=mxfp4,type_dst=mxfp4,ne_src=[32,2,3,4],permute_src=[0,3,1,2],permute_dst=[0,2,1,3],_src_transpose=0","support","1","yes","SYCL" @@ -5392,6 +7516,8 @@ "SYCL0","CPY","type_src=f16,type_dst=q8_0,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=f16,type_dst=q1_0,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=f16,type_dst=q1_0,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=f16,type_dst=q2_0,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=f16,type_dst=q2_0,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=f16,type_dst=mxfp4,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=f16,type_dst=mxfp4,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=f16,type_dst=nvfp4,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" @@ -5442,6 +7568,8 @@ "SYCL0","CPY","type_src=bf16,type_dst=q8_0,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","0","no","SYCL" "SYCL0","CPY","type_src=bf16,type_dst=q1_0,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=bf16,type_dst=q1_0,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=bf16,type_dst=q2_0,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=bf16,type_dst=q2_0,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=bf16,type_dst=mxfp4,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=bf16,type_dst=mxfp4,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=bf16,type_dst=nvfp4,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" @@ -5492,6 +7620,8 @@ "SYCL0","CPY","type_src=f32,type_dst=q8_0,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=f32,type_dst=q1_0,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=f32,type_dst=q1_0,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=f32,type_dst=q2_0,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=f32,type_dst=q2_0,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=f32,type_dst=mxfp4,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=f32,type_dst=mxfp4,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=f32,type_dst=nvfp4,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" @@ -5542,6 +7672,8 @@ "SYCL0","CPY","type_src=q8_0,type_dst=f32,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=q1_0,type_dst=f32,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","0","no","SYCL" "SYCL0","CPY","type_src=q1_0,type_dst=f32,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","0","no","SYCL" +"SYCL0","CPY","type_src=q2_0,type_dst=f32,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" +"SYCL0","CPY","type_src=q2_0,type_dst=f32,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=mxfp4,type_dst=f32,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=mxfp4,type_dst=f32,ne_src=[256,2,3,4],permute_src=[0,2,1,3],permute_dst=[0,0,0,0],_src_transpose=0","support","1","yes","SYCL" "SYCL0","CPY","type_src=nvfp4,type_dst=f32,ne_src=[256,4,4,4],permute_src=[0,0,0,0],permute_dst=[0,0,0,0],_src_transpose=0","support","0","no","SYCL" @@ -6235,6 +8367,9 @@ "SYCL0","SSM_SCAN","type=f32,d_state=128,head_dim=64,n_head=16,n_group=2,n_seq_tokens=32,n_seqs=4,xbc_overlap=0","support","1","yes","SYCL" "SYCL0","SSM_SCAN","type=f32,d_state=256,head_dim=64,n_head=8,n_group=2,n_seq_tokens=32,n_seqs=4,xbc_overlap=0","support","1","yes","SYCL" "SYCL0","SSM_SCAN","type=f32,d_state=128,head_dim=128,n_head=4,n_group=4,n_seq_tokens=16,n_seqs=2,xbc_overlap=1","support","1","yes","SYCL" +"SYCL0","SSM_SCAN","type=f32,d_state=128,head_dim=80,n_head=128,n_group=1,n_seq_tokens=256,n_seqs=1,xbc_overlap=0","support","1","yes","SYCL" +"SYCL0","SSM_SCAN","type=f32,d_state=128,head_dim=80,n_head=128,n_group=1,n_seq_tokens=512,n_seqs=1,xbc_overlap=0","support","1","yes","SYCL" +"SYCL0","SSM_SCAN","type=f32,d_state=128,head_dim=64,n_head=80,n_group=8,n_seq_tokens=300,n_seqs=2,xbc_overlap=0","support","1","yes","SYCL" "SYCL0","RWKV_WKV6","type=f32,head_count=32,head_size=64,n_seq_tokens=1,n_seqs=1","support","1","yes","SYCL" "SYCL0","RWKV_WKV6","type=f32,head_count=32,head_size=64,n_seq_tokens=32,n_seqs=1","support","1","yes","SYCL" "SYCL0","RWKV_WKV6","type=f32,head_count=32,head_size=64,n_seq_tokens=32,n_seqs=4","support","1","yes","SYCL" @@ -6253,6 +8388,9 @@ "SYCL0","MUL_MAT_HADAMARD","type_a=f32,type_b=f32,m=512,n=1,k=512,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT_HADAMARD","type_a=f32,type_b=f32,m=128,n=32,k=128,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT_HADAMARD","type_a=f32,type_b=f32,m=128,n=4,k=128,bs=[2,3],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT_HADAMARD","type_a=f32,type_b=f32,m=256,n=512,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT_HADAMARD","type_a=f32,type_b=f32,m=32,n=1,k=32,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT_HADAMARD","type_a=f32,type_b=f32,m=1024,n=1,k=1024,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" @@ -6334,6 +8472,15 @@ "SYCL0","MUL_MAT","type_a=q1_0,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=q1_0,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=q1_0,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=q2_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=q2_0,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=q2_0,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=q2_0,type_b=f32,m=16,n=4,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=q2_0,type_b=f32,m=16,n=5,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=q2_0,type_b=f32,m=16,n=6,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=q2_0,type_b=f32,m=16,n=7,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=q2_0,type_b=f32,m=16,n=8,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=q2_0,type_b=f32,m=16,n=9,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=mxfp4,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=mxfp4,type_b=f32,m=16,n=2,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=mxfp4,type_b=f32,m=16,n=3,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" @@ -6481,6 +8628,13 @@ "SYCL0","MUL_MAT","type_a=q4_0,type_b=f32,m=2880,n=32,k=2880,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=q8_0,type_b=f32,m=2880,n=32,k=2880,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=mxfp4,type_b=f32,m=2880,n=32,k=2880,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=1,n=1,k=2048,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=1,n=7,k=2048,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=1,n=8,k=2048,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=1,n=9,k=2048,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=1,n=16,k=2048,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=1,n=128,k=2048,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=1,n=512,k=2048,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,2],per=[0,1,2,3],k_v=0,o=1","support","0","no","SYCL" @@ -6861,6 +9015,72 @@ "SYCL0","MUL_MAT","type_a=q1_0,type_b=f16,m=16,n=8,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=q1_0,type_b=f16,m=16,n=16,k=1024,bs=[3,2],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=q1_0,type_b=f16,m=16,n=8,k=256,bs=[1536,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=q2_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=q2_0,type_b=f32,m=16,n=1,k=256,bs=[1,1],nr=[2,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" 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"SYCL0","MUL_MAT","type_a=q1_0,type_b=f32,m=1,n=64,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" +"SYCL0","MUL_MAT","type_a=q2_0,type_b=f32,m=1,n=64,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=mxfp4,type_b=f32,m=1,n=64,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=nvfp4,type_b=f32,m=1,n=64,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=q2_K,type_b=f32,m=1,n=64,k=256,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1","support","1","yes","SYCL" @@ -7550,7 +9773,6 @@ "SYCL0","MUL_MAT","type_a=bf16,type_b=f32,m=128,n=1,k=1056,bs=[1,3],nr=[4,1],per=[0,1,2,3],k_v=2112,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=1056,n=1,k=128,bs=[1,3],nr=[4,1],per=[0,2,1,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=128,n=1,k=1056,bs=[1,3],nr=[4,1],per=[0,1,2,3],k_v=2112,o=1","support","1","yes","SYCL" -zjy 2 "SYCL0","MUL_MAT","type_a=f16,type_b=f32,m=1056,n=1,k=129,bs=[1,3],nr=[4,1],per=[0,2,1,3],k_v=0,o=1","support","0","no","SYCL" "SYCL0","MUL_MAT","type_a=f16,type_b=f32,m=128,n=1,k=1057,bs=[1,3],nr=[4,1],per=[0,1,2,3],k_v=2113,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=bf16,type_b=f32,m=1056,n=1,k=129,bs=[1,3],nr=[4,1],per=[0,2,1,3],k_v=0,o=1","support","1","yes","SYCL" @@ -7563,7 +9785,6 @@ zjy 2 "SYCL0","MUL_MAT","type_a=bf16,type_b=f32,m=129,n=1,k=1056,bs=[1,3],nr=[4,1],per=[0,1,2,3],k_v=2112,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=1057,n=1,k=128,bs=[1,3],nr=[4,1],per=[0,2,1,3],k_v=0,o=1","support","1","yes","SYCL" "SYCL0","MUL_MAT","type_a=f32,type_b=f32,m=129,n=1,k=1056,bs=[1,3],nr=[4,1],per=[0,1,2,3],k_v=2112,o=1","support","1","yes","SYCL" -zjy 2 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+"SYCL0","CONCAT","type=q8_0,ne_a=[128,12,13,14],ne_b_d=7,dim=2,v=4","support","1","yes","SYCL" +"SYCL0","CONCAT","type=q8_0,ne_a=[128,12,13,14],ne_b_d=7,dim=3,v=4","support","1","yes","SYCL" +"SYCL0","CONCAT","type=q8_0,ne_a=[128,12,13,14],ne_b_d=256,dim=0,v=8","support","1","yes","SYCL" +"SYCL0","CONCAT","type=q8_0,ne_a=[128,12,13,14],ne_b_d=7,dim=1,v=8","support","1","yes","SYCL" +"SYCL0","CONCAT","type=q8_0,ne_a=[128,12,13,14],ne_b_d=7,dim=2,v=8","support","1","yes","SYCL" +"SYCL0","CONCAT","type=q8_0,ne_a=[128,12,13,14],ne_b_d=7,dim=3,v=8","support","1","yes","SYCL" +"SYCL0","CONCAT","type=q8_0,ne_a=[128,12,13,14],ne_b_d=256,dim=0,v=12","support","1","yes","SYCL" +"SYCL0","CONCAT","type=q8_0,ne_a=[128,12,13,14],ne_b_d=7,dim=1,v=12","support","1","yes","SYCL" +"SYCL0","CONCAT","type=q8_0,ne_a=[128,12,13,14],ne_b_d=7,dim=2,v=12","support","1","yes","SYCL" +"SYCL0","CONCAT","type=q8_0,ne_a=[128,12,13,14],ne_b_d=7,dim=3,v=12","support","1","yes","SYCL" "SYCL0","ARGSORT","type=f32,ne=[3,1,1,1],order=0","support","1","yes","SYCL" "SYCL0","ARGSORT","type=f32,ne=[4,1,1,1],order=0","support","1","yes","SYCL" "SYCL0","ARGSORT","type=f32,ne=[7,1,1,1],order=0","support","1","yes","SYCL" @@ -11559,8 +14063,8 @@ zjy 2 "SYCL0","ACC","type=f32,ne_a=[256,17,1,1],ne_b=[256,16,1,1],stride_dim=-1","support","1","yes","SYCL" "SYCL0","ACC","type=f32,ne_a=[256,17,2,3],ne_b=[256,16,2,3],stride_dim=-1","support","1","yes","SYCL" "SYCL0","ACC","type=f32,ne_a=[256,17,2,3],ne_b=[128,16,2,3],stride_dim=-1","support","1","yes","SYCL" -"SYCL0","ACC","type=f32,ne_a=[256,17,2,3],ne_b=[256,16,2,3],stride_dim=1","support","0","no","SYCL" -"SYCL0","ACC","type=f32,ne_a=[256,17,2,3],ne_b=[128,16,2,3],stride_dim=2","support","0","no","SYCL" +"SYCL0","ACC","type=f32,ne_a=[256,17,2,3],ne_b=[256,16,2,3],stride_dim=1","support","1","yes","SYCL" +"SYCL0","ACC","type=f32,ne_a=[256,17,2,3],ne_b=[128,16,2,3],stride_dim=2","support","1","yes","SYCL" "SYCL0","ACC","type=f32,ne_a=[256,17,2,3],ne_b=[64,16,2,3],stride_dim=3","support","1","yes","SYCL" "SYCL0","PAD","type=f32,ne_a=[512,512,1,1],pad_0=1,pad_1=1,circular=0","support","1","yes","SYCL" "SYCL0","PAD","type=f32,ne_a=[33,17,2,1],pad_0=4,pad_1=3,circular=1","support","0","no","SYCL" @@ -11651,6 +14155,42 @@ zjy 2 "SYCL0","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,tfrm=2,circular=0","support","1","yes","SYCL" "SYCL0","PAD","type=f32,ne_a=[512,512,1,1],lp0=0,rp0=1,lp1=0,rp1=1,lp2=0,rp2=0,lp3=0,rp3=0,tfrm=2,circular=1","support","0","no","SYCL" "SYCL0","PAD","type=f32,ne_a=[11,22,33,44],lp0=1,rp0=2,lp1=3,rp1=4,lp2=5,rp2=6,lp3=7,rp3=8,tfrm=2,circular=1","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=8,nr23=[4,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" 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+"SYCL0","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=8,nr23=[4,1],kv=1024,nb=64,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q4_0,type_V=q4_0,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=8,nr23=[4,1],kv=2048,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=8,nr23=[4,1],kv=2048,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=8,nr23=[4,1],kv=2048,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q4_0,type_V=q4_0,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=8,nr23=[4,1],kv=2048,nb=64,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=8,nr23=[4,1],kv=2048,nb=64,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=8,nr23=[4,1],kv=2048,nb=64,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q4_0,type_V=q4_0,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=8,nr23=[4,1],kv=2048,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=8,nr23=[4,1],kv=2048,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=8,nr23=[4,1],kv=2048,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q4_0,type_V=q4_0,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=8,nr23=[4,1],kv=2048,nb=64,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=8,nr23=[4,1],kv=2048,nb=64,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=8,nr23=[4,1],kv=2048,nb=64,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q4_0,type_V=q4_0,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=8,nr23=[4,1],kv=2048,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=8,nr23=[4,1],kv=2048,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=8,nr23=[4,1],kv=2048,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q4_0,type_V=q4_0,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=8,nr23=[4,1],kv=2048,nb=64,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=8,nr23=[4,1],kv=2048,nb=64,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=8,nr23=[4,1],kv=2048,nb=64,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q4_0,type_V=q4_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=40,hsv=40,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=40,hsv=40,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=40,hsv=40,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -11877,7 +14417,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=40,hsv=40,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -11886,7 +14426,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -11895,7 +14435,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -11904,7 +14444,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -11915,8 +14455,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -11933,8 +14473,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -11951,8 +14491,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -11969,8 +14509,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -11985,7 +14525,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,2,1,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -11994,7 +14534,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12003,7 +14543,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12012,7 +14552,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12023,8 +14563,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12041,8 +14581,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12059,8 +14599,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12077,8 +14617,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12093,7 +14633,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,2,1,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12102,7 +14642,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12111,7 +14651,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12120,7 +14660,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12131,8 +14671,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12149,8 +14689,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12167,8 +14707,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12185,8 +14725,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12201,7 +14741,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,2,1,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12210,7 +14750,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12219,7 +14759,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12228,7 +14768,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12239,8 +14779,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12257,8 +14797,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12275,8 +14815,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12293,8 +14833,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12309,7 +14849,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,2,1,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12318,7 +14858,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12327,7 +14867,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12336,7 +14876,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12345,7 +14885,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12354,7 +14894,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12363,7 +14903,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12372,7 +14912,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12381,7 +14921,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12390,7 +14930,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12399,7 +14939,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12408,7 +14948,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12417,7 +14957,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12426,7 +14966,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12435,7 +14975,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12444,7 +14984,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12453,7 +14993,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12462,7 +15002,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12471,7 +15011,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12480,7 +15020,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12489,7 +15029,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12498,7 +15038,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12507,7 +15047,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12516,7 +15056,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12525,7 +15065,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12534,7 +15074,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12543,7 +15083,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12552,7 +15092,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12561,7 +15101,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12570,7 +15110,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12579,7 +15119,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12588,7 +15128,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12597,7 +15137,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12606,7 +15146,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12615,7 +15155,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12624,7 +15164,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12635,8 +15175,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12653,8 +15193,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12671,8 +15211,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12689,8 +15229,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12705,7 +15245,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,2,1,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12714,7 +15254,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12723,7 +15263,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12732,7 +15272,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12743,8 +15283,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12761,8 +15301,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12779,8 +15319,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12797,8 +15337,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12813,7 +15353,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,2,1,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12822,7 +15362,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12831,7 +15371,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12840,7 +15380,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12851,8 +15391,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12869,8 +15409,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12887,8 +15427,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12905,8 +15445,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12921,7 +15461,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,2,1,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12930,7 +15470,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12939,7 +15479,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12948,7 +15488,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12959,8 +15499,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12977,8 +15517,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -12995,8 +15535,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13013,8 +15553,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13029,7 +15569,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,2,1,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13038,7 +15578,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13047,7 +15587,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13056,7 +15596,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13065,7 +15605,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13074,7 +15614,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13083,7 +15623,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13092,7 +15632,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13101,7 +15641,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13110,7 +15650,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13119,7 +15659,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13128,7 +15668,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13137,7 +15677,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13146,7 +15686,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13155,7 +15695,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13164,7 +15704,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13173,7 +15713,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13182,7 +15722,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13191,7 +15731,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13200,7 +15740,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13209,7 +15749,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13218,7 +15758,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13227,7 +15767,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13236,7 +15776,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13245,7 +15785,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13254,7 +15794,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13263,7 +15803,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13272,7 +15812,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13281,7 +15821,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13290,7 +15830,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13299,7 +15839,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13308,7 +15848,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13317,7 +15857,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13326,7 +15866,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13335,7 +15875,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13344,7 +15884,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13353,7 +15893,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13362,7 +15902,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13371,7 +15911,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13380,7 +15920,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13389,7 +15929,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13398,7 +15938,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13407,7 +15947,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13416,7 +15956,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13425,7 +15965,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13434,7 +15974,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13443,7 +15983,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13452,7 +15992,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13461,7 +16001,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13470,7 +16010,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13479,7 +16019,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13488,7 +16028,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13497,7 +16037,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13506,7 +16046,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13515,7 +16055,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13524,7 +16064,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13533,7 +16073,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13542,7 +16082,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13551,7 +16091,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13560,7 +16100,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13569,7 +16109,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13578,7 +16118,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13587,7 +16127,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13596,7 +16136,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13605,7 +16145,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13614,7 +16154,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13623,7 +16163,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13632,7 +16172,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13641,7 +16181,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13650,7 +16190,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13659,7 +16199,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13668,7 +16208,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13677,7 +16217,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13686,7 +16226,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13695,7 +16235,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13704,7 +16244,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13713,7 +16253,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13722,7 +16262,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13731,7 +16271,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13740,7 +16280,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13749,7 +16289,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13758,7 +16298,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13767,7 +16307,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13776,7 +16316,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13785,7 +16325,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13794,7 +16334,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13803,7 +16343,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13812,7 +16352,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13821,7 +16361,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13830,7 +16370,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13839,7 +16379,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13848,7 +16388,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13857,7 +16397,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[1,3],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13866,7 +16406,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13875,7 +16415,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13884,7 +16424,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13893,7 +16433,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=64,nh=4,nr23=[4,3],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13902,7 +16442,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13911,7 +16451,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13920,7 +16460,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13931,8 +16471,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13949,8 +16489,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13967,8 +16507,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -13985,8 +16525,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14001,7 +16541,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,2,1,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14010,7 +16550,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14019,7 +16559,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14028,7 +16568,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14039,8 +16579,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14057,8 +16597,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14075,8 +16615,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14093,8 +16633,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14109,7 +16649,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,2,1,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14118,7 +16658,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14127,7 +16667,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14136,7 +16676,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14145,7 +16685,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14154,7 +16694,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14163,7 +16703,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14172,7 +16712,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14181,7 +16721,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14190,7 +16730,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14199,7 +16739,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14208,7 +16748,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14217,7 +16757,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14226,7 +16766,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14235,7 +16775,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14244,7 +16784,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14253,7 +16793,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=1,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14262,7 +16802,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14271,7 +16811,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14280,7 +16820,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14291,8 +16831,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14309,8 +16849,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14327,8 +16867,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14345,8 +16885,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14361,7 +16901,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,2,1,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14370,7 +16910,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14379,7 +16919,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14388,7 +16928,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14399,8 +16939,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14417,8 +16957,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14435,8 +16975,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14453,8 +16993,8 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,2,1,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,2,1,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14469,7 +17009,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,2,1,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14478,7 +17018,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14487,7 +17027,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14496,7 +17036,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14505,7 +17045,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14514,7 +17054,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14523,7 +17063,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14532,7 +17072,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14541,7 +17081,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14550,7 +17090,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14559,7 +17099,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14568,7 +17108,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14577,7 +17117,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14586,7 +17126,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14595,7 +17135,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14604,7 +17144,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14613,7 +17153,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=1,sinks=0,max_bias=8.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14622,7 +17162,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14631,7 +17171,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14640,7 +17180,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14649,7 +17189,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14658,7 +17198,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14667,7 +17207,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14676,7 +17216,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14685,7 +17225,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14694,7 +17234,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14703,7 +17243,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14712,7 +17252,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14721,7 +17261,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14730,7 +17270,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14739,7 +17279,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14748,7 +17288,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14757,7 +17297,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=1,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14766,7 +17306,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14775,7 +17315,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14784,7 +17324,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14793,7 +17333,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=113,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14802,7 +17342,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14811,7 +17351,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14820,7 +17360,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14829,7 +17369,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14838,7 +17378,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14847,7 +17387,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14856,7 +17396,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14865,7 +17405,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[1,1],kv=1024,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14874,7 +17414,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=1,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14883,7 +17423,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=3,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -14892,7 +17432,7 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=32,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=iq4_nl,type_V=iq4_nl,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f32,type_V=f32,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" -"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=bf16,type_V=bf16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q8_0,type_V=q8_0,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_1,type_V=q5_1,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=72,hsv=72,nh=4,nr23=[4,1],kv=512,nb=75,mask=0,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q5_0,type_V=q5_0,permute=[0,1,2,3]","support","1","yes","SYCL" @@ -16748,6 +19288,14 @@ zjy 2 "SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=64,nh=4,nr23=[1,1],kv=128,nb=2,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q1_0,type_V=q4_0,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=128,nh=4,nr23=[1,1],kv=128,nb=2,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q4_0,type_V=q1_0,permute=[0,1,2,3]","support","0","no","SYCL" "SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=64,nh=4,nr23=[1,1],kv=64,nb=2,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q1_0,type_V=f16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=4,nr23=[1,1],kv=96,nb=2,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q2_0,type_V=q2_0,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=64,nh=4,nr23=[1,1],kv=128,nb=2,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q2_0,type_V=q4_0,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=64,hsv=128,nh=4,nr23=[1,1],kv=128,nb=2,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q4_0,type_V=q2_0,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=64,nh=4,nr23=[1,1],kv=64,nb=2,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=q2_0,type_V=f16,permute=[0,1,2,3]","support","0","no","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[6,1],kv=4096,nb=512,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=8,nr23=[4,1],kv=4096,nb=512,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=256,hsv=256,nh=4,nr23=[6,1],kv=16384,nb=512,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" +"SYCL0","FLASH_ATTN_EXT","hsk=128,hsv=128,nh=8,nr23=[4,1],kv=16384,nb=512,mask=1,sinks=0,max_bias=0.000000,logit_softcap=0.000000,prec=f32,type_K=f16,type_V=f16,permute=[0,1,2,3]","support","1","yes","SYCL" "SYCL0","CROSS_ENTROPY_LOSS","type=f32,ne=[10,5,4,3]","support","1","yes","SYCL" "SYCL0","CROSS_ENTROPY_LOSS","type=f32,ne=[30000,1,1,1]","support","1","yes","SYCL" "SYCL0","CROSS_ENTROPY_LOSS_BACK","type=f32,ne=[10,5,4,3]","support","1","yes","SYCL" @@ -16790,3 +19338,19654 @@ zjy 2 "SYCL0","GATED_DELTA_NET","type=f32,head_count=8,head_size=32,n_seq_tokens=4,n_seqs=2,v_repeat=2,permuted=0,kda=1,K=4","support","1","yes","SYCL" "SYCL0","GATED_DELTA_NET","type=f32,head_count=4,head_size=32,n_seq_tokens=8,n_seqs=1,v_repeat=1,permuted=0,kda=0,K=3","support","1","yes","SYCL" "SYCL0","GATED_DELTA_NET","type=f32,head_count=4,head_size=64,n_seq_tokens=16,n_seqs=2,v_repeat=1,permuted=0,kda=0,K=4","support","1","yes","SYCL" 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+"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,1,1,1],ne_kernel=[1,9,1,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,1,1,1],ne_kernel=[3,9,1,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,1,1,1],ne_kernel=[3,9,1,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,1,1,1],ne_kernel=[3,9,1,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,1,1,1],ne_kernel=[3,9,1,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,1,1,1],ne_kernel=[3,9,1,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,1,1,1],ne_kernel=[3,9,1,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,1,1,1],ne_kernel=[3,9,1,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,1,1,1],ne_kernel=[3,9,1,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,1,1,1],ne_kernel=[3,9,1,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,1,1,1],ne_kernel=[1337,9,1,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,1,1,1],ne_kernel=[1337,9,1,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,1,1,1],ne_kernel=[1337,9,1,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,1,1,1],ne_kernel=[1337,9,1,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,1,1,1],ne_kernel=[1337,9,1,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,1,1,1],ne_kernel=[1337,9,1,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,1,1,1],ne_kernel=[1337,9,1,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,1,1,1],ne_kernel=[1337,9,1,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,1,1,1],ne_kernel=[1337,9,1,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,7,1,1],ne_kernel=[1,9,7,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,7,1,1],ne_kernel=[1,9,7,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,7,1,1],ne_kernel=[1,9,7,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,7,1,1],ne_kernel=[1,9,7,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,7,1,1],ne_kernel=[1,9,7,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,7,1,1],ne_kernel=[1,9,7,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,7,1,1],ne_kernel=[1,9,7,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,7,1,1],ne_kernel=[1,9,7,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,7,1,1],ne_kernel=[1,9,7,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,7,1,1],ne_kernel=[3,9,7,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,7,1,1],ne_kernel=[3,9,7,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,7,1,1],ne_kernel=[3,9,7,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,7,1,1],ne_kernel=[3,9,7,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,7,1,1],ne_kernel=[3,9,7,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,7,1,1],ne_kernel=[3,9,7,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,7,1,1],ne_kernel=[3,9,7,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,7,1,1],ne_kernel=[3,9,7,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,7,1,1],ne_kernel=[3,9,7,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,7,1,1],ne_kernel=[1337,9,7,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,7,1,1],ne_kernel=[1337,9,7,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[1,7,1,1],ne_kernel=[1337,9,7,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,7,1,1],ne_kernel=[1337,9,7,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,7,1,1],ne_kernel=[1337,9,7,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,7,1,1],ne_kernel=[1337,9,7,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,7,1,1],ne_kernel=[1337,9,7,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,7,1,1],ne_kernel=[1337,9,7,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[13,7,1,1],ne_kernel=[1337,9,7,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[197,32,1,1],ne_kernel=[16,32,32,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[3,2,1,1],ne_kernel=[2,3,2,1],s0=3,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[3,2,1,1],ne_kernel=[2,3,2,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[3,2,1,1],ne_kernel=[2,3,2,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[3,2,1,1],ne_kernel=[3,2,2,1],s0=2,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[3,2,1,1],ne_kernel=[3,2,2,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[3,2,1,1],ne_kernel=[3,1,2,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_1D","ne_input=[2,1,1,1],ne_kernel=[3,1,1,1],s0=1,p0=0,d0=1","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f32,K=16,OC=32,T_in=197,s0=8,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f32,K=4,OC=3,T_in=7,s0=2,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f32,K=1,OC=5,T_in=13,s0=1,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f32,K=6,OC=4,T_in=11,s0=3,p0=1","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f32,K=2,OC=3,T_in=9,s0=3,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f32,K=5,OC=4,T_in=11,s0=2,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f32,K=8,OC=4,T_in=13,s0=4,p0=2","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f32,K=4,OC=3,T_in=1,s0=2,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f32,K=16,OC=1,T_in=197,s0=8,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f32,K=1,OC=5,T_in=13,s0=3,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f32,K=8,OC=2,T_in=3,s0=2,p0=5","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f16,K=16,OC=32,T_in=197,s0=8,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f16,K=4,OC=3,T_in=7,s0=2,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f16,K=1,OC=5,T_in=13,s0=1,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f16,K=6,OC=4,T_in=11,s0=3,p0=1","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f16,K=2,OC=3,T_in=9,s0=3,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f16,K=5,OC=4,T_in=11,s0=2,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f16,K=8,OC=4,T_in=13,s0=4,p0=2","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f16,K=4,OC=3,T_in=1,s0=2,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f16,K=16,OC=1,T_in=197,s0=8,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f16,K=1,OC=5,T_in=13,s0=3,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=f16,K=8,OC=2,T_in=3,s0=2,p0=5","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=bf16,K=16,OC=32,T_in=197,s0=8,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=bf16,K=4,OC=3,T_in=7,s0=2,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=bf16,K=1,OC=5,T_in=13,s0=1,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=bf16,K=6,OC=4,T_in=11,s0=3,p0=1","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=bf16,K=2,OC=3,T_in=9,s0=3,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=bf16,K=5,OC=4,T_in=11,s0=2,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=bf16,K=8,OC=4,T_in=13,s0=4,p0=2","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=bf16,K=4,OC=3,T_in=1,s0=2,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=bf16,K=16,OC=1,T_in=197,s0=8,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=bf16,K=1,OC=5,T_in=13,s0=3,p0=0","support","1","yes","SYCL" +"SYCL1","COL2IM_1D","type=bf16,K=8,OC=2,T_in=3,s0=2,p0=5","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_2D","kernel_type=f32,ne_input=[3,2,3,1],ne_kernel=[2,2,1,3],stride=1","support","1","yes","SYCL" +"SYCL1","CONV_TRANSPOSE_2D","kernel_type=f32,ne_input=[10,10,9,1],ne_kernel=[3,3,1,9],stride=2","support","1","yes","SYCL" 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+"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=1,nm=1,type_K=q8_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=1,nm=1,type_K=q5_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=1,nm=1,type_K=q5_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=1,nm=1,type_K=q4_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=1,nm=1,type_K=q4_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=1,nm=1,type_K=iq4_nl","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=4,type_K=f32","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=4,type_K=f16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=4,type_K=bf16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=4,type_K=q8_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=4,type_K=q5_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=4,type_K=q5_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=4,type_K=q4_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=4,type_K=q4_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=4,type_K=iq4_nl","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=1,type_K=f32","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=1,type_K=f16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=1,type_K=bf16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=1,type_K=q8_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=1,type_K=q5_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=1,type_K=q5_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=1,type_K=q4_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=1,type_K=q4_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=256,nb=512,ns=4,nm=1,type_K=iq4_nl","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=1,nb=32,ns=4,nm=1,type_K=f32","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=1,nb=32,ns=4,nm=1,type_K=f16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=1,nb=32,ns=4,nm=1,type_K=bf16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=1,nb=32,ns=4,nm=1,type_K=q8_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=1,nb=32,ns=4,nm=1,type_K=q5_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=1,nb=32,ns=4,nm=1,type_K=q5_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=1,nb=32,ns=4,nm=1,type_K=q4_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=1,nb=32,ns=4,nm=1,type_K=q4_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=7,nb=32,ns=4,nm=1,type_K=f32","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=7,nb=32,ns=4,nm=1,type_K=f16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=7,nb=32,ns=4,nm=1,type_K=bf16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=7,nb=32,ns=4,nm=1,type_K=q8_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=7,nb=32,ns=4,nm=1,type_K=q5_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=7,nb=32,ns=4,nm=1,type_K=q5_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=7,nb=32,ns=4,nm=1,type_K=q4_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=7,nb=32,ns=4,nm=1,type_K=q4_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=8,nb=32,ns=4,nm=1,type_K=f32","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=8,nb=32,ns=4,nm=1,type_K=f16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=8,nb=32,ns=4,nm=1,type_K=bf16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=8,nb=32,ns=4,nm=1,type_K=q8_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=8,nb=32,ns=4,nm=1,type_K=q5_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=8,nb=32,ns=4,nm=1,type_K=q5_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=8,nb=32,ns=4,nm=1,type_K=q4_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=8,nb=32,ns=4,nm=1,type_K=q4_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=63,nb=32,ns=4,nm=1,type_K=f32","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=63,nb=32,ns=4,nm=1,type_K=f16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=63,nb=32,ns=4,nm=1,type_K=bf16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=63,nb=32,ns=4,nm=1,type_K=q8_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=63,nb=32,ns=4,nm=1,type_K=q5_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=63,nb=32,ns=4,nm=1,type_K=q5_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=63,nb=32,ns=4,nm=1,type_K=q4_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=63,nb=32,ns=4,nm=1,type_K=q4_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=64,nb=32,ns=4,nm=1,type_K=f32","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=64,nb=32,ns=4,nm=1,type_K=f16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=64,nb=32,ns=4,nm=1,type_K=bf16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=64,nb=32,ns=4,nm=1,type_K=q8_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=64,nb=32,ns=4,nm=1,type_K=q5_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=64,nb=32,ns=4,nm=1,type_K=q5_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=64,nb=32,ns=4,nm=1,type_K=q4_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=64,nb=32,ns=4,nm=1,type_K=q4_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=65,nb=32,ns=4,nm=1,type_K=f32","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=65,nb=32,ns=4,nm=1,type_K=f16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=65,nb=32,ns=4,nm=1,type_K=bf16","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=65,nb=32,ns=4,nm=1,type_K=q8_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=65,nb=32,ns=4,nm=1,type_K=q5_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=65,nb=32,ns=4,nm=1,type_K=q5_0","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=65,nb=32,ns=4,nm=1,type_K=q4_1","support","1","yes","SYCL" +"SYCL1","LIGHTNING_INDEXER","hsk=128,nh=64,kv=65,nb=32,ns=4,nm=1,type_K=q4_0","support","1","yes","SYCL" diff --git a/examples/model-conversion/scripts/causal/convert-model.sh b/examples/model-conversion/scripts/causal/convert-model.sh index 4aa72206288..270e17e6f62 100755 --- a/examples/model-conversion/scripts/causal/convert-model.sh +++ b/examples/model-conversion/scripts/causal/convert-model.sh @@ -47,6 +47,7 @@ CMD_ARGS+=("../../convert_hf_to_gguf.py" "--verbose") CMD_ARGS+=("${MODEL_PATH}") CMD_ARGS+=("--outfile" "${CONVERTED_MODEL}") CMD_ARGS+=("--outtype" "${TYPE}") +CMD_ARGS+=("--model-name" "${MODEL_NAME}") [[ -n "$METADATA_OVERRIDE" ]] && CMD_ARGS+=("--metadata" "${METADATA_OVERRIDE}") [[ -n "$MMPROJ" ]] && CMD_ARGS+=("${MMPROJ}") diff --git a/examples/model-conversion/scripts/embedding/convert-model.sh b/examples/model-conversion/scripts/embedding/convert-model.sh index 9926350c072..8b706e16476 100755 --- a/examples/model-conversion/scripts/embedding/convert-model.sh +++ b/examples/model-conversion/scripts/embedding/convert-model.sh @@ -31,6 +31,7 @@ python ../../convert_hf_to_gguf.py --verbose \ ${EMBEDDING_MODEL_PATH} \ --outfile ${CONVERTED_MODEL} \ --outtype ${TYPE} \ + --model-name ${MODEL_NAME} \ ${SENTENCE_TRANSFORMERS} echo "" diff --git a/examples/sycl/start-svr.sh b/examples/sycl/start-svr.sh index ce31ec51d2b..49177ba2dc5 100755 --- a/examples/sycl/start-svr.sh +++ b/examples/sycl/start-svr.sh @@ -12,6 +12,7 @@ This script processes files with specified options. Options: -h, --help Display this help message and exit. + -d, --device Set SYCL devices (default: SYCL0). -c, --context Set context length. Bigger need more memory. -p, --promote Prompt to start generation with. -m, --model Full model file path. @@ -41,10 +42,16 @@ MODEL_FILE=../models/Qwen3.5-4B-Q4_0.gguf NGL=99 CONTEXT=4096 GGML_SYCL_DEVICE=-1 +SYCL_DEVICES="SYCL0" SPLIT_MODE=layer LOG_VERBOSE=3 while [[ $# -gt 0 ]]; do case "$1" in + -d|--device) + SYCL_DEVICES="$2" + shift + shift + ;; -c|--context) CONTEXT=$2 # Shift twice to consume both the option flag and its value @@ -95,8 +102,6 @@ while [[ $# -gt 0 ]]; do esac done - - source /opt/intel/oneapi/setvars.sh #export GGML_SYCL_DEBUG=1 @@ -107,17 +112,19 @@ source /opt/intel/oneapi/setvars.sh export UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS=1 echo "UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS=${UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS}" +echo "ONEAPI_DEVICE_SELECTOR=${ONEAPI_DEVICE_SELECTOR}" + + if [ $GGML_SYCL_DEVICE -ne -1 ]; then echo "Use $GGML_SYCL_DEVICE as main GPU" #use signle GPU only GPUS_SETTING="-mg $GGML_SYCL_DEVICE -sm ${SPLIT_MODE}" - echo "ONEAPI_DEVICE_SELECTOR=${ONEAPI_DEVICE_SELECTOR}" else - echo "Use all Intel GPUs, including iGPU & dGPU" + echo "Use Intel GPUs: ${SYCL_DEVICES}" GPUS_SETTING="-sm ${SPLIT_MODE}" - fi +fi -echo "run cmd: ZES_ENABLE_SYSMAN=1 ${BIN_FILE} -m ${MODEL_FILE} -ngl ${NGL} -s ${SEED} -c ${CONTEXT} ${GPUS_SETTING} -lv ${LOG_VERBOSE} --mmap --host 0.0.0.0 --port 8000" -ZES_ENABLE_SYSMAN=1 ${BIN_FILE} -m ${MODEL_FILE} -ngl ${NGL} -s ${SEED} -c ${CONTEXT} ${GPUS_SETTING} -lv ${LOG_VERBOSE} --mmap --host 0.0.0.0 --port 8000 +echo "run cmd: ZES_ENABLE_SYSMAN=1 ${BIN_FILE} -m ${MODEL_FILE} -ngl ${NGL} -s ${SEED} -c ${CONTEXT} ${GPUS_SETTING} -lv ${LOG_VERBOSE} --device ${SYCL_DEVICES} --mmap --host 0.0.0.0 --port 8000" +ZES_ENABLE_SYSMAN=1 ${BIN_FILE} -m ${MODEL_FILE} -ngl ${NGL} -s ${SEED} -c ${CONTEXT} ${GPUS_SETTING} -lv ${LOG_VERBOSE} --device ${SYCL_DEVICES} --mmap --host 0.0.0.0 --port 8000 diff --git a/examples/sycl/test.sh b/examples/sycl/test.sh index 116047cd2ea..b9498f49b78 100755 --- a/examples/sycl/test.sh +++ b/examples/sycl/test.sh @@ -12,6 +12,7 @@ This script processes files with specified options. Options: -h, --help Display this help message and exit. + -d, --device Set SYCL devices (default: SYCL0). -c, --context Set context length. Bigger need more memory. -p, --promote Prompt to start generation with. -m, --model Full model file path. @@ -42,10 +43,16 @@ MODEL_FILE=../models/llama-2-7b.Q4_0.gguf NGL=99 CONTEXT=4096 GGML_SYCL_DEVICE=-1 +SYCL_DEVICES="SYCL0" SPLIT_MODE=layer LOG_VERBOSE=3 while [[ $# -gt 0 ]]; do case "$1" in + -d|--device) + SYCL_DEVICES="$2" + shift + shift + ;; -c|--context) CONTEXT=$2 # Shift twice to consume both the option flag and its value @@ -115,16 +122,17 @@ source /opt/intel/oneapi/setvars.sh export UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS=1 echo "UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS=${UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS}" +echo "ONEAPI_DEVICE_SELECTOR=${ONEAPI_DEVICE_SELECTOR}" + if [ $GGML_SYCL_DEVICE -ne -1 ]; then echo "Use $GGML_SYCL_DEVICE as main GPU" #use signle GPU only GPUS_SETTING="-mg $GGML_SYCL_DEVICE -sm ${SPLIT_MODE}" - echo "ONEAPI_DEVICE_SELECTOR=${ONEAPI_DEVICE_SELECTOR}" else - echo "Use all Intel GPUs, including iGPU & dGPU" + echo "Use Intel GPUs: ${SYCL_DEVICES}" GPUS_SETTING="-sm ${SPLIT_MODE}" fi -echo "run cmd: ZES_ENABLE_SYSMAN=1 ${BIN_FILE} -m ${MODEL_FILE} -no-cnv -p "${INPUT_PROMPT}" -n 200 -e -ngl ${NGL} -s ${SEED} -c ${CONTEXT} ${GPUS_SETTING} -lv ${LOG_VERBOSE} --mmap " -ZES_ENABLE_SYSMAN=1 ${BIN_FILE} -m ${MODEL_FILE} -no-cnv -p "${INPUT_PROMPT}" -n 200 -e -ngl ${NGL} -s ${SEED} -c ${CONTEXT} ${GPUS_SETTING} -lv ${LOG_VERBOSE} --mmap +echo "run cmd: ZES_ENABLE_SYSMAN=1 ${BIN_FILE} -m ${MODEL_FILE} -no-cnv -p "${INPUT_PROMPT}" -n 200 -e -ngl ${NGL} -s ${SEED} -c ${CONTEXT} ${GPUS_SETTING} -lv ${LOG_VERBOSE} --device ${SYCL_DEVICES} --mmap " +ZES_ENABLE_SYSMAN=1 ${BIN_FILE} -m ${MODEL_FILE} -no-cnv -p "${INPUT_PROMPT}" -n 200 -e -ngl ${NGL} -s ${SEED} -c ${CONTEXT} ${GPUS_SETTING} -lv ${LOG_VERBOSE} --device ${SYCL_DEVICES} --mmap diff --git a/examples/sycl/win-start-svr.bat b/examples/sycl/win-start-svr.bat index 13b5159e002..80771058930 100644 --- a/examples/sycl/win-start-svr.bat +++ b/examples/sycl/win-start-svr.bat @@ -13,6 +13,7 @@ set "MODEL_FILE=..\models\Qwen3.5-4B-Q4_0.gguf" set "NGL=99" set "CONTEXT=4096" set "GGML_SYCL_DEVICE=-1" +set "SYCL_DEVICES=SYCL0" set "SPLIT_MODE=layer" set "LOG_VERBOSE=3" @@ -36,6 +37,21 @@ if /I "%~1"=="--context" ( goto parse_args ) +if /I "%~1"=="-d" ( + if "%~2"=="" goto missing_value + set "SYCL_DEVICES=%~2" + shift + shift + goto parse_args +) +if /I "%~1"=="--device" ( + if "%~2"=="" goto missing_value + set "SYCL_DEVICES=%~2" + shift + shift + goto parse_args +) + if /I "%~1"=="-m" ( if "%~2"=="" goto missing_value set "MODEL_FILE=%~2" @@ -130,6 +146,7 @@ echo This script processes files with specified options. echo. echo Options: echo -h, --help Display this help message and exit. +echo -d, --device ^ Set SYCL devices (default: SYCL0). echo -c, --context ^ Set context length. Bigger need more memory. echo -m, --model ^ Full model file path. echo -mg,--main-gpu ^ Set main GPU ID (0 - n) for single GPU mode. @@ -160,19 +177,20 @@ REM Support malloc device memory more than 4GB. set "UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS=1" echo UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS=%UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS% +echo ONEAPI_DEVICE_SELECTOR=%ONEAPI_DEVICE_SELECTOR% + if not "%GGML_SYCL_DEVICE%"=="-1" ( echo Use %GGML_SYCL_DEVICE% as main GPU REM Use single GPU only. set "GPUS_SETTING=-mg %GGML_SYCL_DEVICE% -sm %SPLIT_MODE%" - echo ONEAPI_DEVICE_SELECTOR=%ONEAPI_DEVICE_SELECTOR% -) else ( - echo Use all Intel GPUs, including iGPU ^& dGPU + ) else ( + echo Use Intel GPUs: %SYCL_DEVICES% set "GPUS_SETTING=-sm %SPLIT_MODE%" ) -echo run cmd: ZES_ENABLE_SYSMAN=1 %BIN_FILE% -m "%MODEL_FILE%" -ngl %NGL% -s %SEED% -c %CONTEXT% %GPUS_SETTING% -lv %LOG_VERBOSE% --mmap --host 0.0.0.0 --port 8000 +echo run cmd: ZES_ENABLE_SYSMAN=1 %BIN_FILE% -m "%MODEL_FILE%" -ngl %NGL% -s %SEED% -c %CONTEXT% %GPUS_SETTING% -lv %LOG_VERBOSE% --device %SYCL_DEVICES% --mmap --host 0.0.0.0 --port 8000 set "ZES_ENABLE_SYSMAN=1" -%BIN_FILE% -m "%MODEL_FILE%" -ngl %NGL% -s %SEED% -c %CONTEXT% %GPUS_SETTING% -lv %LOG_VERBOSE% --mmap --host 0.0.0.0 --port 8000 +%BIN_FILE% -m "%MODEL_FILE%" -ngl %NGL% -s %SEED% -c %CONTEXT% %GPUS_SETTING% -lv %LOG_VERBOSE% --device "%SYCL_DEVICES%" --mmap --host 0.0.0.0 --port 8000 endlocal diff --git a/examples/sycl/win-test.bat b/examples/sycl/win-test.bat index 39640908b07..cc6da441388 100644 --- a/examples/sycl/win-test.bat +++ b/examples/sycl/win-test.bat @@ -19,6 +19,7 @@ set "MODEL_FILE=..\models\llama-2-7b.Q4_0.gguf" set "NGL=99" set "CONTEXT=4096" set "GGML_SYCL_DEVICE=-1" +set "SYCL_DEVICES=SYCL0" set "SPLIT_MODE=layer" set "LOG_VERBOSE=3" @@ -42,6 +43,21 @@ if /I "%~1"=="--context" ( goto parse_args ) +if /I "%~1"=="-d" ( + if "%~2"=="" goto missing_value + set "SYCL_DEVICES=%~2" + shift + shift + goto parse_args +) +if /I "%~1"=="--device" ( + if "%~2"=="" goto missing_value + set "SYCL_DEVICES=%~2" + shift + shift + goto parse_args +) + if /I "%~1"=="-p" ( if "%~2"=="" goto missing_value set "INPUT_PROMPT=%~2" @@ -151,6 +167,7 @@ echo This script processes files with specified options. echo. echo Options: echo -h, --help Display this help message and exit. +echo -d, --device ^ Set SYCL devices (default: SYCL0). echo -c, --context ^ Set context length. Bigger need more memory. echo -p, --promote ^ Prompt to start generation with. echo -m, --model ^ Full model file path. @@ -182,19 +199,21 @@ REM Support malloc device memory more than 4GB. set "UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS=1" echo UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS=%UR_L0_ENABLE_RELAXED_ALLOCATION_LIMITS% +echo ONEAPI_DEVICE_SELECTOR=%ONEAPI_DEVICE_SELECTOR% + if not "%GGML_SYCL_DEVICE%"=="-1" ( echo Use %GGML_SYCL_DEVICE% as main GPU REM Use single GPU only. set "GPUS_SETTING=-mg %GGML_SYCL_DEVICE% -sm %SPLIT_MODE%" - echo ONEAPI_DEVICE_SELECTOR=%ONEAPI_DEVICE_SELECTOR% -) else ( - echo Use all Intel GPUs, including iGPU ^& dGPU + ) +else ( + echo Use Intel GPUs: %SYCL_DEVICES% set "GPUS_SETTING=-sm %SPLIT_MODE%" ) -echo run cmd: ZES_ENABLE_SYSMAN=1 %BIN_FILE% -m %MODEL_FILE% -no-cnv -p "%INPUT_PROMPT%" -n 200 -e -ngl %NGL% -s %SEED% -c %CONTEXT% %GPUS_SETTING% -lv %LOG_VERBOSE% --mmap +echo run cmd: ZES_ENABLE_SYSMAN=1 %BIN_FILE% -m %MODEL_FILE% -no-cnv -p "%INPUT_PROMPT%" -n 200 -e -ngl %NGL% -s %SEED% -c %CONTEXT% %GPUS_SETTING% -lv %LOG_VERBOSE% --device %SYCL_DEVICES% --mmap set "ZES_ENABLE_SYSMAN=1" -%BIN_FILE% -m "%MODEL_FILE%" -no-cnv -p "%INPUT_PROMPT%" -n 200 -e -ngl %NGL% -s %SEED% -c %CONTEXT% %GPUS_SETTING% -lv %LOG_VERBOSE% --mmap +%BIN_FILE% -m "%MODEL_FILE%" -no-cnv -p "%INPUT_PROMPT%" -n 200 -e -ngl %NGL% -s %SEED% -c %CONTEXT% %GPUS_SETTING% -lv %LOG_VERBOSE% --device "%SYCL_DEVICES%" --mmap endlocal diff --git a/ggml/CMakeLists.txt b/ggml/CMakeLists.txt index 6c7337edd39..1b1de6b7d45 100644 --- a/ggml/CMakeLists.txt +++ b/ggml/CMakeLists.txt @@ -4,8 +4,8 @@ project("ggml" C CXX ASM) ### GGML Version set(GGML_VERSION_MAJOR 0) -set(GGML_VERSION_MINOR 18) -set(GGML_VERSION_PATCH 1) +set(GGML_VERSION_MINOR 19) +set(GGML_VERSION_PATCH 0) set(GGML_VERSION_BASE "${GGML_VERSION_MAJOR}.${GGML_VERSION_MINOR}.${GGML_VERSION_PATCH}") list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/") diff --git a/ggml/src/ggml-cpu/arch/arm/cpu-feats.cpp b/ggml/src/ggml-cpu/arch/arm/cpu-feats.cpp index adfbd2e4e9b..a64ad7a3c74 100644 --- a/ggml/src/ggml-cpu/arch/arm/cpu-feats.cpp +++ b/ggml/src/ggml-cpu/arch/arm/cpu-feats.cpp @@ -8,6 +8,22 @@ #include #endif +#if !defined(HWCAP_FPHP) +#define HWCAP_FPHP (1 << 9) +#endif + +#if !defined(HWCAP_ASIMDHP) +#define HWCAP_ASIMDHP (1 << 10) +#endif + +#if !defined(HWCAP_ASIMDDP) +#define HWCAP_ASIMDDP (1 << 20) +#endif + +#if !defined(HWCAP_SVE) +#define HWCAP_SVE (1 << 22) +#endif + #if !defined(HWCAP2_SVE2) #define HWCAP2_SVE2 (1 << 1) #endif @@ -23,7 +39,7 @@ struct aarch64_features { // has_neon not needed, aarch64 has NEON guaranteed bool has_dotprod = false; - bool has_fp16_va = false; + bool has_fp16 = false; bool has_sve = false; bool has_sve2 = false; bool has_i8mm = false; @@ -36,7 +52,7 @@ struct aarch64_features { uint32_t hwcap2 = getauxval(AT_HWCAP2); has_dotprod = !!(hwcap & HWCAP_ASIMDDP); - has_fp16_va = !!(hwcap & HWCAP_FPHP); + has_fp16 = !!(hwcap & HWCAP_FPHP) && !!(hwcap & HWCAP_ASIMDHP); has_sve = !!(hwcap & HWCAP_SVE); has_sve2 = !!(hwcap2 & HWCAP2_SVE2); has_i8mm = !!(hwcap2 & HWCAP2_I8MM); @@ -75,7 +91,7 @@ static int ggml_backend_cpu_aarch64_score() { score += 1<<1; #endif #ifdef GGML_USE_FP16_VECTOR_ARITHMETIC - if (!af.has_fp16_va) { return 0; } + if (!af.has_fp16) { return 0; } score += 1<<2; #endif #ifdef GGML_USE_SVE diff --git a/ggml/src/ggml-cpu/spacemit/ime.cpp b/ggml/src/ggml-cpu/spacemit/ime.cpp index 9563ea3e4bd..29d683270e5 100644 --- a/ggml/src/ggml-cpu/spacemit/ime.cpp +++ b/ggml/src/ggml-cpu/spacemit/ime.cpp @@ -195,6 +195,7 @@ template class tensor_ case GGML_TYPE_Q4_K: case GGML_TYPE_Q6_K: case GGML_TYPE_Q8_0: + case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: case GGML_TYPE_Q5_K: //case GGML_TYPE_MXFP4: @@ -214,6 +215,7 @@ template class tensor_ case GGML_TYPE_Q4_K: case GGML_TYPE_Q6_K: case GGML_TYPE_Q8_0: + case GGML_TYPE_Q5_0: case GGML_TYPE_Q5_1: case GGML_TYPE_Q5_K: //case GGML_TYPE_MXFP4: diff --git a/ggml/src/ggml-cuda/cpy.cu b/ggml/src/ggml-cuda/cpy.cu index eb5eb0eb4eb..fd7ffc0bc55 100644 --- a/ggml/src/ggml-cuda/cpy.cu +++ b/ggml/src/ggml-cuda/cpy.cu @@ -253,9 +253,9 @@ static void ggml_cpy_f32_q8_0_cuda( const int64_t nb03, const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t nb10, const int64_t nb11, const int64_t nb12, const int64_t nb13, cudaStream_t stream) { GGML_ASSERT(ne % QK8_0 == 0); - const int64_t num_blocks = ne / QK8_0; + const int64_t num_blocks = (ne/QK8_0 + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE; GGML_ASSERT(num_blocks <= INT_MAX); - cpy_f32_q<<>> + cpy_f32_q<<>> (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); } @@ -264,9 +264,9 @@ static void ggml_cpy_q8_0_f32_cuda( const int64_t ne00, const int64_t ne01, const int64_t ne02, const int64_t nb00, const int64_t nb01, const int64_t nb02, const int64_t nb03, const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t nb10, const int64_t nb11, const int64_t nb12, const int64_t nb13, cudaStream_t stream) { - const int64_t num_blocks = ne; + const int64_t num_blocks = (ne/QK8_0 + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE; GGML_ASSERT(num_blocks <= INT_MAX); - cpy_q_f32<<>> + cpy_q_f32<<>> (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); } @@ -276,9 +276,9 @@ static void ggml_cpy_f32_q4_0_cuda( const int64_t nb03, const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t nb10, const int64_t nb11, const int64_t nb12, const int64_t nb13, cudaStream_t stream) { GGML_ASSERT(ne % QK4_0 == 0); - const int64_t num_blocks = ne / QK4_0; + const int64_t num_blocks = (ne/QK4_0 + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE; GGML_ASSERT(num_blocks <= INT_MAX); - cpy_f32_q<<>> + cpy_f32_q<<>> (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); } @@ -289,9 +289,9 @@ static void ggml_cpy_q4_0_f32_cuda( const int64_t nb03, const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t nb10, const int64_t nb11, const int64_t nb12, const int64_t nb13, cudaStream_t stream) { - const int64_t num_blocks = ne; + const int64_t num_blocks = (ne/QK4_0 + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE; GGML_ASSERT(num_blocks <= INT_MAX); - cpy_q_f32, QK4_0><<>>( + cpy_q_f32, QK4_0><<>>( cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); } @@ -302,9 +302,9 @@ static void ggml_cpy_f32_q4_1_cuda( const int64_t nb03, const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t nb10, const int64_t nb11, const int64_t nb12, const int64_t nb13, cudaStream_t stream) { GGML_ASSERT(ne % QK4_1 == 0); - const int64_t num_blocks = ne / QK4_1; + const int64_t num_blocks = (ne/QK4_1 + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE; GGML_ASSERT(num_blocks <= INT_MAX); - cpy_f32_q<<>> + cpy_f32_q<<>> (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); } @@ -315,9 +315,9 @@ static void ggml_cpy_q4_1_f32_cuda( const int64_t nb03, const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t nb10, const int64_t nb11, const int64_t nb12, const int64_t nb13, cudaStream_t stream) { - const int64_t num_blocks = ne; + const int64_t num_blocks = (ne/QK4_1 + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE; GGML_ASSERT(num_blocks <= INT_MAX); - cpy_q_f32, QK4_1><<>>( + cpy_q_f32, QK4_1><<>>( cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); } @@ -328,9 +328,9 @@ static void ggml_cpy_f32_q5_0_cuda( const int64_t nb03, const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t nb10, const int64_t nb11, const int64_t nb12, const int64_t nb13, cudaStream_t stream) { GGML_ASSERT(ne % QK5_0 == 0); - const int64_t num_blocks = ne / QK5_0; + const int64_t num_blocks = (ne/QK5_0 + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE; GGML_ASSERT(num_blocks <= INT_MAX); - cpy_f32_q<<>> + cpy_f32_q<<>> (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); } @@ -341,9 +341,9 @@ static void ggml_cpy_q5_0_f32_cuda( const int64_t nb03, const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t nb10, const int64_t nb11, const int64_t nb12, const int64_t nb13, cudaStream_t stream) { - const int64_t num_blocks = ne; + const int64_t num_blocks = (ne/QK5_0 + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE; GGML_ASSERT(num_blocks <= INT_MAX); - cpy_q_f32, QK5_0><<>>( + cpy_q_f32, QK5_0><<>>( cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); } @@ -354,9 +354,9 @@ static void ggml_cpy_f32_q5_1_cuda( const int64_t nb03, const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t nb10, const int64_t nb11, const int64_t nb12, const int64_t nb13, cudaStream_t stream) { GGML_ASSERT(ne % QK5_1 == 0); - const int64_t num_blocks = ne / QK5_1; + const int64_t num_blocks = (ne/QK5_1 + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE; GGML_ASSERT(num_blocks <= INT_MAX); - cpy_f32_q<<>> + cpy_f32_q<<>> (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); } @@ -367,9 +367,9 @@ static void ggml_cpy_q5_1_f32_cuda( const int64_t nb03, const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t nb10, const int64_t nb11, const int64_t nb12, const int64_t nb13, cudaStream_t stream) { - const int64_t num_blocks = ne; + const int64_t num_blocks = (ne/QK5_1 + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE; GGML_ASSERT(num_blocks <= INT_MAX); - cpy_q_f32, QK5_1><<>>( + cpy_q_f32, QK5_1><<>>( cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); } @@ -380,9 +380,9 @@ static void ggml_cpy_f32_iq4_nl_cuda( const int64_t nb03, const int64_t ne10, const int64_t ne11, const int64_t ne12, const int64_t nb10, const int64_t nb11, const int64_t nb12, const int64_t nb13, cudaStream_t stream) { GGML_ASSERT(ne % QK4_NL == 0); - const int64_t num_blocks = ne / QK4_NL; + const int64_t num_blocks = (ne/QK4_NL + CUDA_CPY_BLOCK_SIZE - 1) / CUDA_CPY_BLOCK_SIZE; GGML_ASSERT(num_blocks <= INT_MAX); - cpy_f32_q<<>> + cpy_f32_q<<>> (cx, cdst, ne, ne00, ne01, ne02, nb00, nb01, nb02, nb03, ne10, ne11, ne12, nb10, nb11, nb12, nb13); } diff --git a/ggml/src/ggml-cuda/ggml-cuda.cu b/ggml/src/ggml-cuda/ggml-cuda.cu index 561ab7ac599..dec61932407 100644 --- a/ggml/src/ggml-cuda/ggml-cuda.cu +++ b/ggml/src/ggml-cuda/ggml-cuda.cu @@ -2651,6 +2651,52 @@ static bool ggml_cuda_should_fuse_rope_set_rows(const ggml_tensor * rope, return true; } +static bool ggml_cuda_should_fuse_rms_norm_mul_rope(const ggml_tensor * rms_norm, + const ggml_tensor * mul, + const ggml_tensor * rope) { + if (rms_norm->op != GGML_OP_RMS_NORM || mul->op != GGML_OP_MUL || rope->op != GGML_OP_ROPE) { + return false; + } + + if (rms_norm->src[0]->type != GGML_TYPE_F32 || rms_norm->type != GGML_TYPE_F32 || + mul->src[0]->type != GGML_TYPE_F32 || mul->src[1]->type != GGML_TYPE_F32 || + mul->type != GGML_TYPE_F32 || rope->type != GGML_TYPE_F32) { + return false; + } + + if (rope->src[0] != mul) { + return false; + } + + //if rms norm is the B operand, then we don't handle broadcast + if (rms_norm == mul->src[1] && !ggml_are_same_shape(mul->src[0], rms_norm)) { + return false; + } + + if (!ggml_are_same_shape(rms_norm, mul)) { + return false; + } + + //rms_norm kernel assumes contiguous rows + if (!ggml_is_contiguous_rows(rms_norm->src[0]) || + !ggml_is_contiguous_rows(mul->src[0]) || !ggml_is_contiguous_rows(mul->src[1])) { + return false; + } + + // the fused kernel handles the norm/neox rope modes only + const int mode = ((const int32_t *) rope->op_params)[2]; + if (mode != GGML_ROPE_TYPE_NORMAL && mode != GGML_ROPE_TYPE_NEOX) { + return false; + } + + const int n_dims = ((const int32_t *) rope->op_params)[1]; + if (n_dims % 2 != 0 || rope->src[0]->ne[0] % 2 != 0) { + return false; + } + + return true; +} + // match gated_delta_net + the strided cpy that scatters its state snapshots into the cache // (slot i -> rollback group i, slot 0 newest), so the kernel can write them and skip the cpy. static int ggml_cuda_try_gdn_cache_fusion( @@ -2980,6 +3026,36 @@ static bool ggml_cuda_can_fuse(const struct ggml_cgraph * cgraph, } } + std::initializer_list rms_norm_mul_rope_ops = { GGML_OP_RMS_NORM, GGML_OP_MUL, GGML_OP_ROPE }; + std::initializer_list rms_norm_mul_rope_set_rows_ops = { GGML_OP_RMS_NORM, GGML_OP_MUL, GGML_OP_ROPE, GGML_OP_VIEW, GGML_OP_SET_ROWS }; + + if (is_equal(rms_norm_mul_rope_set_rows_ops, ops) && ggml_can_fuse_subgraph(cgraph, node_idx, ops, { node_idx + 4 })) { + const ggml_tensor * rms_norm = cgraph->nodes[node_idx]; + const ggml_tensor * mul = cgraph->nodes[node_idx + 1]; + const ggml_tensor * rope = cgraph->nodes[node_idx + 2]; + const ggml_tensor * view = cgraph->nodes[node_idx + 3]; + const ggml_tensor * set_rows = cgraph->nodes[node_idx + 4]; + + if (ggml_check_edges(cgraph, node_idx, {{1, 0, 0}, {2, 0, 1}, {3, 0, 2}, {4, 0, 3}}) && + ggml_cuda_should_fuse_rms_norm_mul_rope(rms_norm, mul, rope) && + ggml_cuda_should_fuse_rope_set_rows(rope, view, set_rows)) { + int out_nodes[] = { node_idx + 4 }; + return ggml_cuda_check_fusion_memory_ranges(cgraph, node_idx, (int)ops.size(), out_nodes, 1); + } + } + + if (is_equal(rms_norm_mul_rope_ops, ops) && ggml_can_fuse(cgraph, node_idx, ops)) { + const ggml_tensor * rms_norm = cgraph->nodes[node_idx]; + const ggml_tensor * mul = cgraph->nodes[node_idx + 1]; + const ggml_tensor * rope = cgraph->nodes[node_idx + 2]; + + if (ggml_cuda_should_fuse_rms_norm_mul_rope(rms_norm, mul, rope)) { + int out_nodes[] = { node_idx + 2 }; + return ggml_cuda_check_fusion_memory_ranges(cgraph, node_idx, (int)ops.size(), out_nodes, 1); + } + return false; + } + std::initializer_list rope_set_rows_ops = { GGML_OP_ROPE, GGML_OP_VIEW, GGML_OP_SET_ROWS }; if (is_equal(rope_set_rows_ops, ops) && ggml_can_fuse_subgraph(cgraph, node_idx, ops, { node_idx + 2 })) { @@ -2988,7 +3064,8 @@ static bool ggml_cuda_can_fuse(const struct ggml_cgraph * cgraph, const ggml_tensor * set_rows = cgraph->nodes[node_idx + 2]; if (ggml_cuda_should_fuse_rope_set_rows(rope, view, set_rows)) { - return true; + int out_nodes[] = { node_idx + 2 }; + return ggml_cuda_check_fusion_memory_ranges(cgraph, node_idx, (int)ops.size(), out_nodes, 1); } } @@ -3840,6 +3917,16 @@ static int ggml_cuda_try_fuse(ggml_backend_cuda_context * cuda_ctx, ggml_cgraph return fused_node_count - 1; } + if (ggml_cuda_can_fuse(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL, GGML_OP_ROPE, GGML_OP_VIEW, GGML_OP_SET_ROWS }, {})) { + ggml_cuda_op_rms_norm_mul_rope_fused(*cuda_ctx, node, cgraph->nodes[i + 1], cgraph->nodes[i + 2], cgraph->nodes[i + 4]); + return 4; + } + + if (ggml_cuda_can_fuse(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL, GGML_OP_ROPE }, {})) { + ggml_cuda_op_rms_norm_mul_rope_fused(*cuda_ctx, node, cgraph->nodes[i + 1], cgraph->nodes[i + 2], nullptr); + return 2; + } + if (ggml_cuda_can_fuse(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL, GGML_OP_ADD }, {})) { ggml_cuda_op_rms_norm_fused_add(*cuda_ctx, node, cgraph->nodes[i + 1], cgraph->nodes[i + 2]); return 2; @@ -4033,7 +4120,11 @@ static void ggml_cuda_graph_evaluate_and_capture(ggml_backend_cuda_context * cud continue; } #ifndef NDEBUG - assert(node->buffer->buft == ggml_backend_cuda_buffer_type(cuda_ctx->device)); + // On integrated GPUs (APUs, e.g. RDNA3.5) the scheduler may place a + // node's output on the host-visible buffer, which the compute path + // handles. Allow that here, mirroring the src-tensor check below. + assert(node->buffer->buft == ggml_backend_cuda_buffer_type(cuda_ctx->device) || + (integrated && ggml_backend_buft_is_cuda_host(node->buffer->buft))); for (int j = 0; j < GGML_MAX_SRC; j++) { if (node->src[j] != nullptr) { assert(node->src[j]->buffer); @@ -5205,6 +5296,7 @@ static bool ggml_backend_cuda_device_offload_op(ggml_backend_dev_t dev, const gg static ggml_backend_event_t ggml_backend_cuda_device_event_new(ggml_backend_dev_t dev) { #ifdef GGML_CUDA_NO_PEER_COPY + GGML_UNUSED(dev); return nullptr; #else ggml_backend_cuda_device_context * dev_ctx = (ggml_backend_cuda_device_context *)dev->context; diff --git a/ggml/src/ggml-cuda/quantize.cu b/ggml/src/ggml-cuda/quantize.cu index 2bd9b626239..bcc7723957b 100644 --- a/ggml/src/ggml-cuda/quantize.cu +++ b/ggml/src/ggml-cuda/quantize.cu @@ -8,7 +8,6 @@ struct __builtin_align__(32) float8 { float x; float y; float z; float w; float p; float q; float r; float s; }; -#endif #if CUDART_VERSION >= 12080 static __device__ __forceinline__ float nvfp4_native_scale_error( @@ -49,6 +48,7 @@ static __device__ __forceinline__ float nvfp4_native_scale_error( return err; } #endif // CUDART_VERSION >= 12080 +#endif // defined(BLACKWELL_MMA_AVAILABLE) __launch_bounds__(CUDA_QUANTIZE_BLOCK_SIZE, 1) static __global__ void quantize_q8_1( diff --git a/ggml/src/ggml-cuda/rope.cu b/ggml/src/ggml-cuda/rope.cu index e20a5cb6bed..504c6b818d4 100644 --- a/ggml/src/ggml-cuda/rope.cu +++ b/ggml/src/ggml-cuda/rope.cu @@ -670,3 +670,238 @@ void ggml_cuda_op_rope_back(ggml_backend_cuda_context & ctx, ggml_tensor * dst) void ggml_cuda_op_rope_fused(ggml_backend_cuda_context & ctx, ggml_tensor * rope, ggml_tensor * set_rows) { ggml_cuda_op_rope_impl(ctx, rope, set_rows); } + +// fused RMS_NORM + MUL + ROPE (+ VIEW + SET_ROWS) +// one block per row: block_reduce gives the norm scale, then each thread applies mul and rope to the elements it owns +template +static __global__ void rms_norm_mul_rope_f32( + const float * x, D * dst, const int ncols, + const int64_t s01, const int64_t s02, const int64_t s03, + const int64_t s1, const int64_t s2, const int64_t s3, + const float eps, + const float * mul, + const int64_t mul_s01, const int64_t mul_s02, const int64_t mul_s03, + const uint3 mul_ncols_packed, const uint3 mul_nrows_packed, + const uint3 mul_nchannels_packed, const uint3 mul_nsamples_packed, + const int n_dims, const int32_t * pos, + const float freq_scale, const float ext_factor, const float attn_factor, + const rope_corr_dims corr_dims, const float theta_scale, + const float * freq_factors, + const int64_t * row_indices, const int set_rows_stride, + const bool is_neox) { + ggml_cuda_pdl_lc(); + const int row = blockIdx.x; + const int channel = blockIdx.y; + const int sample = blockIdx.z; + const int tid = threadIdx.x; + + x += sample*s03 + channel*s02 + row*s01; + + const uint32_t mul_row = fastmodulo(row, mul_nrows_packed); + const uint32_t mul_channel = fastmodulo(channel, mul_nchannels_packed); + const uint32_t mul_sample = fastmodulo(sample, mul_nsamples_packed); + mul += mul_sample*mul_s03 + mul_channel*mul_s02 + mul_row*mul_s01; + + float tmp = 0.0f; + + ggml_cuda_pdl_sync(); + for (int col = tid; col < ncols; col += block_size) { + const float xi = x[col]; + tmp += xi * xi; + } + + extern __shared__ float s_sum[]; + tmp = block_reduce(tmp, s_sum); + + const float scale = rsqrtf(tmp/ncols + eps); + + int64_t idst = sample*s3 + channel*s2 + row*s1; + if (set_rows_stride != 0) { + idst = row*s1 + row_indices[channel]*set_rows_stride; + } + dst += idst; + + for (int i0 = 2*tid; i0 < ncols; i0 += 2*block_size) { + int ix0; + int ix1; + if (is_neox && i0 < n_dims) { + ix0 = i0/2; + ix1 = i0/2 + n_dims/2; + } else { + ix0 = i0 + 0; + ix1 = i0 + 1; + } + + const float x0 = scale * x[ix0] * mul[fastmodulo(ix0, mul_ncols_packed)]; + const float x1 = scale * x[ix1] * mul[fastmodulo(ix1, mul_ncols_packed)]; + + if (i0 >= n_dims) { + dst[ix0] = ggml_cuda_cast(x0); + dst[ix1] = ggml_cuda_cast(x1); + continue; + } + + const float theta_base = pos[channel]*powf(theta_scale, i0/2.0f); + const float freq_factor = has_ff ? freq_factors[i0/2] : 1.0f; + + float cos_theta; + float sin_theta; + rope_yarn(theta_base/freq_factor, freq_scale, corr_dims, i0, ext_factor, attn_factor, cos_theta, sin_theta); + + dst[ix0] = ggml_cuda_cast(x0*cos_theta - x1*sin_theta); + dst[ix1] = ggml_cuda_cast(x0*sin_theta + x1*cos_theta); + } +} + +template +static void rms_norm_mul_rope_cuda( + const float * x, D * dst, + const int ncols, const int nrows, const int nchannels, const int nsamples, + const int64_t s01, const int64_t s02, const int64_t s03, + const int64_t s1, const int64_t s2, const int64_t s3, + const float eps, + const float * mul, + const int64_t mul_s01, const int64_t mul_s02, const int64_t mul_s03, + const uint32_t mul_ncols, const uint32_t mul_nrows, + const uint32_t mul_nchannels, const uint32_t mul_nsamples, + const int n_dims, const int32_t * pos, + const float freq_scale, const float freq_base, const float ext_factor, const float attn_factor, + const rope_corr_dims corr_dims, + const float * freq_factors, + const int64_t * row_indices, const int set_rows_stride, + const bool is_neox, cudaStream_t stream) { + GGML_ASSERT(ncols % 2 == 0); + + const dim3 blocks_num(nrows, nchannels, nsamples); + + const float theta_scale = powf(freq_base, -2.0f/n_dims); + + const uint3 mul_ncols_packed = init_fastdiv_values(mul_ncols); + const uint3 mul_nrows_packed = init_fastdiv_values(mul_nrows); + const uint3 mul_nchannels_packed = init_fastdiv_values(mul_nchannels); + const uint3 mul_nsamples_packed = init_fastdiv_values(mul_nsamples); + + if (ncols < 1024) { + const dim3 block_dims(256, 1, 1); + const ggml_cuda_kernel_launch_params launch_params = {blocks_num, block_dims, 32*sizeof(float), stream}; + if (freq_factors == nullptr) { + ggml_cuda_kernel_launch(rms_norm_mul_rope_f32<256, false, D>, launch_params, + x, dst, ncols, s01, s02, s03, s1, s2, s3, eps, mul, mul_s01, mul_s02, mul_s03, + mul_ncols_packed, mul_nrows_packed, mul_nchannels_packed, mul_nsamples_packed, + n_dims, pos, freq_scale, ext_factor, attn_factor, corr_dims, theta_scale, + freq_factors, row_indices, set_rows_stride, is_neox); + } else { + ggml_cuda_kernel_launch(rms_norm_mul_rope_f32<256, true, D>, launch_params, + x, dst, ncols, s01, s02, s03, s1, s2, s3, eps, mul, mul_s01, mul_s02, mul_s03, + mul_ncols_packed, mul_nrows_packed, mul_nchannels_packed, mul_nsamples_packed, + n_dims, pos, freq_scale, ext_factor, attn_factor, corr_dims, theta_scale, + freq_factors, row_indices, set_rows_stride, is_neox); + } + } else { + const dim3 block_dims(1024, 1, 1); + const ggml_cuda_kernel_launch_params launch_params = {blocks_num, block_dims, 32*sizeof(float), stream}; + if (freq_factors == nullptr) { + ggml_cuda_kernel_launch(rms_norm_mul_rope_f32<1024, false, D>, launch_params, + x, dst, ncols, s01, s02, s03, s1, s2, s3, eps, mul, mul_s01, mul_s02, mul_s03, + mul_ncols_packed, mul_nrows_packed, mul_nchannels_packed, mul_nsamples_packed, + n_dims, pos, freq_scale, ext_factor, attn_factor, corr_dims, theta_scale, + freq_factors, row_indices, set_rows_stride, is_neox); + } else { + ggml_cuda_kernel_launch(rms_norm_mul_rope_f32<1024, true, D>, launch_params, + x, dst, ncols, s01, s02, s03, s1, s2, s3, eps, mul, mul_s01, mul_s02, mul_s03, + mul_ncols_packed, mul_nrows_packed, mul_nchannels_packed, mul_nsamples_packed, + n_dims, pos, freq_scale, ext_factor, attn_factor, corr_dims, theta_scale, + freq_factors, row_indices, set_rows_stride, is_neox); + } + } +} + +void ggml_cuda_op_rms_norm_mul_rope_fused(ggml_backend_cuda_context & ctx, + ggml_tensor * rms_norm, ggml_tensor * mul, ggml_tensor * rope, ggml_tensor * set_rows) { + const ggml_tensor * x = rms_norm->src[0]; + const ggml_tensor * mul_src = mul->src[0] == rms_norm ? mul->src[1] : mul->src[0]; + + float eps = 0.0f; + memcpy(&eps, rms_norm->op_params, sizeof(float)); + GGML_ASSERT(eps >= 0.0f); + + GGML_ASSERT(x->type == GGML_TYPE_F32); + GGML_ASSERT(mul_src->type == GGML_TYPE_F32); + GGML_ASSERT(rope->type == GGML_TYPE_F32); + + void * dst_d = rope->data; + ggml_type dst_type = rope->type; + const int64_t * row_indices = nullptr; + int set_rows_stride = 0; + + if (set_rows != nullptr) { + dst_d = set_rows->data; + dst_type = set_rows->type; + row_indices = (const int64_t *) set_rows->src[1]->data; + set_rows_stride = set_rows->nb[1] / ggml_type_size(set_rows->type); + } + + const int n_dims = ((const int32_t *) rope->op_params)[1]; + const int mode = ((const int32_t *) rope->op_params)[2]; + const int n_ctx_orig = ((const int32_t *) rope->op_params)[4]; + + float freq_base; + float freq_scale; + float ext_factor; + float attn_factor; + float beta_fast; + float beta_slow; + + memcpy(&freq_base, (const int32_t *) rope->op_params + 5, sizeof(float)); + memcpy(&freq_scale, (const int32_t *) rope->op_params + 6, sizeof(float)); + memcpy(&ext_factor, (const int32_t *) rope->op_params + 7, sizeof(float)); + memcpy(&attn_factor, (const int32_t *) rope->op_params + 8, sizeof(float)); + memcpy(&beta_fast, (const int32_t *) rope->op_params + 9, sizeof(float)); + memcpy(&beta_slow, (const int32_t *) rope->op_params + 10, sizeof(float)); + + const bool is_neox = mode & GGML_ROPE_TYPE_NEOX; + + const int32_t * pos = (const int32_t *) rope->src[1]->data; + + const float * freq_factors = rope->src[2] != nullptr ? (const float *) rope->src[2]->data : nullptr; + + rope_corr_dims corr_dims; + ggml_rope_yarn_corr_dims(n_dims, n_ctx_orig, freq_base, beta_fast, beta_slow, corr_dims.v); + + const size_t ts0 = ggml_type_size(x->type); + GGML_ASSERT(x->nb[0] == ts0); + const int64_t s01 = x->nb[1] / ts0; + const int64_t s02 = x->nb[2] / ts0; + const int64_t s03 = x->nb[3] / ts0; + + const size_t ts_mul = ggml_type_size(mul_src->type); + GGML_ASSERT(mul_src->nb[0] == ts_mul); + const int64_t mul_s01 = mul_src->nb[1] / ts_mul; + const int64_t mul_s02 = mul_src->nb[2] / ts_mul; + const int64_t mul_s03 = mul_src->nb[3] / ts_mul; + + const size_t ts_dst = ggml_type_size(rope->type); + const int64_t s1 = rope->nb[1] / ts_dst; + const int64_t s2 = rope->nb[2] / ts_dst; + const int64_t s3 = rope->nb[3] / ts_dst; + + cudaStream_t stream = ctx.stream(); + + if (dst_type == GGML_TYPE_F32) { + rms_norm_mul_rope_cuda((const float *) x->data, (float *) dst_d, + x->ne[0], x->ne[1], x->ne[2], x->ne[3], s01, s02, s03, s1, s2, s3, eps, + (const float *) mul_src->data, mul_s01, mul_s02, mul_s03, + mul_src->ne[0], mul_src->ne[1], mul_src->ne[2], mul_src->ne[3], + n_dims, pos, freq_scale, freq_base, ext_factor, attn_factor, corr_dims, + freq_factors, row_indices, set_rows_stride, is_neox, stream); + } else if (dst_type == GGML_TYPE_F16) { + rms_norm_mul_rope_cuda((const float *) x->data, (half *) dst_d, + x->ne[0], x->ne[1], x->ne[2], x->ne[3], s01, s02, s03, s1, s2, s3, eps, + (const float *) mul_src->data, mul_s01, mul_s02, mul_s03, + mul_src->ne[0], mul_src->ne[1], mul_src->ne[2], mul_src->ne[3], + n_dims, pos, freq_scale, freq_base, ext_factor, attn_factor, corr_dims, + freq_factors, row_indices, set_rows_stride, is_neox, stream); + } else { + GGML_ABORT("fatal error"); + } +} diff --git a/ggml/src/ggml-cuda/rope.cuh b/ggml/src/ggml-cuda/rope.cuh index 72af086cd1b..7ce2d71c508 100644 --- a/ggml/src/ggml-cuda/rope.cuh +++ b/ggml/src/ggml-cuda/rope.cuh @@ -7,3 +7,5 @@ void ggml_cuda_op_rope(ggml_backend_cuda_context & ctx, ggml_tensor * dst); void ggml_cuda_op_rope_back(ggml_backend_cuda_context & ctx, ggml_tensor * dst); void ggml_cuda_op_rope_fused(ggml_backend_cuda_context & ctx, ggml_tensor * dst, ggml_tensor * set_rows); + +void ggml_cuda_op_rms_norm_mul_rope_fused(ggml_backend_cuda_context & ctx, ggml_tensor * rms_norm, ggml_tensor * mul, ggml_tensor * rope, ggml_tensor * set_rows); diff --git a/ggml/src/ggml-metal/ggml-metal-ops.cpp b/ggml/src/ggml-metal/ggml-metal-ops.cpp index c5d7619c12f..6d324056dd2 100644 --- a/ggml/src/ggml-metal/ggml-metal-ops.cpp +++ b/ggml/src/ggml-metal/ggml-metal-ops.cpp @@ -3816,7 +3816,7 @@ int ggml_metal_op_norm(ggml_metal_op_t ctx, int idx) { } nth = std::min(nth, ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)); - nth = std::min(nth, args.ne00_t); + nth = std::min(nth, (args.ne00_t + 31)/32*32); const size_t smem = pipeline.smem; diff --git a/ggml/src/ggml-metal/ggml-metal.metal b/ggml/src/ggml-metal/ggml-metal.metal index 7d12cb0fe39..92258b73749 100644 --- a/ggml/src/ggml-metal/ggml-metal.metal +++ b/ggml/src/ggml-metal/ggml-metal.metal @@ -11328,8 +11328,8 @@ kernel void kernel_lightning_indexer( const int i_kv_0 = tgpig.x*NK; // first key of this threadgroup const int i_kv = i_kv_0 + sgitg*NKPSG; // first key of this simdgroup - threadgroup half4x4 sk4x4[NK*DK16]; - threadgroup half * sk = (threadgroup half *) sk4x4; + threadgroup half sk[NK * DK16 * 16]; + threadgroup half4x4 * sk4x4 = (threadgroup half4x4 *) sk; for (short i = tiitg; i < NK*DK16; i += NTG) { const short ik = i/DK16; diff --git a/ggml/src/ggml-sycl/common.hpp b/ggml/src/ggml-sycl/common.hpp index 619933e0fda..4fa34a526f6 100644 --- a/ggml/src/ggml-sycl/common.hpp +++ b/ggml/src/ggml-sycl/common.hpp @@ -1022,9 +1022,20 @@ static T block_reduce(T val, T * shared_vals, int block_size_template) { } static __dpct_inline__ float ggml_sycl_ue4m3_to_fp32(uint8_t x) { - const uint32_t bits = x * (x != 0x7F && x != 0xFF); - const __nv_fp8_e4m3 xf = *reinterpret_cast(&bits); - return static_cast(xf) / 2; + // UE4M3 is unsigned: 4 exp bits (bias 7), 3 mantissa bits, no sign, no NaN. + // exp == 0xF is a valid exponent (256-448 range), not NaN. + if (x == 0 || x == 0x7F) { + return 0.0f; + } + const int exp = (x >> 3) & 0xF; + const int man = x & 0x7; + float raw; + if (exp == 0) { + raw = man * (1.0f / 8.0f) * sycl::pow(2.0f, -6.0f); + } else { + raw = (1.0f + man / 8.0f) * sycl::pow(2.0f, (float) exp - 7.0f); + } + return raw * 0.5f; } #endif // GGML_SYCL_COMMON_HPP diff --git a/ggml/src/ggml-sycl/dsv4-hc.cpp b/ggml/src/ggml-sycl/dsv4-hc.cpp new file mode 100644 index 00000000000..bb66e8c1b43 --- /dev/null +++ b/ggml/src/ggml-sycl/dsv4-hc.cpp @@ -0,0 +1,280 @@ +#include "ggml-impl.h" +#include "dsv4-hc.hpp" + +#include + +static constexpr int DSV4_HC = 4; + +static void dsv4_hc_pre_f32_sycl( + const float * x, const float * weights, float * dst, + int64_t n_embd, int64_t hc, int64_t n_tokens, + int64_t sx0, int64_t sx1, int64_t sx2, + int64_t sw0, int64_t sw1, + int64_t sd0, int64_t sd1, + queue_ptr stream) { + const int64_t nr = n_embd * n_tokens; + const int64_t block_size = 256; + const int64_t num_blocks = (nr + block_size - 1) / block_size; + + stream->parallel_for( + sycl::nd_range<1>(sycl::range<1>(num_blocks * block_size), sycl::range<1>(block_size)), + [=](sycl::nd_item<1> item) { + const int64_t ir = item.get_global_id(0); + if (ir >= nr) { + return; + } + + const int64_t i0 = ir % n_embd; + const int64_t it = ir / n_embd; + + float sum = x[i0*sx0 + it*sx2] * weights[it*sw1]; + for (int64_t ih = 1; ih < hc; ++ih) { + const float xv = x[i0*sx0 + ih*sx1 + it*sx2]; + const float wv = weights[ih*sw0 + it*sw1]; + sum += xv * wv; + } + + dst[i0*sd0 + it*sd1] = sum; + }); +} + +static void dsv4_hc_comb_norm_cols(float * comb, float eps) { + for (int idst = 0; idst < DSV4_HC; ++idst) { + float sum = eps; + for (int isrc = 0; isrc < DSV4_HC; ++isrc) { + sum += comb[idst + DSV4_HC*isrc]; + } + + const float inv_sum = 1.0f / sum; + for (int isrc = 0; isrc < DSV4_HC; ++isrc) { + comb[idst + DSV4_HC*isrc] *= inv_sum; + } + } +} + +static void dsv4_hc_comb_norm_rows(float * comb, float eps) { + for (int isrc = 0; isrc < DSV4_HC; ++isrc) { + float sum = eps; + for (int idst = 0; idst < DSV4_HC; ++idst) { + sum += comb[idst + DSV4_HC*isrc]; + } + + const float inv_sum = 1.0f / sum; + for (int idst = 0; idst < DSV4_HC; ++idst) { + comb[idst + DSV4_HC*isrc] *= inv_sum; + } + } +} + +static void dsv4_hc_comb_f32_sycl( + const float * mixes, + const float * scale, + const float * base, + float * dst, + int64_t n_tokens, + int64_t sm0, + int64_t sm1, + int64_t ss0, + int64_t sb0, + int64_t sd0, + int64_t sd1, + int64_t sd2, + float eps, + int32_t n_iter, + queue_ptr stream) { + constexpr int comb_offset = 2*DSV4_HC; + + const int64_t block_size = 256; + const int64_t num_blocks = (n_tokens + block_size - 1) / block_size; + + stream->parallel_for( + sycl::nd_range<1>(sycl::range<1>(num_blocks * block_size), sycl::range<1>(block_size)), + [=](sycl::nd_item<1> item_ct1) { + const int64_t it = item_ct1.get_global_id(0); + + if (it >= n_tokens) { + return; + } + + const float scale_comb = scale[2*ss0]; + float comb[DSV4_HC*DSV4_HC]; + + for (int isrc = 0; isrc < DSV4_HC; ++isrc) { + float max = -INFINITY; + for (int idst = 0; idst < DSV4_HC; ++idst) { + const int idx = idst + DSV4_HC*isrc; + const float v = mixes[(comb_offset + idx)*sm0 + it*sm1] * scale_comb + base[(comb_offset + idx)*sb0]; + comb[idx] = v; + max = fmaxf(max, v); + } + + float sum = 0.0f; + for (int idst = 0; idst < DSV4_HC; ++idst) { + const int idx = idst + DSV4_HC*isrc; + const float v = expf(comb[idx] - max); + comb[idx] = v; + sum += v; + } + + const float inv_sum = 1.0f / sum; + for (int idst = 0; idst < DSV4_HC; ++idst) { + const int idx = idst + DSV4_HC*isrc; + comb[idx] = comb[idx] * inv_sum + eps; + } + } + + dsv4_hc_comb_norm_cols(comb, eps); + for (int32_t i = 1; i < n_iter; ++i) { + dsv4_hc_comb_norm_rows(comb, eps); + dsv4_hc_comb_norm_cols(comb, eps); + } + + for (int isrc = 0; isrc < DSV4_HC; ++isrc) { + for (int idst = 0; idst < DSV4_HC; ++idst) { + const int idx = idst + DSV4_HC*isrc; + dst[idst*sd0 + isrc*sd1 + it*sd2] = comb[idx]; + } + } + }); +} + +static void dsv4_hc_post_f32_sycl( + const float * x, const float * residual, const float * post, const float * comb, float * dst, + int64_t n_embd, int64_t hc, int64_t n_tokens, + int64_t sx0, int64_t sx1, + int64_t sr0, int64_t sr1, int64_t sr2, + int64_t sp0, int64_t sp1, + int64_t sc0, int64_t sc1, int64_t sc2, + int64_t sd0, int64_t sd1, int64_t sd2, + queue_ptr stream) { + const int64_t nr = n_embd * hc * n_tokens; + const int64_t block_size = 256; + const int64_t num_blocks = (nr + block_size - 1) / block_size; + + stream->parallel_for( + sycl::nd_range<1>(sycl::range<1>(num_blocks * block_size), sycl::range<1>(block_size)), + [=](sycl::nd_item<1> item) { + const int64_t ir = item.get_global_id(0); + if (ir >= nr) { + return; + } + + const int64_t i0 = ir % n_embd; + const int64_t idst = (ir / n_embd) % hc; + const int64_t it = ir / (n_embd * hc); + + float sum = x[i0*sx0 + it*sx1] * post[idst*sp0 + it*sp1]; + for (int64_t isrc = 0; isrc < hc; ++isrc) { + sum += residual[i0*sr0 + isrc*sr1 + it*sr2] * comb[idst*sc0 + isrc*sc1 + it*sc2]; + } + + dst[i0*sd0 + idst*sd1 + it*sd2] = sum; + }); +} + +void ggml_sycl_op_dsv4_hc_pre(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { + scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/2); + const ggml_tensor * x = dst->src[0]; + const ggml_tensor * weights = dst->src[1]; + + GGML_ASSERT(x->type == GGML_TYPE_F32); + GGML_ASSERT(weights->type == GGML_TYPE_F32); + GGML_ASSERT(dst->type == GGML_TYPE_F32); + + GGML_TENSOR_LOCALS(size_t, nbx, x, nb); + GGML_TENSOR_LOCALS(size_t, nbw, weights, nb); + GGML_TENSOR_LOCALS(size_t, nbd, dst, nb); + + const int64_t n_embd = x->ne[0]; + const int64_t hc = x->ne[1]; + const int64_t n_tokens = x->ne[2]; + + queue_ptr stream = ctx.stream(); + + dsv4_hc_pre_f32_sycl( + (const float *) x->data, (const float *) weights->data, (float *) dst->data, + n_embd, hc, n_tokens, + nbx0 / sizeof(float), nbx1 / sizeof(float), nbx2 / sizeof(float), + nbw0 / sizeof(float), nbw1 / sizeof(float), + nbd0 / sizeof(float), nbd1 / sizeof(float), + stream); +} + +void ggml_sycl_op_dsv4_hc_comb(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { + scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/3); + + const ggml_tensor * mixes = dst->src[0]; + const ggml_tensor * scale = dst->src[1]; + const ggml_tensor * base = dst->src[2]; + + GGML_ASSERT(mixes->type == GGML_TYPE_F32); + GGML_ASSERT(scale->type == GGML_TYPE_F32); + GGML_ASSERT(base->type == GGML_TYPE_F32); + GGML_ASSERT(dst->type == GGML_TYPE_F32); + + constexpr int64_t hc_mix_dim = (2 + DSV4_HC)*DSV4_HC; + + GGML_ASSERT(mixes->ne[0] == hc_mix_dim); + GGML_ASSERT(dst->ne[0] == DSV4_HC); + GGML_ASSERT(dst->ne[1] == DSV4_HC); + GGML_ASSERT(dst->ne[2] == mixes->ne[1]); + GGML_ASSERT(scale->ne[0] >= 3); + GGML_ASSERT(base->ne[0] == hc_mix_dim); + + GGML_TENSOR_LOCALS(size_t, nbm, mixes, nb); + GGML_TENSOR_LOCALS(size_t, nbs, scale, nb); + GGML_TENSOR_LOCALS(size_t, nbb, base, nb); + GGML_TENSOR_LOCALS(size_t, nbd, dst, nb); + + const int64_t n_tokens = mixes->ne[1]; + const float eps = ggml_get_op_params_f32(dst, 0); + const int32_t n_iter = ggml_get_op_params_i32(dst, 1); + + queue_ptr stream = ctx.stream(); + + dsv4_hc_comb_f32_sycl( + (const float *) mixes->data, (const float *) scale->data, (const float *) base->data, (float *) dst->data, + n_tokens, + nbm0 / sizeof(float), nbm1 / sizeof(float), + nbs0 / sizeof(float), + nbb0 / sizeof(float), + nbd0 / sizeof(float), nbd1 / sizeof(float), nbd2 / sizeof(float), + eps, n_iter, stream); +} + +void ggml_sycl_op_dsv4_hc_post(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { + scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/4); + const ggml_tensor * x = dst->src[0]; + const ggml_tensor * residual = dst->src[1]; + const ggml_tensor * post = dst->src[2]; + const ggml_tensor * comb = dst->src[3]; + + GGML_ASSERT(x->type == GGML_TYPE_F32); + GGML_ASSERT(residual->type == GGML_TYPE_F32); + GGML_ASSERT(post->type == GGML_TYPE_F32); + GGML_ASSERT(comb->type == GGML_TYPE_F32); + GGML_ASSERT(dst->type == GGML_TYPE_F32); + + GGML_TENSOR_LOCALS(size_t, nbx, x, nb); + GGML_TENSOR_LOCALS(size_t, nbr, residual, nb); + GGML_TENSOR_LOCALS(size_t, nbp, post, nb); + GGML_TENSOR_LOCALS(size_t, nbc, comb, nb); + GGML_TENSOR_LOCALS(size_t, nbd, dst, nb); + + const int64_t n_embd = x->ne[0]; + const int64_t n_tokens = x->ne[1]; + const int64_t hc = residual->ne[1]; + + queue_ptr stream = ctx.stream(); + + dsv4_hc_post_f32_sycl( + (const float *) x->data, (const float *) residual->data, + (const float *) post->data, (const float *) comb->data, (float *) dst->data, + n_embd, hc, n_tokens, + nbx0 / sizeof(float), nbx1 / sizeof(float), + nbr0 / sizeof(float), nbr1 / sizeof(float), nbr2 / sizeof(float), + nbp0 / sizeof(float), nbp1 / sizeof(float), + nbc0 / sizeof(float), nbc1 / sizeof(float), nbc2 / sizeof(float), + nbd0 / sizeof(float), nbd1 / sizeof(float), nbd2 / sizeof(float), + stream); +} diff --git a/ggml/src/ggml-sycl/dsv4-hc.hpp b/ggml/src/ggml-sycl/dsv4-hc.hpp new file mode 100644 index 00000000000..330518d8a9f --- /dev/null +++ b/ggml/src/ggml-sycl/dsv4-hc.hpp @@ -0,0 +1,10 @@ +#ifndef GGML_SYCL_DSV4_HC_HPP +#define GGML_SYCL_DSV4_HC_HPP + +#include "common.hpp" + +void ggml_sycl_op_dsv4_hc_pre(ggml_backend_sycl_context & ctx, ggml_tensor * dst); +void ggml_sycl_op_dsv4_hc_comb(ggml_backend_sycl_context & ctx, ggml_tensor * dst); +void ggml_sycl_op_dsv4_hc_post(ggml_backend_sycl_context & ctx, ggml_tensor * dst); + +#endif // GGML_SYCL_DSV4_HC_HPP diff --git a/ggml/src/ggml-sycl/element_wise.cpp b/ggml/src/ggml-sycl/element_wise.cpp index 3cd055494ec..0e707d531be 100644 --- a/ggml/src/ggml-sycl/element_wise.cpp +++ b/ggml/src/ggml-sycl/element_wise.cpp @@ -420,53 +420,31 @@ static void clamp(const T * x, T * dst, const float min, const float max, const } } -template -static void gated_op_fused_geglu(const T * x, const T * g, T * dst, const uint64_t k, const sycl::uint3 n_fd, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) { - SYCL_GLOBAL_ID_LOOP(k, item_ct1) { - const sycl::uint2 rc = fast_div_modulo((uint32_t) i, n_fd); - const int64_t j0 = rc.x() * o0 + rc.y(); - const int64_t j1 = o0 == o1 ? j0 : rc.x() * o1 + rc.y(); - dst[i] = op_gelu(x[j0]) * g[j1]; - } -} - -template -static void gated_op_fused_reglu(const T * x, const T * g, T * dst, const uint64_t k, const sycl::uint3 n_fd, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) { +template +static void unary_gated_op_flat_kernel(const T * x, const T * g, T * dst, const uint64_t k, const sycl::nd_item<1> & item_ct1, F func) { SYCL_GLOBAL_ID_LOOP(k, item_ct1) { - const sycl::uint2 rc = fast_div_modulo((uint32_t) i, n_fd); - const int64_t j0 = rc.x() * o0 + rc.y(); - const int64_t j1 = o0 == o1 ? j0 : rc.x() * o1 + rc.y(); - dst[i] = op_relu(x[j0]) * g[j1]; + dst[i] = func(x[i]) * g[i]; } } -template -static void gated_op_fused_swiglu(const T * x, const T * g, T * dst, const uint64_t k, const sycl::uint3 n_fd, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) { - SYCL_GLOBAL_ID_LOOP(k, item_ct1) { - const sycl::uint2 rc = fast_div_modulo((uint32_t) i, n_fd); - const int64_t j0 = rc.x() * o0 + rc.y(); - const int64_t j1 = o0 == o1 ? j0 : rc.x() * o1 + rc.y(); - dst[i] = op_silu(x[j0]) * g[j1]; - } -} - -template -static void gated_op_fused_geglu_erf(const T * x, const T * g, T * dst, const uint64_t k, const sycl::uint3 n_fd, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) { - SYCL_GLOBAL_ID_LOOP(k, item_ct1) { - const sycl::uint2 rc = fast_div_modulo((uint32_t) i, n_fd); - const int64_t j0 = rc.x() * o0 + rc.y(); - const int64_t j1 = o0 == o1 ? j0 : rc.x() * o1 + rc.y(); - dst[i] = op_gelu_erf(x[j0]) * g[j1]; - } -} +template +static void unary_gated_op_generic_kernel( + const T * x, + const T * g, + T * dst, + const uint64_t k, + const sycl::uint3 n_fd, + const uint64_t o0, + const uint64_t o1, + const sycl::nd_item<1> & item_ct1, + F func) { -template -static void gated_op_fused_geglu_quick(const T * x, const T * g, T * dst, const uint64_t k, const sycl::uint3 n_fd, const uint64_t o0, const uint64_t o1, const sycl::nd_item<1> &item_ct1) { + // rows of n columns at strides o0 and o1: two halves of one fused tensor, or two tensors SYCL_GLOBAL_ID_LOOP(k, item_ct1) { const sycl::uint2 rc = fast_div_modulo((uint32_t) i, n_fd); const int64_t j0 = rc.x() * o0 + rc.y(); const int64_t j1 = o0 == o1 ? j0 : rc.x() * o1 + rc.y(); - dst[i] = op_gelu_quick(x[j0]) * g[j1]; + dst[i] = func(x[j0]) * g[j1]; } } @@ -670,6 +648,35 @@ static inline void ggml_sycl_op_unary( }); } +template +static inline void ggml_sycl_op_unary_gated( + ggml_backend_sycl_context & ctx, ggml_tensor * dst, F func) { + + dispatch_ggml_sycl_op_fused_glu(ctx, dst, + [func](const auto * x_ptr, const auto * g_ptr, auto * dst_ptr, uint64_t k, uint64_t n, uint64_t o0, uint64_t o1, queue_ptr main_stream) { + + const uint32_t num_blocks = (uint32_t) ceil_div(k, SYCL_GLU_BLOCK_SIZE); + const sycl::nd_range<1> launch_range(num_blocks * sycl::range<1>(SYCL_GLU_BLOCK_SIZE), + sycl::range<1>(SYCL_GLU_BLOCK_SIZE)); + + // o0 == n and o1 == n make the index math the identity, so index flat + // note: not ggml_is_contiguous - a fused [gate|up] src0 is contiguous with o0 == 2n + if (o0 == n && o1 == n) { + main_stream->parallel_for(launch_range, + [=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] { + unary_gated_op_flat_kernel(x_ptr, g_ptr, dst_ptr, k, item_ct1, func); + }); + } else { + // launch-invariant divisor, and only this path needs it + const sycl::uint3 n_fd = init_fastdiv_values((uint32_t) n); + main_stream->parallel_for(launch_range, + [=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] { + unary_gated_op_generic_kernel(x_ptr, g_ptr, dst_ptr, k, n_fd, o0, o1, item_ct1, func); + }); + } + }); +} + static inline void ggml_sycl_op_arange(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { GGML_ASSERT(dst->type == GGML_TYPE_F32); @@ -967,42 +974,21 @@ static inline void ggml_sycl_op_acc(ggml_backend_sycl_context & ctx, ggml_tensor } static inline void ggml_sycl_op_geglu(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { - ggml_sycl_detail::dispatch_ggml_sycl_op_fused_glu(ctx, dst, - [](const auto* x_ptr, const auto* g_ptr, auto* dst_ptr, uint64_t k, uint64_t n, uint64_t o0, uint64_t o1, queue_ptr main_stream) { - const uint32_t num_blocks = ceil_div(k, SYCL_GELU_BLOCK_SIZE); - const sycl::uint3 n_fd = init_fastdiv_values((uint32_t) n); - main_stream->parallel_for( - sycl::nd_range<1>((num_blocks * sycl::range<1>(SYCL_GELU_BLOCK_SIZE)), - sycl::range<1>(SYCL_GELU_BLOCK_SIZE)), [=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] { - gated_op_fused_geglu(x_ptr, g_ptr, dst_ptr, k, n_fd, o0, o1, item_ct1); - }); - }); + ggml_sycl_detail::ggml_sycl_op_unary_gated(ctx, dst, [](auto x) { + return op_gelu(x); + }); } static inline void ggml_sycl_op_reglu(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { - ggml_sycl_detail::dispatch_ggml_sycl_op_fused_glu(ctx, dst, - [](const auto* x_ptr, const auto* g_ptr, auto* dst_ptr, uint64_t k, uint64_t n, uint64_t o0, uint64_t o1, queue_ptr main_stream) { - const uint32_t num_blocks = ceil_div((uint32_t)k, SYCL_RELU_BLOCK_SIZE); // Using RELU block size for reglu - const sycl::uint3 n_fd = init_fastdiv_values((uint32_t) n); - main_stream->parallel_for( - sycl::nd_range<1>((num_blocks * sycl::range<1>(SYCL_RELU_BLOCK_SIZE)), - sycl::range<1>(SYCL_RELU_BLOCK_SIZE)), [=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] { - gated_op_fused_reglu(x_ptr, g_ptr, dst_ptr, k, n_fd, o0, o1, item_ct1); - }); - }); + ggml_sycl_detail::ggml_sycl_op_unary_gated(ctx, dst, [](auto x) { + return op_relu(x); + }); } static inline void ggml_sycl_op_swiglu(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { - ggml_sycl_detail::dispatch_ggml_sycl_op_fused_glu(ctx, dst, - [](const auto* x_ptr, const auto* g_ptr, auto* dst_ptr, uint64_t k, uint64_t n, uint64_t o0, uint64_t o1, queue_ptr main_stream) { - const uint32_t num_blocks = ceil_div((uint32_t)k, SYCL_SILU_BLOCK_SIZE); // Using SILU block size for swiglu - const sycl::uint3 n_fd = init_fastdiv_values((uint32_t) n); - main_stream->parallel_for( - sycl::nd_range<1>((num_blocks * sycl::range<1>(SYCL_SILU_BLOCK_SIZE)), - sycl::range<1>(SYCL_SILU_BLOCK_SIZE)), [=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] { - gated_op_fused_swiglu(x_ptr, g_ptr, dst_ptr, k, n_fd, o0, o1, item_ct1); - }); - }); + ggml_sycl_detail::ggml_sycl_op_unary_gated(ctx, dst, [](auto x) { + return op_silu(x); + }); } __dpct_inline__ float ggml_sycl_op_swiglu_oai_single(float x, float g, float alpha = 1.702f, float limit = 7.0f) { @@ -1097,29 +1083,15 @@ void ggml_sycl_op_swiglu_oai(ggml_backend_sycl_context & ctx, ggml_tensor * dst) } static inline void ggml_sycl_op_geglu_erf(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { - ggml_sycl_detail::dispatch_ggml_sycl_op_fused_glu(ctx, dst, - [](const auto* x_ptr, const auto* g_ptr, auto* dst_ptr, uint64_t k, uint64_t n, uint64_t o0, uint64_t o1, queue_ptr main_stream) { - const uint32_t num_blocks = ceil_div(k, SYCL_GELU_BLOCK_SIZE); - const sycl::uint3 n_fd = init_fastdiv_values((uint32_t) n); - main_stream->parallel_for( - sycl::nd_range<1>((num_blocks * sycl::range<1>(SYCL_GELU_BLOCK_SIZE)), - sycl::range<1>(SYCL_GELU_BLOCK_SIZE)), [=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] { - gated_op_fused_geglu_erf(x_ptr, g_ptr, dst_ptr, k, n_fd, o0, o1, item_ct1); - }); - }); + ggml_sycl_detail::ggml_sycl_op_unary_gated(ctx, dst, [](auto x) { + return op_gelu_erf(x); + }); } static inline void ggml_sycl_op_geglu_quick(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { - ggml_sycl_detail::dispatch_ggml_sycl_op_fused_glu(ctx, dst, - [](const auto* x_ptr, const auto* g_ptr, auto* dst_ptr, uint64_t k, uint64_t n, uint64_t o0, uint64_t o1, queue_ptr main_stream) { - const uint32_t num_blocks = ceil_div(k, SYCL_GELU_BLOCK_SIZE); - const sycl::uint3 n_fd = init_fastdiv_values((uint32_t) n); - main_stream->parallel_for( - sycl::nd_range<1>((num_blocks * sycl::range<1>(SYCL_GELU_BLOCK_SIZE)), - sycl::range<1>(SYCL_GELU_BLOCK_SIZE)), [=](sycl::nd_item<1> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] { - gated_op_fused_geglu_quick(x_ptr, g_ptr, dst_ptr, k, n_fd, o0, o1, item_ct1); - }); - }); + ggml_sycl_detail::ggml_sycl_op_unary_gated(ctx, dst, [](auto x) { + return op_gelu_quick(x); + }); } diff --git a/ggml/src/ggml-sycl/fattn-vec.hpp b/ggml/src/ggml-sycl/fattn-vec.hpp index 04baac44147..53ad0eaee42 100644 --- a/ggml/src/ggml-sycl/fattn-vec.hpp +++ b/ggml/src/ggml-sycl/fattn-vec.hpp @@ -73,6 +73,7 @@ static void flash_attn_ext_vec(const char* __restrict__ Q, const int32_t nb31, const int32_t nb32, const int64_t nb33) { + #ifdef SYCL_FLASH_ATTN // Skip unused kernel variants for faster compilation: @@ -469,7 +470,6 @@ static void flash_attn_ext_vec(const char* __restrict__ Q, } } - item_ct1.barrier(sycl::access::fence_space::local_space); #pragma unroll @@ -591,22 +591,24 @@ void ggml_sycl_flash_attn_ext_vec_case_impl(ggml_backend_sycl_context & ctx, ggm const auto arch = ggml_sycl_info().devices[ctx.device].hw_info.arch; const int nthreads = ggml_sycl_fattn_vec_get_nthreads_device(arch); - // 256 threads would overflow the 64 KB work-group local memory at D == 512, so keep 128 there. - if (D <= 256 && nthreads == 256) { - constexpr int nthreads_hw = 256; - constexpr int nwarps = nthreads_hw / warp_size; - launch_fattn, warp_size>( - ctx, dst, nwarps, nbytes_shared, D, need_f16_K, need_f16_V, false); - } else { - constexpr int nthreads_hw = 128; - constexpr int nwarps = nthreads_hw / warp_size; - launch_fattn, warp_size>( - ctx, dst, nwarps, nbytes_shared, D, need_f16_K, need_f16_V, false); + if constexpr (D <= 256) { + if (nthreads == 256) { + constexpr int nthreads_hw = 256; + constexpr int nwarps = nthreads_hw / warp_size; + launch_fattn, warp_size>( + ctx, dst, nwarps, nbytes_shared, D, need_f16_K, need_f16_V, false); + return; + } } + + constexpr int nthreads_hw = 128; + constexpr int nwarps = nthreads_hw / warp_size; + launch_fattn, warp_size>( + ctx, dst, nwarps, nbytes_shared, D, need_f16_K, need_f16_V, false); } template diff --git a/ggml/src/ggml-sycl/ggml-sycl.cpp b/ggml/src/ggml-sycl/ggml-sycl.cpp index d91e41f9575..18d58782ebf 100644 --- a/ggml/src/ggml-sycl/ggml-sycl.cpp +++ b/ggml/src/ggml-sycl/ggml-sycl.cpp @@ -62,6 +62,8 @@ #include "ggml-sycl/repeat_back.hpp" #include "ggml-sycl/set_rows.hpp" #include "ggml-sycl/set.hpp" +#include "ggml-sycl/dsv4-hc.hpp" +#include "ggml-sycl/lightning-indexer.hpp" #include "ggml-sycl/conv2d.hpp" #include "ggml-sycl/conv2d-dw.hpp" #include "ggml-sycl/conv2d-transpose.hpp" @@ -4942,6 +4944,18 @@ static bool ggml_sycl_compute_forward(ggml_backend_sycl_context & ctx, struct gg case GGML_OP_SET_ROWS: ggml_sycl_op_set_rows(ctx, dst); break; + case GGML_OP_DSV4_HC_PRE: + ggml_sycl_op_dsv4_hc_pre(ctx, dst); + break; + case GGML_OP_DSV4_HC_COMB: + ggml_sycl_op_dsv4_hc_comb(ctx, dst); + break; + case GGML_OP_DSV4_HC_POST: + ggml_sycl_op_dsv4_hc_post(ctx, dst); + break; + case GGML_OP_LIGHTNING_INDEXER: + ggml_sycl_op_lightning_indexer(ctx, dst); + break; case GGML_OP_DUP: ggml_sycl_dup(ctx, dst); break; @@ -5795,17 +5809,33 @@ static bool do_ggml_backend_sycl_device_supports_op(ggml_backend_dev_t dev, cons case GGML_OP_SET_ROWS: { - - auto res = ((op->type == GGML_TYPE_F32 || op->type == GGML_TYPE_F16 || op->type == GGML_TYPE_BF16 || - op->type == GGML_TYPE_Q8_0 || op->type == GGML_TYPE_Q5_1 || op->type == GGML_TYPE_Q5_0 || - op->type == GGML_TYPE_Q1_0 || - op->type == GGML_TYPE_Q4_1 || op->type == GGML_TYPE_Q4_0 || op->type == GGML_TYPE_IQ4_NL || - op->type == GGML_TYPE_MXFP4 || op->type == GGML_TYPE_NVFP4) && - op->src[0]->type == GGML_TYPE_F32 && - (op->src[1]->type == GGML_TYPE_I64 || op->src[1]->type == GGML_TYPE_I32)); + auto res = (op->src[0]->type == GGML_TYPE_F32 || op->src[0]->type == GGML_TYPE_F16 || + op->src[0]->type == GGML_TYPE_BF16) && + (op->src[1]->type == GGML_TYPE_I64 || op->src[1]->type == GGML_TYPE_I32); return res; } break; + case GGML_OP_DSV4_HC_PRE: + return op->src[0]->type == GGML_TYPE_F32 && op->src[1]->type == GGML_TYPE_F32 && + op->type == GGML_TYPE_F32; + case GGML_OP_DSV4_HC_COMB: + return op->src[0]->type == GGML_TYPE_F32 && op->src[1]->type == GGML_TYPE_F32 && + op->src[2]->type == GGML_TYPE_F32 && op->type == GGML_TYPE_F32; + case GGML_OP_DSV4_HC_POST: + return op->src[0]->type == GGML_TYPE_F32 && op->src[1]->type == GGML_TYPE_F32 && + op->src[2]->type == GGML_TYPE_F32 && op->src[3]->type == GGML_TYPE_F32 && + op->type == GGML_TYPE_F32; + case GGML_OP_LIGHTNING_INDEXER: + return op->src[0]->type == GGML_TYPE_F32 && + (op->src[1]->type == GGML_TYPE_F16 || op->src[1]->type == GGML_TYPE_F32 || + op->src[1]->type == GGML_TYPE_BF16 || op->src[1]->type == GGML_TYPE_Q8_0 || + op->src[1]->type == GGML_TYPE_Q5_1 || op->src[1]->type == GGML_TYPE_Q5_0 || + op->src[1]->type == GGML_TYPE_Q4_1 || op->src[1]->type == GGML_TYPE_Q4_0 || + op->src[1]->type == GGML_TYPE_IQ4_NL) && + op->src[2]->type == GGML_TYPE_F32 && + op->src[3]->type == GGML_TYPE_F16 && + op->type == GGML_TYPE_F32 && + op->src[0]->ne[0] == WARP_SIZE * 8; case GGML_OP_CPY: { ggml_type src0_type = op->src[0]->type; diff --git a/ggml/src/ggml-sycl/lightning-indexer.cpp b/ggml/src/ggml-sycl/lightning-indexer.cpp new file mode 100644 index 00000000000..823b713caf2 --- /dev/null +++ b/ggml/src/ggml-sycl/lightning-indexer.cpp @@ -0,0 +1,197 @@ +#include "lightning-indexer.hpp" +#include "dequantize.hpp" + +static void lightning_indexer_f32_sycl( + const char * q, const char * k, const char * w, const char * m, float * dst, + int64_t n_embd, int64_t n_head, int64_t n_batch, int64_t n_stream, int64_t n_kv, + int64_t nem3, + int64_t nbq1, int64_t nbq2, int64_t nbq3, + int64_t nbk2, int64_t nbk3, + int64_t nbw1, int64_t nbw3, + int64_t nbm1, int64_t nbm3, + int64_t nb1, int64_t nb3, + ggml_type k_type, + queue_ptr stream) { + + constexpr int64_t LANES = WARP_SIZE; + constexpr int64_t ELEMS_PER_LANE = 8; + constexpr int64_t ROWS_PER_BLOCK = 4; + constexpr int64_t BLOCK_SIZE = ROWS_PER_BLOCK * LANES; + + const int64_t n_rows = n_batch * n_stream * n_kv; + const int64_t n_blocks = (n_rows + ROWS_PER_BLOCK - 1) / ROWS_PER_BLOCK; + + stream->parallel_for( + sycl::nd_range<1>( + sycl::range<1>(n_blocks * BLOCK_SIZE), + sycl::range<1>(BLOCK_SIZE)), + [=](sycl::nd_item<1> item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] { + const int64_t ir = item.get_global_id(0); + const int64_t lane = ir % LANES; + const int64_t row = ir / LANES; + if (row >= n_rows) { + return; + } + + const int64_t i_bs = row / n_kv; + const int64_t i_kv = row % n_kv; + const int64_t i_batch = i_bs / n_stream; + const int64_t i_stream = i_bs % n_stream; + + // load K row slice into registers (row is contiguous, nbk0 == type size) + const char * k_base = k + i_kv*nbk2 + i_stream*nbk3; + float k_local[ELEMS_PER_LANE]; + if (k_type == GGML_TYPE_F16) { + const sycl::half * k_row = (const sycl::half *) k_base; +#pragma unroll + for (int64_t j = 0; j < ELEMS_PER_LANE; ++j) { + k_local[j] = static_cast(k_row[lane*ELEMS_PER_LANE + j]); + } + } else if (k_type == GGML_TYPE_F32) { + const float * k_row = (const float *) k_base; +#pragma unroll + for (int64_t j = 0; j < ELEMS_PER_LANE; ++j) { + k_local[j] = k_row[lane*ELEMS_PER_LANE + j]; + } + } else { + const int64_t lane_base = lane * ELEMS_PER_LANE; + switch (k_type) { + case GGML_TYPE_BF16: { + const sycl::ext::oneapi::bfloat16 * k_row = (const sycl::ext::oneapi::bfloat16 *) k_base; +#pragma unroll + for (int64_t j = 0; j < ELEMS_PER_LANE; ++j) { + k_local[j] = static_cast(k_row[lane_base + j]); + } + } break; + case GGML_TYPE_Q4_0: + case GGML_TYPE_Q4_1: + case GGML_TYPE_Q5_0: + case GGML_TYPE_Q5_1: { +#pragma unroll + for (int64_t j = 0; j < ELEMS_PER_LANE; ++j) { + const int64_t idx = lane_base + j; + const int64_t ib = idx / QK4_0; + const int iqs = idx % (QK4_0/2); + dfloat2 kv; + if (k_type == GGML_TYPE_Q4_0) { + dequantize_q4_0(k_base, ib, iqs, kv); + } else if (k_type == GGML_TYPE_Q4_1) { + dequantize_q4_1(k_base, ib, iqs, kv); + } else if (k_type == GGML_TYPE_Q5_0) { + dequantize_q5_0(k_base, ib, iqs, kv); + } else { + dequantize_q5_1(k_base, ib, iqs, kv); + } + k_local[j] = (idx % QK4_0) < (QK4_0/2) ? static_cast(kv.x()) : static_cast(kv.y()); + } + } break; + case GGML_TYPE_Q8_0: { +#pragma unroll + for (int64_t pair = 0; pair < ELEMS_PER_LANE / 2; ++pair) { + const int64_t elem0 = lane_base + 2 * pair; + dfloat2 kv; + dequantize_q8_0(k_base, elem0 / QK8_0, elem0 % QK8_0, kv); + k_local[2 * pair + 0] = static_cast(kv.x()); + k_local[2 * pair + 1] = static_cast(kv.y()); + } + } break; + case GGML_TYPE_IQ4_NL: { +#pragma unroll + for (int64_t pair = 0; pair < ELEMS_PER_LANE / 2; ++pair) { + const int64_t elem0 = lane_base + 2 * pair; + dfloat2 kv; + dequantize_iq4_nl(k_base, elem0 / QK4_NL, elem0 % QK4_NL, kv); + k_local[2 * pair + 0] = static_cast(kv.x()); + k_local[2 * pair + 1] = static_cast(kv.y()); + } + } break; + default: +#pragma unroll + for (int64_t j = 0; j < ELEMS_PER_LANE; ++j) { + k_local[j] = 0.0f; + } + break; + } + } + + const char * q_base = q + i_batch*nbq2 + i_stream*nbq3; + const float * w_base = (const float *) (w + i_batch*nbw1 + i_stream*nbw3); + + float score = 0.0f; + for (int64_t h = 0; h < n_head; ++h) { + const float * q_row = (const float *) (q_base + h*nbq1); + float dot = 0.0f; +#pragma unroll + for (int64_t j = 0; j < ELEMS_PER_LANE; ++j) { + const int64_t i = lane*ELEMS_PER_LANE + j; + if (i < n_embd) { + dot += q_row[i] * k_local[j]; + } + } + dot = sycl::reduce_over_group(item.get_sub_group(), dot, sycl::plus()); + if (lane == 0) { + score += sycl::max(dot, 0.0f) * w_base[h]; + } + } + + if (lane == 0) { + const sycl::half * m_base = (const sycl::half *) (m + i_batch*nbm1 + (i_stream % nem3)*nbm3); + // flat-index store: storing through a strided base pointer + // hangs/misroutes writes on this stack when n_batch*n_stream > 1 + const int64_t dst_idx = i_kv + i_batch*(nb1/sizeof(float)) + i_stream*(nb3/sizeof(float)); + dst[dst_idx] = score + static_cast(m_base[i_kv]); + } + }); +} + +void ggml_sycl_op_lightning_indexer(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { + scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/4); + const ggml_tensor * q = dst->src[0]; + const ggml_tensor * k = dst->src[1]; + const ggml_tensor * w = dst->src[2]; // weights + const ggml_tensor * m = dst->src[3]; // mask + + GGML_ASSERT(dst->type == GGML_TYPE_F32); + GGML_ASSERT( q->type == GGML_TYPE_F32); + GGML_ASSERT( w->type == GGML_TYPE_F32); + GGML_ASSERT( m->type == GGML_TYPE_F16); + GGML_ASSERT(k->type == GGML_TYPE_F16 || k->type == GGML_TYPE_F32 || k->type == GGML_TYPE_BF16 || + k->type == GGML_TYPE_Q8_0 || k->type == GGML_TYPE_Q5_1 || k->type == GGML_TYPE_Q5_0 || + k->type == GGML_TYPE_Q4_1 || k->type == GGML_TYPE_Q4_0 || k->type == GGML_TYPE_IQ4_NL); + + GGML_TENSOR_LOCALS(int64_t, neq, q, ne); + GGML_TENSOR_LOCALS(size_t, nbq, q, nb); + GGML_TENSOR_LOCALS(int64_t, nek, k, ne); + GGML_TENSOR_LOCALS(size_t, nbk, k, nb); + GGML_TENSOR_LOCALS(size_t, nbw, w, nb); + GGML_TENSOR_LOCALS(int64_t, nem, m, ne); + GGML_TENSOR_LOCALS(size_t, nbm, m, nb); + GGML_TENSOR_LOCALS(int64_t, ne, dst, ne); + GGML_TENSOR_LOCALS(size_t, nb, dst, nb); + + // input rows must be contiguous + GGML_ASSERT(nbq0 == ggml_type_size(q->type)); + GGML_ASSERT(nbk0 == ggml_type_size(k->type)); + GGML_ASSERT(nbm0 == ggml_type_size(m->type)); + GGML_ASSERT(nb0 == ggml_type_size(dst->type)); + + const int64_t n_embd = neq0; + const int64_t n_head = neq1; + const int64_t n_batch = neq2; + const int64_t n_stream = neq3; + const int64_t n_kv = nek2; + + GGML_ASSERT(n_embd == WARP_SIZE * 8); + + lightning_indexer_f32_sycl( + (const char *) q->data, (const char *) k->data, + (const char *) w->data, (const char *) m->data, (float *) dst->data, + n_embd, n_head, n_batch, n_stream, n_kv, nem3, + nbq1, nbq2, nbq3, + nbk2, nbk3, + nbw1, nbw3, + nbm1, nbm3, + nb1, nb3, + k->type, + ctx.stream()); +} diff --git a/ggml/src/ggml-sycl/lightning-indexer.hpp b/ggml/src/ggml-sycl/lightning-indexer.hpp new file mode 100644 index 00000000000..0b88c418ece --- /dev/null +++ b/ggml/src/ggml-sycl/lightning-indexer.hpp @@ -0,0 +1,8 @@ +#ifndef GGML_SYCL_LIGHTNING_INDEXER_HPP +#define GGML_SYCL_LIGHTNING_INDEXER_HPP + +#include "common.hpp" + +void ggml_sycl_op_lightning_indexer(ggml_backend_sycl_context & ctx, ggml_tensor * dst); + +#endif // GGML_SYCL_LIGHTNING_INDEXER_HPP diff --git a/ggml/src/ggml-sycl/presets.hpp b/ggml/src/ggml-sycl/presets.hpp index 502e3b61050..789f3ef0f20 100644 --- a/ggml/src/ggml-sycl/presets.hpp +++ b/ggml/src/ggml-sycl/presets.hpp @@ -20,8 +20,6 @@ #define MATRIX_ROW_PADDING 512 // last row of quant. matrices is a multiple of this to avoid out-of-bounds memory accesses #define SYCL_COL2IM_1D_BLOCK_SIZE 256 -#define SYCL_GELU_BLOCK_SIZE 256 -#define SYCL_SILU_BLOCK_SIZE 256 #define SYCL_TANH_BLOCK_SIZE 256 #define SYCL_RELU_BLOCK_SIZE 256 #define SYCL_HARDSIGMOID_BLOCK_SIZE 256 diff --git a/ggml/src/ggml-sycl/set_rows.cpp b/ggml/src/ggml-sycl/set_rows.cpp index 5fb97790712..52a0bcb6eba 100644 --- a/ggml/src/ggml-sycl/set_rows.cpp +++ b/ggml/src/ggml-sycl/set_rows.cpp @@ -1,6 +1,10 @@ #include "set_rows.hpp" #include "cpy.hpp" +#include "ggml-quants.h" + +#include + namespace utils { template static constexpr bool is_arithmetic_v() { @@ -20,7 +24,17 @@ convert (const char* src, char* dst) { *reinterpret_cast(dst) = dst_val; } -template +#ifdef GGML_SYCL_HAS_BF16 +// sycl::vec::convert does not provide a half -> bfloat16 path, so route through float. +template<> +inline void convert(const char* src, char* dst) { + const float tmp = sycl::vec(*reinterpret_cast(src)) + .template convert()[0]; + *reinterpret_cast(dst) = sycl::ext::oneapi::bfloat16(tmp); +} +#endif + +template static void set_rows_sycl_q(const char * __restrict__ src0_d, const TIdx * __restrict__ src1_d, blockType * __restrict__ dst_d, @@ -68,13 +82,22 @@ static void set_rows_sycl_q(const char * __restrict__ src0_d, const int64_t i11 = i02 % ne11; const int64_t i10 = i01; const size_t src_offset = calculate_offset<3>({ nb01, nb02, nb03 }, { i01, i02, i03 }); - const char * src_block = src0_d + src_offset + i00 * sizeof(float); + const char * src_block = src0_d + src_offset + i00 * sizeof(TIn); const size_t src1_offset = calculate_offset<3>({ nb10, nb11, nb12 }, { i10, i11, i12 }); const int64_t dst_row = src1_d[src1_offset / sizeof(TIdx)]; const size_t dst_offset = calculate_offset<3>({ nb1, nb2, nb3 }, { dst_row, i02, i03 }) + (i00 / qk) * sizeof(blockType); char * dst_block = reinterpret_cast(reinterpret_cast(dst_d) + dst_offset); - cpyblck(src_block, dst_block); + if constexpr (std::is_same_v) { + cpyblck(src_block, dst_block); + } else { + float src_block_f32[qk]; + const TIn * src_block_t = reinterpret_cast(src_block); + for (int j = 0; j < qk; ++j) { + src_block_f32[j] = (float) src_block_t[j]; + } + cpyblck(reinterpret_cast(src_block_f32), dst_block); + } }); GGML_UNUSED(ne10); GGML_UNUSED(ne13); @@ -82,6 +105,139 @@ static void set_rows_sycl_q(const char * __restrict__ src0_d, GGML_UNUSED(nb13); } +template +using quantize_row_qk_t = void (*)(const float *, blockType *, int64_t); + +using quantize_rows_f_t = size_t (*)(const float *, void *, int64_t, int64_t, const float *); + +template quantize_row> +static void set_rows_sycl_qk_host( + const ggml_tensor * src0, + const ggml_tensor * src1, + ggml_tensor * dst, + const int64_t ne00, + const int64_t ne01, + const int64_t ne02, + const int64_t ne03, + const int64_t ne11, + const int64_t ne12, + const size_t nb01, + const size_t nb02, + const size_t nb03, + const size_t nb10, + const size_t nb11, + const size_t nb12, + const size_t nb1, + const size_t nb2, + const size_t nb3, + queue_ptr stream) { + GGML_ASSERT(ne00 % qk == 0); + + const size_t src0_bytes = ggml_nbytes(src0); + const size_t src1_bytes = ggml_nbytes(src1); + + std::vector src0_host(src0_bytes); + std::vector src1_host(src1_bytes); + + stream->memcpy(src0_host.data(), src0->data, src0_bytes); + stream->memcpy(src1_host.data(), src1->data, src1_bytes); + stream->wait(); + + std::vector src_row_f32(ne00); + const int64_t nblocks = ne00 / qk; + std::vector dst_row_q(nblocks); + + for (int64_t i03 = 0; i03 < ne03; ++i03) { + for (int64_t i02 = 0; i02 < ne02; ++i02) { + for (int64_t i01 = 0; i01 < ne01; ++i01) { + const int64_t i12 = i03 % ne12; + const int64_t i11 = i02 % ne11; + const int64_t i10 = i01; + + const size_t src1_offset = calculate_offset<3>({ nb10, nb11, nb12 }, { i10, i11, i12 }); + const int64_t dst_row = *(const TIdx *) (src1_host.data() + src1_offset); + + const size_t src0_row_offset = calculate_offset<3>({ nb01, nb02, nb03 }, { i01, i02, i03 }); + const TIn * src_row = reinterpret_cast(src0_host.data() + src0_row_offset); + + for (int64_t i00 = 0; i00 < ne00; ++i00) { + src_row_f32[i00] = (float) src_row[i00]; + } + + quantize_row(src_row_f32.data(), dst_row_q.data(), ne00); + + const size_t dst_offset = calculate_offset<3>({ nb1, nb2, nb3 }, { dst_row, i02, i03 }); + stream->memcpy((char *) dst->data + dst_offset, dst_row_q.data(), nblocks * sizeof(blockType)); + stream->wait(); + } + } + } +} + +template +static void set_rows_sycl_iq_host( + const ggml_tensor * src0, + const ggml_tensor * src1, + ggml_tensor * dst, + const int64_t ne00, + const int64_t ne01, + const int64_t ne02, + const int64_t ne03, + const int64_t ne11, + const int64_t ne12, + const size_t nb01, + const size_t nb02, + const size_t nb03, + const size_t nb10, + const size_t nb11, + const size_t nb12, + const size_t nb1, + const size_t nb2, + const size_t nb3, + queue_ptr stream) { + GGML_ASSERT(ne00 % qk == 0); + + const size_t src0_bytes = ggml_nbytes(src0); + const size_t src1_bytes = ggml_nbytes(src1); + + std::vector src0_host(src0_bytes); + std::vector src1_host(src1_bytes); + + stream->memcpy(src0_host.data(), src0->data, src0_bytes); + stream->memcpy(src1_host.data(), src1->data, src1_bytes); + stream->wait(); + + std::vector src_row_f32(ne00); + const int64_t nblocks = ne00 / qk; + std::vector dst_row_q(nblocks); + + for (int64_t i03 = 0; i03 < ne03; ++i03) { + for (int64_t i02 = 0; i02 < ne02; ++i02) { + for (int64_t i01 = 0; i01 < ne01; ++i01) { + const int64_t i12 = i03 % ne12; + const int64_t i11 = i02 % ne11; + const int64_t i10 = i01; + + const size_t src1_offset = calculate_offset<3>({ nb10, nb11, nb12 }, { i10, i11, i12 }); + const int64_t dst_row = *(const TIdx *) (src1_host.data() + src1_offset); + + const size_t src0_row_offset = calculate_offset<3>({ nb01, nb02, nb03 }, { i01, i02, i03 }); + const TIn * src_row = reinterpret_cast(src0_host.data() + src0_row_offset); + + for (int64_t i00 = 0; i00 < ne00; ++i00) { + src_row_f32[i00] = (float) src_row[i00]; + } + + quantize_rows(src_row_f32.data(), dst_row_q.data(), 1, ne00, nullptr); + + const size_t dst_offset = calculate_offset<3>({ nb1, nb2, nb3 }, { dst_row, i02, i03 }); + stream->memcpy((char *) dst->data + dst_offset, dst_row_q.data(), nblocks * sizeof(blockType)); + stream->wait(); + } + } + } +} + template static void k_set_rows( const char * __restrict__ src0, const TIdx * __restrict__ src1, char * __restrict__ dst, @@ -200,31 +356,194 @@ static void set_rows_sycl(ggml_backend_sycl_context & ctx, const ggml_tensor * s break; #endif case GGML_TYPE_Q8_0: - set_rows_sycl_q(src0_d, src1_d, (block_q8_0 *)dst->data, ne00, ne01, ne02, ne03, ne10, ne11, ne12, ne13, nb00, nb01, nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); + set_rows_sycl_q( + src0_d, src1_d, (block_q8_0 *) dst->data, ne00, ne01, ne02, ne03, + ne10, ne11, ne12, ne13, nb00, nb01, + nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); break; case GGML_TYPE_Q1_0: - set_rows_sycl_q(src0_d, src1_d, (block_q1_0 *)dst->data, ne00, ne01, ne02, ne03, ne10, ne11, ne12, ne13, nb00, nb01, nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); + set_rows_sycl_q( + src0_d, src1_d, (block_q1_0 *) dst->data, ne00, ne01, ne02, ne03, + ne10, ne11, ne12, ne13, nb00, nb01, + nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); + break; + case GGML_TYPE_Q2_0: + set_rows_sycl_q( + src0_d, src1_d, (block_q2_0 *) dst->data, ne00, ne01, ne02, ne03, + ne10, ne11, ne12, ne13, nb00, nb01, + nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); break; case GGML_TYPE_Q5_1: - set_rows_sycl_q(src0_d, src1_d, (block_q5_1 *)dst->data, ne00, ne01, ne02, ne03, ne10, ne11, ne12, ne13, nb00, nb01, nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); + set_rows_sycl_q( + src0_d, src1_d, (block_q5_1 *) dst->data, ne00, ne01, ne02, ne03, + ne10, ne11, ne12, ne13, nb00, nb01, + nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); break; case GGML_TYPE_Q5_0: - set_rows_sycl_q(src0_d, src1_d, (block_q5_0 *)dst->data, ne00, ne01, ne02, ne03, ne10, ne11, ne12, ne13, nb00, nb01, nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); + set_rows_sycl_q( + src0_d, src1_d, (block_q5_0 *) dst->data, ne00, ne01, ne02, ne03, + ne10, ne11, ne12, ne13, nb00, nb01, + nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); break; case GGML_TYPE_Q4_1: - set_rows_sycl_q(src0_d, src1_d, (block_q4_1 *)dst->data, ne00, ne01, ne02, ne03, ne10, ne11, ne12, ne13, nb00, nb01, nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); + set_rows_sycl_q( + src0_d, src1_d, (block_q4_1 *) dst->data, ne00, ne01, ne02, ne03, + ne10, ne11, ne12, ne13, nb00, nb01, + nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); break; case GGML_TYPE_Q4_0: - set_rows_sycl_q(src0_d, src1_d, (block_q4_0 *)dst->data, ne00, ne01, ne02, ne03, ne10, ne11, ne12, ne13, nb00, nb01, nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); + set_rows_sycl_q( + src0_d, src1_d, (block_q4_0 *) dst->data, ne00, ne01, ne02, ne03, + ne10, ne11, ne12, ne13, nb00, nb01, + nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); break; case GGML_TYPE_IQ4_NL: - set_rows_sycl_q(src0_d, src1_d, (block_iq4_nl *)dst->data, ne00, ne01, ne02, ne03, ne10, ne11, ne12, ne13, nb00, nb01, nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); + set_rows_sycl_q( + src0_d, src1_d, (block_iq4_nl *) dst->data, ne00, ne01, ne02, ne03, + ne10, ne11, ne12, ne13, nb00, nb01, + nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); break; case GGML_TYPE_MXFP4: - set_rows_sycl_q(src0_d, src1_d, (block_mxfp4 *)dst->data, ne00, ne01, ne02, ne03, ne10, ne11, ne12, ne13, nb00, nb01, nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); + set_rows_sycl_q( + src0_d, src1_d, (block_mxfp4 *) dst->data, ne00, ne01, ne02, ne03, + ne10, ne11, ne12, ne13, nb00, nb01, + nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); break; case GGML_TYPE_NVFP4: - set_rows_sycl_q(src0_d, src1_d, (block_nvfp4 *)dst->data, ne00, ne01, ne02, ne03, ne10, ne11, ne12, ne13, nb00, nb01, nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); + set_rows_sycl_q( + src0_d, src1_d, (block_nvfp4 *) dst->data, ne00, ne01, ne02, ne03, + ne10, ne11, ne12, ne13, nb00, nb01, + nb02, nb03, nb10, nb11, nb12, nb13, nb1, nb2, nb3, stream); + break; + case GGML_TYPE_Q2_K: + set_rows_sycl_qk_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); + break; + case GGML_TYPE_Q3_K: + set_rows_sycl_qk_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); + break; + case GGML_TYPE_Q4_K: + set_rows_sycl_qk_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); + break; + case GGML_TYPE_Q5_K: + set_rows_sycl_qk_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); + break; + case GGML_TYPE_Q6_K: + set_rows_sycl_qk_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); + break; + case GGML_TYPE_IQ2_XXS: + set_rows_sycl_iq_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); + break; + case GGML_TYPE_IQ2_XS: + set_rows_sycl_iq_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); + break; + case GGML_TYPE_IQ2_S: + set_rows_sycl_iq_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); + break; + case GGML_TYPE_IQ3_XXS: + set_rows_sycl_qk_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); + break; + case GGML_TYPE_IQ3_S: + set_rows_sycl_qk_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); + break; + case GGML_TYPE_IQ1_S: + set_rows_sycl_iq_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); + break; + case GGML_TYPE_IQ1_M: + set_rows_sycl_iq_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); + break; + case GGML_TYPE_IQ4_XS: + set_rows_sycl_qk_host( + src0, src1, dst, + ne00, ne01, ne02, ne03, + ne11, ne12, + nb01, nb02, nb03, + nb10, nb11, nb12, + nb1, nb2, nb3, + stream); break; default: GGML_ABORT("Unsupported tensor type!"); @@ -237,12 +556,21 @@ void ggml_sycl_op_set_rows(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { const ggml_tensor * src0 = dst->src[0]; const ggml_tensor * src1 = dst->src[1]; - GGML_ASSERT(dst->src[0]->type == GGML_TYPE_F32); + GGML_ASSERT(dst->src[0]->type == GGML_TYPE_F32 || dst->src[0]->type == GGML_TYPE_F16); GGML_ASSERT(dst->src[1]->type == GGML_TYPE_I64 || dst->src[1]->type == GGML_TYPE_I32); - if (src1->type == GGML_TYPE_I64) { - set_rows_sycl(ctx, src0, src1, dst); + // dispatch on the index type (src1) and the source value type (src0) + if (src0->type == GGML_TYPE_F16) { + if (src1->type == GGML_TYPE_I64) { + set_rows_sycl(ctx, src0, src1, dst); + } else { + set_rows_sycl(ctx, src0, src1, dst); + } } else { - set_rows_sycl(ctx, src0, src1, dst); + if (src1->type == GGML_TYPE_I64) { + set_rows_sycl(ctx, src0, src1, dst); + } else { + set_rows_sycl(ctx, src0, src1, dst); + } } } diff --git a/ggml/src/ggml-sycl/ssm_conv.cpp b/ggml/src/ggml-sycl/ssm_conv.cpp index e55223586a1..3eafa1a680d 100644 --- a/ggml/src/ggml-sycl/ssm_conv.cpp +++ b/ggml/src/ggml-sycl/ssm_conv.cpp @@ -36,9 +36,13 @@ static void kernel_ssm_conv( return; } - const int channel = static_cast(idx % d_inner); - const int token = static_cast((idx / d_inner) % n_t); - const int seq = static_cast(idx / (static_cast(d_inner) * static_cast(n_t))); + // src has the tokens of one channel contiguous, dst has the channels of one + // token contiguous, so either the loads or the store must be strided. Indexing + // token-fastest coalesces the d_conv loads, which measured faster except for + // short, cache-resident rows. + const int token = static_cast(idx % n_t); + const int channel = static_cast((idx / n_t) % d_inner); + const int seq = static_cast(idx / (static_cast(n_t) * static_cast(d_inner))); const float *s = src_data + static_cast(seq) * static_cast(src_stride_seq) diff --git a/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ggml/src/ggml-vulkan/ggml-vulkan.cpp index 2418ba6d178..a923755f9ed 100644 --- a/ggml/src/ggml-vulkan/ggml-vulkan.cpp +++ b/ggml/src/ggml-vulkan/ggml-vulkan.cpp @@ -186,13 +186,22 @@ static bool is_pow2(uint32_t x) { return x > 1 && (x & (x-1)) == 0; } #define VK_DEVICE_DESCRIPTOR_POOL_SIZE 256 -#define VK_CHECK(err, msg) \ +#define VK_CHECK(err, msg, dev) \ do { \ - vk::Result err_ = (err); \ + vk::Result err_; \ + try { \ + err_ = (err); \ + } catch (vk::DeviceLostError &) { \ + ggml_vk_print_device_lost_info(dev); \ + GGML_LOG_ERROR("ggml_vulkan: %s at %s:%d\n", \ + #err, __FILE__, __LINE__); \ + throw; \ + } \ if (err_ != vk::Result::eSuccess) { \ - fprintf(stderr, "ggml_vulkan: %s error %s at %s:%d\n", \ + GGML_LOG_ERROR("ggml_vulkan: %s error %s at %s:%d\n", \ #err, to_string(err_).c_str(), __FILE__, __LINE__); \ - exit(1); \ + throw vk::SystemError(vk::make_error_code(err_), \ + "ggml_vulkan: " msg); \ } \ } while (0) @@ -302,9 +311,13 @@ struct vk_command_pool { } }; +static void ggml_vk_print_device_fault_info(const vk_device& device); +static void ggml_vk_print_device_lost_info(const vk_device& device); + // Prevent simultaneous submissions to the same queue. struct vk_queue_handle { vk::Queue queue; + vk_device_ref device; virtual void submit(vk::ArrayProxy submits, vk::Fence fence) = 0; virtual void lock() {} // no-op by default (internally synchronized case) virtual void unlock() {} @@ -315,7 +328,14 @@ struct vk_queue_handle_synchronized : vk_queue_handle { std::mutex mutex; void submit(vk::ArrayProxy submits, vk::Fence fence) override { std::lock_guard guard(mutex); - queue.submit(submits, fence); + try { + queue.submit(submits, fence); + } catch (vk::DeviceLostError &) { + if (auto dev = device.lock()) { + ggml_vk_print_device_lost_info(dev); + } + throw; + } } void lock() override { mutex.lock(); } void unlock() override { mutex.unlock(); } @@ -324,7 +344,14 @@ struct vk_queue_handle_synchronized : vk_queue_handle { struct vk_queue_handle_unsynchronized : vk_queue_handle { void submit(vk::ArrayProxy submits, vk::Fence fence) override { // Driver guarantees internal synchronization via VK_KHR_internally_synchronized_queues - queue.submit(submits, fence); + try { + queue.submit(submits, fence); + } catch (vk::DeviceLostError &) { + if (auto dev = device.lock()) { + ggml_vk_print_device_lost_info(dev); + } + throw; + } } // lock()/unlock() inherited no-ops }; @@ -835,6 +862,15 @@ struct vk_device_struct { bool pipeline_executable_properties_support {}; + bool device_fault {}; + PFN_vkGetDeviceFaultInfoEXT pfn_vkGetDeviceFaultInfoEXT {}; + + bool serialize_submissions {}; + + const ggml_cgraph * diag_cgraph {}; + int diag_prev_start = -1; + int diag_prev_end = -1; + size_t idx; bool mul_mat_l[GGML_TYPE_COUNT]; @@ -1118,6 +1154,57 @@ void vk_command_pool::destroy(vk::Device& device) { cmd_buffers.clear(); } +static void ggml_vk_print_device_fault_info(const vk_device& device) { + if (!device->device_fault || !device->pfn_vkGetDeviceFaultInfoEXT) { + return; + } + + VkDeviceFaultCountsEXT fault_counts {}; + fault_counts.sType = VK_STRUCTURE_TYPE_DEVICE_FAULT_COUNTS_EXT; + VkResult res = device->pfn_vkGetDeviceFaultInfoEXT(device->device, &fault_counts, nullptr); + if (res != VK_SUCCESS) { + GGML_LOG_ERROR("ggml_vulkan: vkGetDeviceFaultInfoEXT (counts) failed: %d\n", res); + return; + } + + std::vector address_infos(fault_counts.addressInfoCount); + std::vector vendor_infos(fault_counts.vendorInfoCount); + + VkDeviceFaultInfoEXT fault_info {}; + fault_info.sType = VK_STRUCTURE_TYPE_DEVICE_FAULT_INFO_EXT; + fault_info.pAddressInfos = address_infos.data(); + fault_info.pVendorInfos = vendor_infos.data(); + + res = device->pfn_vkGetDeviceFaultInfoEXT(device->device, &fault_counts, &fault_info); + if (res != VK_SUCCESS) { + GGML_LOG_ERROR("ggml_vulkan: vkGetDeviceFaultInfoEXT (info) failed: %d\n", res); + return; + } + + if (fault_counts.addressInfoCount == 0 && fault_counts.vendorInfoCount == 0 && fault_info.description[0] == '\0') { + return; + } + + if (fault_info.description[0] != '\0') { + GGML_LOG_ERROR("ggml_vulkan: device fault on %s: %s\n", device->name.c_str(), fault_info.description); + } + + for (uint32_t i = 0; i < fault_counts.addressInfoCount; i++) { + const auto& info = address_infos[i]; + GGML_LOG_CONT(" address fault %u: type=%d address=0x%llx precision=0x%llx\n", + i, (int)info.addressType, + (unsigned long long)info.reportedAddress, + (unsigned long long)info.addressPrecision); + } + for (uint32_t i = 0; i < fault_counts.vendorInfoCount; i++) { + const auto& info = vendor_infos[i]; + GGML_LOG_CONT(" vendor fault %u: %s (code=0x%llx data=0x%llx)\n", + i, info.description, + (unsigned long long)info.vendorFaultCode, + (unsigned long long)info.vendorFaultData); + } +} + struct vk_buffer_struct { vk::Buffer buffer = VK_NULL_HANDLE; vk::DeviceMemory device_memory = VK_NULL_HANDLE; @@ -2059,6 +2146,36 @@ static uint64_t ggml_vk_get_node_flops(const ggml_tensor * node) { return 0; } +static void ggml_vk_print_node_list(const ggml_cgraph * cgraph, int start, int end) { + uint64_t total_flops = 0; + int n_ops = 0; + for (int j = start; j <= end && j < cgraph->n_nodes; j++) { + uint64_t flops = ggml_vk_get_node_flops(cgraph->nodes[j]); + total_flops += flops; + n_ops++; + if (flops > 0) { + GGML_LOG_CONT(" node %d: %s (%s) [%.2f GFLOP]\n", + j, cgraph->nodes[j]->name, ggml_op_name(cgraph->nodes[j]->op), + flops / 1e9); + } else { + GGML_LOG_CONT(" node %d: %s (%s)\n", + j, cgraph->nodes[j]->name, ggml_op_name(cgraph->nodes[j]->op)); + } + } + GGML_LOG_CONT(" total: %d ops, %.2f GFLOP\n", n_ops, total_flops / 1e9); +} + +static void ggml_vk_print_device_lost_info(const vk_device& device) { + ggml_vk_print_device_fault_info(device); + if (device->serialize_submissions && device->diag_cgraph != nullptr && device->diag_prev_start >= 0) { + GGML_LOG_ERROR("ggml_vulkan: device lost on %s, likely caused by previous submission (nodes %d to %d):\n", + device->name.c_str(), device->diag_prev_start, device->diag_prev_end); + ggml_vk_print_node_list(device->diag_cgraph, device->diag_prev_start, device->diag_prev_end); + } else { + GGML_LOG_ERROR("ggml_vulkan: device lost on %s\n", device->name.c_str()); + } +} + class vk_perf_logger { public: void print_timings(bool force = false) { @@ -2471,17 +2588,27 @@ static void ggml_vk_wait_for_fence(ggml_backend_vk_context * ctx) { // Use waitForFences while most of the graph executes. Hopefully the CPU can sleep // during this wait. if (ctx->almost_ready_fence_pending) { - VK_CHECK(ctx->device->device.waitForFences({ ctx->almost_ready_fence }, true, UINT64_MAX), "almost_ready_fence"); + VK_CHECK(ctx->device->device.waitForFences({ ctx->almost_ready_fence }, true, UINT64_MAX), "almost_ready_fence", ctx->device); ctx->device->device.resetFences({ ctx->almost_ready_fence }); ctx->almost_ready_fence_pending = false; } // Spin (w/pause) waiting for the graph to finish executing. vk::Result result; - while ((result = ctx->device->device.getFenceStatus(ctx->fence)) != vk::Result::eSuccess) { + for (;;) { + try { + result = ctx->device->device.getFenceStatus(ctx->fence); + } catch (vk::DeviceLostError &) { + ggml_vk_print_device_lost_info(ctx->device); + GGML_LOG_ERROR("ggml_vulkan: getFenceStatus at %s:%d\n", __FILE__, __LINE__); + throw; + } + if (result == vk::Result::eSuccess) { + break; + } if (result != vk::Result::eNotReady) { - fprintf(stderr, "ggml_vulkan: error %s at %s:%d\n", to_string(result).c_str(), __FILE__, __LINE__); - exit(1); + GGML_LOG_ERROR("ggml_vulkan: error %s at %s:%d\n", to_string(result).c_str(), __FILE__, __LINE__); + throw vk::SystemError(vk::make_error_code(result), "ggml_vulkan: getFenceStatus"); } for (uint32_t i = 0; i < 100; ++i) { YIELD(); @@ -3172,6 +3299,7 @@ static std::unique_ptr ggml_vk_create_queue(vk_device& device, uint32_ } h->queue = device->device.getQueue2(queue_info2); + h->device = device; q->handle = h; q->cmd_pool.init(device, q.get()); @@ -6117,6 +6245,8 @@ static vk_device ggml_vk_get_device(size_t idx) { #endif } else if (strcmp(VK_KHR_INTERNALLY_SYNCHRONIZED_QUEUES_EXTENSION_NAME, properties.extensionName) == 0) { internally_sync_support = true; + } else if (strcmp("VK_EXT_device_fault", properties.extensionName) == 0) { + device->device_fault = true; } } @@ -6471,8 +6601,18 @@ static vk_device ggml_vk_get_device(size_t idx) { } #endif + VkPhysicalDeviceFaultFeaturesEXT fault_features {}; + fault_features.sType = VK_STRUCTURE_TYPE_PHYSICAL_DEVICE_FAULT_FEATURES_EXT; + if (device->device_fault) { + last_struct->pNext = (VkBaseOutStructure *)&fault_features; + last_struct = (VkBaseOutStructure *)&fault_features; + device_extensions.push_back("VK_EXT_device_fault"); + } + vkGetPhysicalDeviceFeatures2(device->physical_device, &device_features2); + device->device_fault = device->device_fault && fault_features.deviceFault; + device->has_internally_synchronized_queues = internally_synchronized_queues_features.internallySynchronizedQueues; // Build queue create infos only after querying whether internally synchronized queues are enabled. @@ -6771,6 +6911,11 @@ static vk_device ggml_vk_get_device(size_t idx) { device_create_info.setPNext(&device_features2); device->device = device->physical_device.createDevice(device_create_info); + if (device->device_fault) { + device->pfn_vkGetDeviceFaultInfoEXT = (PFN_vkGetDeviceFaultInfoEXT) + vkGetDeviceProcAddr(device->device, "vkGetDeviceFaultInfoEXT"); + } + // Queues device->compute_queue = ggml_vk_create_queue(device, compute_queue_family_index, 0, { vk::PipelineStageFlagBits::eComputeShader | vk::PipelineStageFlagBits::eTransfer }, false); @@ -6893,6 +7038,8 @@ static vk_device ggml_vk_get_device(size_t idx) { device->idx = idx; + device->serialize_submissions = getenv("GGML_VK_SERIALIZE_SUBMISSIONS") != nullptr; + device->disable_fusion = getenv("GGML_VK_DISABLE_FUSION") != nullptr; device->add_rms_fusion = !device->disable_fusion && @@ -8319,7 +8466,7 @@ static void ggml_vk_buffer_write_2d(vk_buffer& dst, size_t offset, const void * } ggml_vk_submit(subctx, dst->device->fence); - VK_CHECK(dst->device->device.waitForFences({ dst->device->fence }, true, UINT64_MAX), "vk_buffer_write_2d waitForFences"); + VK_CHECK(dst->device->device.waitForFences({ dst->device->fence }, true, UINT64_MAX), "vk_buffer_write_2d waitForFences", dst->device); dst->device->device.resetFences({ dst->device->fence }); ggml_vk_queue_command_pools_cleanup(dst->device); } @@ -8431,7 +8578,7 @@ static void ggml_vk_buffer_read_2d(vk_buffer& src, size_t offset, void * dst, si ggml_vk_ctx_end(subctx); ggml_vk_submit(subctx, src->device->fence); VK_CHECK(src->device->device.waitForFences({ src->device->fence }, true, UINT64_MAX), - "vk_buffer_read_2d uma waitForFences"); + "vk_buffer_read_2d uma waitForFences", src->device); src->device->device.resetFences({ src->device->fence }); ggml_vk_queue_command_pools_cleanup(src->device); @@ -8452,7 +8599,7 @@ static void ggml_vk_buffer_read_2d(vk_buffer& src, size_t offset, void * dst, si ggml_vk_ctx_end(subctx); ggml_vk_submit(subctx, src->device->fence); - VK_CHECK(src->device->device.waitForFences({ src->device->fence }, true, UINT64_MAX), "vk_buffer_read_2d waitForFences"); + VK_CHECK(src->device->device.waitForFences({ src->device->fence }, true, UINT64_MAX), "vk_buffer_read_2d waitForFences", src->device); src->device->device.resetFences({ src->device->fence }); ggml_vk_queue_command_pools_cleanup(src->device); @@ -8487,7 +8634,7 @@ static void ggml_vk_buffer_copy(vk_buffer& dst, size_t dst_offset, vk_buffer& sr ggml_vk_buffer_copy_async(subctx, dst, dst_offset, src, src_offset, size); ggml_vk_ctx_end(subctx); ggml_vk_submit(subctx, src->device->fence); - VK_CHECK(src->device->device.waitForFences({ src->device->fence }, true, UINT64_MAX), "vk_buffer_copy waitForFences"); + VK_CHECK(src->device->device.waitForFences({ src->device->fence }, true, UINT64_MAX), "vk_buffer_copy waitForFences", src->device); src->device->device.resetFences({ src->device->fence }); ggml_vk_queue_command_pools_cleanup(src->device); } else { @@ -8531,7 +8678,7 @@ static void ggml_vk_buffer_memset(vk_buffer& dst, size_t offset, uint32_t c, siz ggml_vk_ctx_end(subctx); ggml_vk_submit(subctx, dst->device->fence); - VK_CHECK(dst->device->device.waitForFences({ dst->device->fence }, true, UINT64_MAX), "vk_memset waitForFences"); + VK_CHECK(dst->device->device.waitForFences({ dst->device->fence }, true, UINT64_MAX), "vk_memset waitForFences", dst->device); dst->device->device.resetFences({ dst->device->fence }); ggml_vk_queue_command_pools_cleanup(dst->device); } @@ -14266,7 +14413,7 @@ static void ggml_vk_test_matmul(ggml_backend_vk_context * ctx, size_t m, size_t auto begin = std::chrono::high_resolution_clock::now(); ggml_vk_submit(subctx, ctx->fence); - VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_matmul waitForFences"); + VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_matmul waitForFences", ctx->device); ctx->device->device.resetFences({ ctx->fence }); ggml_vk_queue_command_pools_cleanup(ctx->device); @@ -14468,7 +14615,7 @@ static void ggml_vk_test_dequant(ggml_backend_vk_context * ctx, size_t ne, ggml_ auto begin = std::chrono::high_resolution_clock::now(); ggml_vk_submit(subctx, ctx->fence); - VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_dequant waitForFences"); + VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_dequant waitForFences", ctx->device); ctx->device->device.resetFences({ ctx->fence }); ggml_vk_queue_command_pools_cleanup(ctx->device); @@ -14754,7 +14901,7 @@ static void ggml_vk_test_dequant_matmul(ggml_backend_vk_context * ctx, size_t m, auto begin = std::chrono::high_resolution_clock::now(); ggml_vk_submit(subctx, ctx->fence); - VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_dequant waitForFences"); + VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "ggml_vk_test_dequant waitForFences", ctx->device); ctx->device->device.resetFences({ ctx->fence }); ggml_vk_queue_command_pools_cleanup(ctx->device); @@ -15553,7 +15700,9 @@ static void ggml_vk_compute_forward(ggml_backend_vk_context * ctx, ggml_cgraph * memset(mset.dst, mset.val, mset.n); } - if (almost_ready && !ctx->almost_ready_fence_pending) { + if (ctx->device->serialize_submissions) { + ggml_vk_submit(subctx, ctx->fence); + } else if (almost_ready && !ctx->almost_ready_fence_pending) { ggml_vk_submit(subctx, ctx->almost_ready_fence); ctx->almost_ready_fence_pending = true; } else { @@ -16164,12 +16313,20 @@ static void ggml_vk_synchronize(ggml_backend_vk_context * ctx) { memcpy(cpy.dst, cpy.src, cpy.n); } - ggml_vk_submit(compute_ctx, {}); + if (ctx->device->serialize_submissions) { + ggml_vk_submit(compute_ctx, ctx->fence); + VK_CHECK(ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX), "synchronize waitForFences", ctx->device); + ctx->device->device.resetFences({ ctx->fence }); + } else { + ggml_vk_submit(compute_ctx, {}); + } ctx->submit_pending = true; } if (ctx->submit_pending) { - if (ctx->device->async_use_transfer_queue && ctx->transfer_semaphore_last_submitted < ctx->transfer_semaphore.value) { + if (ctx->device->serialize_submissions) { + ctx->submit_pending = false; + } else if (ctx->device->async_use_transfer_queue && ctx->transfer_semaphore_last_submitted < ctx->transfer_semaphore.value) { vk::TimelineSemaphoreSubmitInfo tl_info{ 1, &ctx->transfer_semaphore.value, 0, nullptr, @@ -16186,7 +16343,9 @@ static void ggml_vk_synchronize(ggml_backend_vk_context * ctx) { } else { ctx->device->compute_queue->handle->submit({}, ctx->fence); } - ggml_vk_wait_for_fence(ctx); + if (!ctx->device->serialize_submissions) { + ggml_vk_wait_for_fence(ctx); + } ctx->submit_pending = false; if (cmd_buf) { cmd_buf->in_use = false; @@ -16758,6 +16917,10 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg VK_LOG_DEBUG("ggml_backend_vk_graph_compute(" << cgraph->n_nodes << " nodes)"); ggml_backend_vk_context * ctx = (ggml_backend_vk_context *)backend->context; + ctx->device->diag_cgraph = nullptr; + ctx->device->diag_prev_start = -1; + ctx->device->diag_prev_end = -1; + if (vk_instance.debug_utils_support) { vk::DebugUtilsLabelEXT dul = {}; dul.pLabelName = "ggml_backend_vk_graph_compute"; @@ -16849,6 +17012,36 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg } uint64_t flops_per_submit = std::min(flops_cap, ctx->last_total_flops / 40u); + auto const submit_after = [&](int start, int end) { + if (ctx->device->serialize_submissions) { + try { + auto res = ctx->device->device.waitForFences({ ctx->fence }, true, UINT64_MAX); + if (res != vk::Result::eSuccess) { + GGML_LOG_ERROR("ggml_vulkan: waitForFences error during serialized submission\n"); + throw vk::SystemError(vk::make_error_code(res), "ggml_vulkan: waitForFences during serialized submission"); + } + } catch (vk::DeviceLostError &) { + ggml_vk_print_device_fault_info(ctx->device); + GGML_LOG_ERROR("ggml_vulkan: device lost on %s waiting for submission (nodes %d to %d):\n", + ctx->device->name.c_str(), start, end); + ggml_vk_print_node_list(cgraph, start, end); + throw; + } + ctx->device->device.resetFences({ ctx->fence }); + ctx->submit_pending = false; + ctx->device->diag_cgraph = cgraph; + ctx->device->diag_prev_start = start; + ctx->device->diag_prev_end = end; + } + first_node_in_batch = true; + submitted_nodes = 0; + batch_flops = 0; + if (submit_count < 3) { + flops_per_submit *= 2; + } + submit_count++; + }; + for (int i = 0; i < cgraph->n_nodes; i++) { if (first_node_in_batch) { submit_node_idx = i; @@ -16856,8 +17049,20 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg { auto node_flops = ggml_vk_get_node_flops(cgraph->nodes[i]); - batch_flops += node_flops; total_flops += node_flops; + + // Flush the current batch before recording a node that would push it over the flop threshold + if (flops_per_submit != 0 && submitted_nodes > 0 && batch_flops + node_flops >= flops_per_submit) { + vk_context flush_ctx = ggml_vk_get_compute_ctx(ctx); + ggml_vk_ctx_end(flush_ctx); + flush_ctx->exit_tensor_idx = -1; + ctx->compute_ctx.reset(); + ggml_vk_compute_forward(ctx, cgraph, cgraph->nodes[submit_node_idx], submit_node_idx, false); + submit_after(submit_node_idx, i - 1); + submit_node_idx = i; + } + + batch_flops += node_flops; } // op_srcs_fused_elementwise indicates whether an op's srcs all contribute to @@ -17111,13 +17316,7 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg } if (submit && enqueued) { - first_node_in_batch = true; - submitted_nodes = 0; - batch_flops = 0; - if (submit_count < 3) { - flops_per_submit *= 2; - } - submit_count++; + submit_after(submit_node_idx, i + (int)ctx->num_additional_fused_ops); } i += ctx->num_additional_fused_ops; ctx->num_additional_fused_ops = 0; @@ -17133,13 +17332,13 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg ggml_vk_ctx_end(compute_ctx); ggml_vk_submit(compute_ctx, ctx->device->fence); - VK_CHECK(ctx->device->device.waitForFences({ ctx->device->fence }, true, UINT64_MAX), "GGML_VULKAN_PERF waitForFences"); + VK_CHECK(ctx->device->device.waitForFences({ ctx->device->fence }, true, UINT64_MAX), "GGML_VULKAN_PERF waitForFences", ctx->device); ctx->device->device.resetFences({ ctx->device->fence }); ctx->compute_ctx.reset(); // Get the results and pass them to the logger std::vector timestamps(cgraph->n_nodes + 1); - VK_CHECK(ctx->device->device.getQueryPoolResults(ctx->query_pool, 0, ctx->query_idx, (cgraph->n_nodes + 1)*sizeof(uint64_t), timestamps.data(), sizeof(uint64_t), vk::QueryResultFlagBits::e64 | vk::QueryResultFlagBits::eWait), "get timestamp results"); + VK_CHECK(ctx->device->device.getQueryPoolResults(ctx->query_pool, 0, ctx->query_idx, (cgraph->n_nodes + 1)*sizeof(uint64_t), timestamps.data(), sizeof(uint64_t), vk::QueryResultFlagBits::e64 | vk::QueryResultFlagBits::eWait), "get timestamp results", ctx->device); if (!vk_perf_logger_concurrent) { // Log each op separately for (int i = 1; i < ctx->query_idx; i++) { @@ -18366,7 +18565,7 @@ static void ggml_backend_vk_device_event_synchronize(ggml_backend_dev_t dev, ggm vk::Semaphore sem = vkev->tl_semaphore.s; uint64_t val = vkev->tl_semaphore.value; vk::SemaphoreWaitInfo swi{vk::SemaphoreWaitFlags{}, sem, val}; - VK_CHECK(device->device.waitSemaphores(swi, UINT64_MAX), "event_synchronize"); + VK_CHECK(device->device.waitSemaphores(swi, UINT64_MAX), "event_synchronize", device); // Reset and move submitted events for (auto& event : vkev->events_submitted) { diff --git a/scripts/sync-ggml.last b/scripts/sync-ggml.last index 35e94d9fb61..7af9ecb0f60 100644 --- a/scripts/sync-ggml.last +++ b/scripts/sync-ggml.last @@ -1 +1 @@ -90951f99af1fbebef3fbdd58ff5b8715b0bb9c43 +30bf8685ed4eb0a47f2b06229543327749904150 diff --git a/src/llama-model-loader.cpp b/src/llama-model-loader.cpp index c4bf6077f46..0c799a5a8de 100644 --- a/src/llama-model-loader.cpp +++ b/src/llama-model-loader.cpp @@ -1253,7 +1253,13 @@ struct ggml_tensor * llama_model_loader::create_tensor( for (size_t dim = 0; dim < GGML_MAX_DIMS; dim++) { t_meta.ne[dim] = dim < ne.size() ? ne.begin()[dim] : 1; GGML_ASSERT(t_meta.ne[dim] >= 1); - t_meta.nb[dim] = dim == 0 ? ggml_type_size(type) : t_meta.ne[dim-1]*t_meta.nb[dim-1]; + if (dim == 0) { + t_meta.nb[dim] = ggml_type_size(type); + } else if (dim == 1) { + t_meta.nb[dim] = ggml_row_size(type, t_meta.ne[dim-1]); + } else { + t_meta.nb[dim] = t_meta.nb[dim-1]*t_meta.ne[dim-1]; + } GGML_ASSERT(t_meta.nb[dim] >= 1); } ggml_set_name(&t_meta, tn.str().c_str()); @@ -1276,10 +1282,18 @@ struct ggml_tensor * llama_model_loader::create_tensor( if (flags & TENSOR_ALLOW_RESHAPE) { for (size_t dim = 0; dim < GGML_MAX_DIMS; dim++) { t_meta.ne[dim] = dim < ne.size() ? ne.begin()[dim] : 1; - t_meta.nb[dim] = dim == 0 ? ggml_type_size(t_meta.type) : t_meta.ne[dim-1]*t_meta.nb[dim-1]; + if (dim == 0) { + t_meta.nb[dim] = ggml_type_size(t_meta.type); + } else if (dim == 1) { + t_meta.nb[dim] = ggml_row_size(t_meta.type, t_meta.ne[dim-1]); + } else { + t_meta.nb[dim] = t_meta.ne[dim-1]*t_meta.nb[dim-1]; + } } } + GGML_ASSERT(ggml_nbytes(&t_meta) == ggml_nbytes(cur)); + ggml_backend_buffer_type_t buft = buft_for_tensor(&t_meta); if (buft == nullptr) { return nullptr; diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp index 8cb59893586..14a2340604a 100644 --- a/tests/test-backend-ops.cpp +++ b/tests/test-backend-ops.cpp @@ -2584,6 +2584,7 @@ struct test_rms_norm_mul_rope : public test_case { const float eps; const bool multi_add; // test a sequence of adds feeding into rms_norm const bool set_rows; + const bool broadcast; // multiply by a 1D [ne0] weight, as model norm weights are int mode; std::string op_desc(ggml_tensor * t) override { @@ -2594,12 +2595,12 @@ struct test_rms_norm_mul_rope : public test_case { bool run_whole_graph() override { return true; } std::string vars() override { - return VARS_TO_STR5(ne, eps, multi_add, set_rows, mode); + return VARS_TO_STR6(ne, eps, multi_add, set_rows, broadcast, mode); } test_rms_norm_mul_rope(std::array ne, float eps = 1e-6f, bool multi_add = false, - bool set_rows = false, int mode = GGML_ROPE_TYPE_NORMAL) - : ne(ne), eps(eps), multi_add(multi_add), set_rows(set_rows), mode(mode) {} + bool set_rows = false, bool broadcast = false, int mode = GGML_ROPE_TYPE_NORMAL) + : ne(ne), eps(eps), multi_add(multi_add), set_rows(set_rows), broadcast(broadcast), mode(mode) {} ggml_tensor * build_graph(ggml_context * ctx) override { ggml_tensor * a = ggml_new_tensor_4d(ctx, GGML_TYPE_F32, ne[0], ne[1], ne[2], 1); @@ -2610,7 +2611,9 @@ struct test_rms_norm_mul_rope : public test_case { a = ggml_add(ctx, ggml_add(ctx, a, b), c); } - a = ggml_mul(ctx, ggml_rms_norm(ctx, a, eps), b); + ggml_tensor * w = broadcast ? ggml_new_tensor_1d(ctx, GGML_TYPE_F32, ne[0]) : b; + + a = ggml_mul(ctx, ggml_rms_norm(ctx, a, eps), w); ggml_tensor * pos = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, ne[2]); @@ -8576,6 +8579,9 @@ static std::vector> make_test_cases_eval() { test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 2, 3, 4}, {-1,-1,-1,-1}, {1, 0, 2, 3})); // cpy not-contiguous } } + // quant block count not a multiple of the kernel block size + test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_Q4_0, {96, 1, 1, 1})); + test_cases.emplace_back(new test_cpy(GGML_TYPE_Q4_0, GGML_TYPE_F32, {96, 1, 1, 1})); test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_I32, {256, 2, 3, 4})); test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_I32, {256, 2, 3, 4}, {-1,-1,-1,-1}, {1, 0, 2, 3})); test_cases.emplace_back(new test_cpy(GGML_TYPE_I32, GGML_TYPE_F32, {256, 2, 3, 4})); @@ -8722,6 +8728,13 @@ static std::vector> make_test_cases_eval() { test_cases.emplace_back(new test_l2_norm(GGML_TYPE_F32, { n, 5, 4, 3 }, eps, true)); test_cases.emplace_back(new test_l2_norm(GGML_TYPE_F32, { n, 5, 4, 3 }, eps, false, true)); } + // row lengths that are not a multiple of 32, for the scalar (33) and float4 (132, 260) paths + for (uint32_t n : { 33, 132, 260 }) { + for (bool v : { false, true }) { + test_cases.emplace_back(new test_norm(GGML_TYPE_F32, { n, 5, 4, 3 }, v, eps)); + test_cases.emplace_back(new test_rms_norm(GGML_TYPE_F32, { n, 5, 4, 3 }, v, eps)); + } + } } // in-place tests @@ -8746,16 +8759,18 @@ static std::vector> make_test_cases_eval() { for (auto multi_add : {false, true}) { for (auto set_rows : {false, true}) { - for (auto rope : {GGML_ROPE_TYPE_NORMAL, GGML_ROPE_TYPE_NEOX}) { - test_cases.emplace_back(new test_rms_norm_mul_rope({768, 1, 1, 1}, 1e-6f, multi_add, set_rows, rope)); - test_cases.emplace_back(new test_rms_norm_mul_rope({768, 3, 1, 1}, 1e-6f, multi_add, set_rows, rope)); - test_cases.emplace_back(new test_rms_norm_mul_rope({768, 3, 5, 1}, 1e-6f, multi_add, set_rows, rope)); - test_cases.emplace_back(new test_rms_norm_mul_rope({128, 32, 2, 1}, 1e-6f, multi_add, set_rows, rope)); - test_cases.emplace_back(new test_rms_norm_mul_rope({128, 4, 2, 1}, 1e-6f, multi_add, set_rows, rope)); - test_cases.emplace_back(new test_rms_norm_mul_rope({128, 32, 50, 1}, 1e-6f, multi_add, set_rows, rope)); - test_cases.emplace_back(new test_rms_norm_mul_rope({128, 4, 50, 1}, 1e-6f, multi_add, set_rows, rope)); - test_cases.emplace_back(new test_rms_norm_mul_rope({8192, 2, 2, 1}, 1e-6f, multi_add, set_rows, rope)); - test_cases.emplace_back(new test_rms_norm_mul_rope({8192, 2, 2, 1}, 1e-6f, multi_add, set_rows, rope)); + for (auto broadcast : {false, true}) { + for (auto rope : {GGML_ROPE_TYPE_NORMAL, GGML_ROPE_TYPE_NEOX}) { + test_cases.emplace_back(new test_rms_norm_mul_rope({768, 1, 1, 1}, 1e-6f, multi_add, set_rows, broadcast, rope)); + test_cases.emplace_back(new test_rms_norm_mul_rope({768, 3, 1, 1}, 1e-6f, multi_add, set_rows, broadcast, rope)); + test_cases.emplace_back(new test_rms_norm_mul_rope({768, 3, 5, 1}, 1e-6f, multi_add, set_rows, broadcast, rope)); + test_cases.emplace_back(new test_rms_norm_mul_rope({128, 32, 2, 1}, 1e-6f, multi_add, set_rows, broadcast, rope)); + test_cases.emplace_back(new test_rms_norm_mul_rope({128, 4, 2, 1}, 1e-6f, multi_add, set_rows, broadcast, rope)); + test_cases.emplace_back(new test_rms_norm_mul_rope({128, 32, 50, 1}, 1e-6f, multi_add, set_rows, broadcast, rope)); + test_cases.emplace_back(new test_rms_norm_mul_rope({128, 4, 50, 1}, 1e-6f, multi_add, set_rows, broadcast, rope)); + test_cases.emplace_back(new test_rms_norm_mul_rope({8192, 2, 2, 1}, 1e-6f, multi_add, set_rows, broadcast, rope)); + test_cases.emplace_back(new test_rms_norm_mul_rope({8192, 2, 2, 1}, 1e-6f, multi_add, set_rows, broadcast, rope)); + } } } } @@ -9747,6 +9762,15 @@ static std::vector> make_test_cases_eval() { static std::vector> make_test_cases_perf() { std::vector> test_cases; + // SWIGLU at a 27B-class FFN width, fused [gate|up] vs split operands + // note: same bytes either way, so a backend that indexes them differently shows it here + for (ggml_type type : {GGML_TYPE_F16, GGML_TYPE_F32}) { + for (int64_t n_tokens : {512, 2048}) { + test_cases.emplace_back(new test_glu(GGML_GLU_OP_SWIGLU, type, { 2*17408, n_tokens, 1, 1 }, 0, false)); + test_cases.emplace_back(new test_glu_split(GGML_GLU_OP_SWIGLU, type, { 17408, n_tokens, 1, 1 }, 0)); + } + } + // Conv2d: K=CRS=NPQ=4096 matmul performance uint32_t iwh_idx = 0; uint32_t kwh_idx = 1; diff --git a/tests/test-backend-sampler.cpp b/tests/test-backend-sampler.cpp index 1165f46f0c9..e5ae634cd6a 100644 --- a/tests/test-backend-sampler.cpp +++ b/tests/test-backend-sampler.cpp @@ -1668,9 +1668,18 @@ static std::vector collect_tests_to_run(const std::st } } else { for (const auto & test : BACKEND_TESTS) { - if (test.enabled_by_default) { - selected.push_back(&test); + if (!test.enabled_by_default) { + continue; + } +#ifdef GGML_USE_HIP + // TODO: remove this when https://github.com/ggml-org/llama.cpp/pull/26592 is merged + if (test.name == "penalties" || test.name == "set_sampler" || + test.name == "mixed" || test.name == "top_p") { + fprintf(stderr, "Skipping test '%s' on HIP backend (no backend TOP_K support)\n", test.name.c_str()); + continue; } +#endif // GGML_USE_HIP + selected.push_back(&test); } } diff --git a/tests/test-llama-archs.cpp b/tests/test-llama-archs.cpp index eb90798b62c..0e29d221ba1 100644 --- a/tests/test-llama-archs.cpp +++ b/tests/test-llama-archs.cpp @@ -437,6 +437,14 @@ static bool arch_supported(const llm_arch arch) { } #endif // GGML_USE_WEBGPU + // FIXME: jamba produces incorrect output (~0.55 NMSE vs CPU) on the HIP + // backend on RDNA3.5 (gfx1151); the SSM kernels need investigation. +#ifdef GGML_USE_HIP + if (arch == LLM_ARCH_JAMBA) { + return false; + } +#endif // GGML_USE_HIP + return true; } diff --git a/tests/test-model-resolution.cpp b/tests/test-model-resolution.cpp index a96e40bb2bf..2437eeec608 100644 --- a/tests/test-model-resolution.cpp +++ b/tests/test-model-resolution.cpp @@ -195,7 +195,7 @@ static const std::vector dspark_dflash = { struct plan_case { const char * name; - const std::vector & files; + const std::vector files; const char * hf_repo; const char * hf_file; bool sidecars; // request mmproj + mtp + dflash + eagle3 + dspark diff --git a/tests/test-mtmd-c-api.c b/tests/test-mtmd-c-api.c index 46a038f4a5f..970d8a60000 100644 --- a/tests/test-mtmd-c-api.c +++ b/tests/test-mtmd-c-api.c @@ -1,4 +1,6 @@ #include +#include +#include #include #include "mtmd.h" @@ -62,6 +64,72 @@ int main(void) { } } + // test chunk save/load round-trip + for (size_t i = 0; i < n_chunks; i++) { + const mtmd_input_chunk * chunk = mtmd_input_chunks_get(chunks, i); + assert(chunk != NULL); + enum mtmd_input_chunk_type type = mtmd_input_chunk_get_type(chunk); + + // query the required buffer size (out_buf == NULL) + size_t expected_len = 0; + int32_t rc = mtmd_input_chunk_save(chunk, NULL, 0, &expected_len); + printf(" Chunk %zu: save query rc = %d, expected_len = %zu\n", i, rc, expected_len); + assert(rc == 0); + assert(expected_len > 0); + + // saving into a too-small buffer must fail, not crash + char tiny_buf[1]; + rc = mtmd_input_chunk_save(chunk, tiny_buf, sizeof(tiny_buf), NULL); + printf(" Chunk %zu: save into too-small buffer rc = %d (expect non-zero)\n", i, rc); + assert(rc != 0); + + // save into a properly-sized buffer + char * buf = (char *) malloc(expected_len); + assert(buf != NULL); + rc = mtmd_input_chunk_save(chunk, buf, expected_len, NULL); + assert(rc == 0); + + // loading from a truncated buffer must fail gracefully, not crash + if (expected_len > 1) { + mtmd_input_chunk * bad = mtmd_input_chunk_load(buf, expected_len - 1); + printf(" Chunk %zu: load from truncated buffer = %p (expect NULL)\n", i, (void *) bad); + assert(bad == NULL); + } + + // load it back + mtmd_input_chunk * loaded = mtmd_input_chunk_load(buf, expected_len); + assert(loaded != NULL); + + // metadata must match the original chunk + assert(mtmd_input_chunk_get_type(loaded) == type); + assert(mtmd_input_chunk_get_n_tokens(loaded) == mtmd_input_chunk_get_n_tokens(chunk)); + assert(mtmd_input_chunk_get_n_pos(loaded) == mtmd_input_chunk_get_n_pos(chunk)); + + if (type == MTMD_INPUT_CHUNK_TYPE_TEXT) { + size_t n_tok_orig, n_tok_loaded; + const llama_token * tok_orig = mtmd_input_chunk_get_tokens_text(chunk, &n_tok_orig); + const llama_token * tok_loaded = mtmd_input_chunk_get_tokens_text(loaded, &n_tok_loaded); + printf(" Chunk %zu: loaded %zu text tokens (orig %zu), first token %d (orig %d)\n", + i, n_tok_loaded, n_tok_orig, + n_tok_loaded > 0 ? tok_loaded[0] : -1, + n_tok_orig > 0 ? tok_orig[0] : -1); + assert(n_tok_orig == n_tok_loaded); + for (size_t j = 0; j < n_tok_orig; j++) { + assert(tok_orig[j] == tok_loaded[j]); + } + } else if (type == MTMD_INPUT_CHUNK_TYPE_IMAGE || type == MTMD_INPUT_CHUNK_TYPE_AUDIO) { + const char * id_orig = mtmd_input_chunk_get_id(chunk); + const char * id_loaded = mtmd_input_chunk_get_id(loaded); + printf(" Chunk %zu: loaded id '%s' (orig '%s')\n", i, id_loaded, id_orig); + assert(id_orig != NULL && id_loaded != NULL); + assert(strcmp(id_orig, id_loaded) == 0); + } + + mtmd_input_chunk_free(loaded); + free(buf); + } + printf("Chunk save/load round-trip OK\n"); + // Free the chunks mtmd_input_chunks_free(chunks); diff --git a/tools/cli/README.md b/tools/cli/README.md index 5754377cb97..8944328e9c2 100644 --- a/tools/cli/README.md +++ b/tools/cli/README.md @@ -54,7 +54,6 @@ | `-ctv, --cache-type-v TYPE` | KV cache data type for V
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_CACHE_TYPE_V) | | `-dt, --defrag-thold N` | KV cache defragmentation threshold (DEPRECATED)
(env: LLAMA_ARG_DEFRAG_THOLD) | | `-np, --parallel N` | number of parallel sequences to decode (default: 1)
(env: LLAMA_ARG_N_PARALLEL) | -| `--rpc SERVERS` | comma-separated list of RPC servers (host:port)
(env: LLAMA_ARG_RPC) | | `--mlock` | DEPRECATED in favor of `--load-mode`: force system to keep model in RAM rather than swapping or compressing
(env: LLAMA_ARG_MLOCK) | | `--mmap, --no-mmap` | DEPRECATED in favor of `--load-mode`: whether to memory-map model. (if mmap disabled, slower load but may reduce pageouts if not using mlock)
(env: LLAMA_ARG_MMAP) | | `-dio, --direct-io, -ndio, --no-direct-io` | DEPRECATED in favor of `--load-mode`: use DirectIO if available
(env: LLAMA_ARG_DIO) | diff --git a/tools/completion/README.md b/tools/completion/README.md index 56b5ea9e3d2..7628a82f077 100644 --- a/tools/completion/README.md +++ b/tools/completion/README.md @@ -137,7 +137,6 @@ llama-completion.exe -m models\gemma-1.1-7b-it.Q4_K_M.gguf --ignore-eos -n -1 | `-ctv, --cache-type-v TYPE` | KV cache data type for V
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_CACHE_TYPE_V) | | `-dt, --defrag-thold N` | KV cache defragmentation threshold (DEPRECATED)
(env: LLAMA_ARG_DEFRAG_THOLD) | | `-np, --parallel N` | number of parallel sequences to decode (default: 1)
(env: LLAMA_ARG_N_PARALLEL) | -| `--rpc SERVERS` | comma-separated list of RPC servers (host:port)
(env: LLAMA_ARG_RPC) | | `--mlock` | DEPRECATED in favor of `--load-mode`: force system to keep model in RAM rather than swapping or compressing
(env: LLAMA_ARG_MLOCK) | | `--mmap, --no-mmap` | DEPRECATED in favor of `--load-mode`: whether to memory-map model. (if mmap disabled, slower load but may reduce pageouts if not using mlock)
(env: LLAMA_ARG_MMAP) | | `-dio, --direct-io, -ndio, --no-direct-io` | DEPRECATED in favor of `--load-mode`: use DirectIO if available
(env: LLAMA_ARG_DIO) | diff --git a/tools/mtmd/clip-impl.h b/tools/mtmd/clip-impl.h index e1567ee5baf..acfecdde84e 100644 --- a/tools/mtmd/clip-impl.h +++ b/tools/mtmd/clip-impl.h @@ -591,6 +591,8 @@ struct clip_image_u8 { } }; +struct mtmd_serialization; // forward declaration + // For images, buf.size() == nx*ny*3 // Memory layout: RGBRGBRGB... // For seq, buf.size() == nx*ny*3*nt @@ -671,6 +673,9 @@ struct clip_image_f32 { return buf.empty(); } + void serialize(struct mtmd_serialization & ser) const; + void deserialize(struct mtmd_serialization & ser); + private: std::vector buf; int nx_ = 0; @@ -752,6 +757,9 @@ struct clip_image_f32_batch { } return new_batch; } + + void serialize(struct mtmd_serialization & ser) const; + void deserialize(struct mtmd_serialization & ser); }; // diff --git a/tools/mtmd/clip-model.h b/tools/mtmd/clip-model.h index 101f49cd184..7db01b576bd 100644 --- a/tools/mtmd/clip-model.h +++ b/tools/mtmd/clip-model.h @@ -170,6 +170,17 @@ struct clip_hparams { warmup_image_size = static_cast(std::sqrt(image_max_pixels)); } + // used by longest_edge preprocessor (no model-specific value for min/max tokens) + void set_limit_image_tokens() { + const int patch_area = patch_size * patch_size * n_merge * n_merge; + if (custom_image_min_tokens > 0) { + image_min_pixels = custom_image_min_tokens * patch_area; + } + if (custom_image_max_tokens > 0) { + image_max_pixels = custom_image_max_tokens * patch_area; + } + } + void set_warmup_n_tokens(int n_tokens) { int n_tok_per_side = static_cast(std::sqrt(n_tokens)); GGML_ASSERT(n_tok_per_side * n_tok_per_side == n_tokens && "n_tokens must be n*n"); diff --git a/tools/mtmd/clip.cpp b/tools/mtmd/clip.cpp index b1360fd7d30..3b610562987 100644 --- a/tools/mtmd/clip.cpp +++ b/tools/mtmd/clip.cpp @@ -1434,6 +1434,7 @@ struct clip_model_loader { // use default llava-uhd preprocessing params get_u32(KEY_PROJ_SCALE_FACTOR, hparams.n_merge, false); get_u32(KEY_PREPROC_IMAGE_SIZE, hparams.image_longest_edge, false); + hparams.set_limit_image_tokens(); } break; case PROJECTOR_TYPE_LFM2: { @@ -1471,6 +1472,7 @@ struct clip_model_loader { get_u32(KEY_SPATIAL_MERGE_SIZE, hparams.n_merge, false); hparams.image_longest_edge = hparams.image_size; get_u32(KEY_PREPROC_IMAGE_SIZE, hparams.image_longest_edge, false); + hparams.set_limit_image_tokens(); hparams.set_warmup_n_tokens(256); // avoid OOM on warmup } break; case PROJECTOR_TYPE_DOTS_OCR: @@ -1595,6 +1597,7 @@ struct clip_model_loader { if (hparams.image_longest_edge == 0) { hparams.image_longest_edge = 3024; } + // note: the step3vl preprocessor slices based on a fixed window grid, so it does not support custom min/max image tokens hparams.warmup_image_size = hparams.image_size; } break; case PROJECTOR_TYPE_YOUTUVL: diff --git a/tools/mtmd/mtmd-helper-gen.cpp b/tools/mtmd/mtmd-helper-gen.cpp index b52dc8e5a34..85671d1a331 100644 --- a/tools/mtmd/mtmd-helper-gen.cpp +++ b/tools/mtmd/mtmd-helper-gen.cpp @@ -112,7 +112,6 @@ class qwen3tts_gen_audio_pipeline : public mtmd_gen_audio_pipeline { c2w_state.clear(); audio_pcm.clear(); overlay.clear(); - overlay_idx = 0; h_state_buf.clear(); out_buf.clear(); prompt_embd_buf.clear(); @@ -205,11 +204,9 @@ class qwen3tts_gen_audio_pipeline : public mtmd_gen_audio_pipeline { top_p = inp->top_p > 0 ? inp->top_p : 1.0f; out_type = inp->out_type; - // the text stream keeps flowing during generation: after frame k, the input adds - // trailing text row k on top of the codes embedding, then tts_eos, then tts_pad - for (int i = 3; i < n_ids - 5; i++) overlay.push_back(row(ids[(size_t) i])); - overlay.push_back(row(tts_eos)); - overlay.push_back(row(tts_pad)); + // the prompt above holds the whole text stream up to tts_eos, so every generated + // frame adds tts_pad on top of the codes embedding + overlay = row(tts_pad); return 0; } @@ -265,9 +262,7 @@ class qwen3tts_gen_audio_pipeline : public mtmd_gen_audio_pipeline { } std::vector fb(out.embd, out.embd + n_embd); - const auto & ov = overlay[std::min(overlay_idx, overlay.size() - 1)]; - for (int i = 0; i < n_embd; i++) fb[(size_t) i] += ov[(size_t) i]; - overlay_idx++; + for (int i = 0; i < n_embd; i++) fb[(size_t) i] += overlay[(size_t) i]; const int n_pos_per_embd = mrope ? 4 : 1; decode_embd_batch batch_embd(fb.data(), 1, n_pos_per_embd, n_embd); @@ -437,8 +432,7 @@ class qwen3tts_gen_audio_pipeline : public mtmd_gen_audio_pipeline { std::vector codes_buf; std::vector c2w_state; std::vector audio_pcm; - std::vector> overlay; - size_t overlay_idx = 0; + std::vector overlay; std::vector h_state_buf; mtmd_helper_gen_audio_outtype out_type = MTMD_HELPER_GEN_AUDIO_OUTTYPE_WAV; std::vector out_buf; diff --git a/tools/mtmd/mtmd-image.cpp b/tools/mtmd/mtmd-image.cpp index 10cfe52f56f..073d83d4534 100644 --- a/tools/mtmd/mtmd-image.cpp +++ b/tools/mtmd/mtmd-image.cpp @@ -139,50 +139,46 @@ struct img_tool { } } - // calculate the size of the **resized** image, while preserving the aspect ratio - // the calculated size will be aligned to the nearest multiple of align_size - // if H or W size is larger than longest_edge, it will be resized to longest_edge - static clip_image_size calc_size_preserved_ratio(const clip_image_size & inp_size, const int align_size, const int longest_edge) { - GGML_ASSERT(align_size > 0); - if (inp_size.width <= 0 || inp_size.height <= 0 || longest_edge <= 0) { - return {0, 0}; - } - - float scale = std::min(static_cast(longest_edge) / inp_size.width, - static_cast(longest_edge) / inp_size.height); - - float target_width_f = static_cast(inp_size.width) * scale; - float target_height_f = static_cast(inp_size.height) * scale; - - auto ceil_by_factor = [f = align_size](float x) { return static_cast(std::ceil(x / static_cast(f))) * f; }; - int aligned_width = ceil_by_factor(target_width_f); - int aligned_height = ceil_by_factor(target_height_f); - - return {aligned_width, aligned_height}; - } + struct calc_size_opt { + int align_size = 1; + int min_pixels = 0; // 0 = disabled + int max_pixels = 0; // 0 = disabled + // applied before min/max_pixels, so min_pixels can push an edge back above longest_edge + int longest_edge = 0; // 0 = disabled + }; - // calculate the size of the **resized** image, while preserving the aspect ratio - // the calculated size will have min_pixels <= W*H <= max_pixels - // this is referred as "smart_resize" in transformers code - static clip_image_size calc_size_preserved_ratio(const clip_image_size & inp_size, const int align_size, const int min_pixels, const int max_pixels) { - GGML_ASSERT(align_size > 0); + // calculate the size of the **resized** image, while preserving the aspect ratio and + // aligning to the nearest multiple of align_size ("smart_resize" in transformers code) + static clip_image_size calc_size_preserved_ratio(const clip_image_size & inp_size, const calc_size_opt & opts) { + GGML_ASSERT(opts.align_size > 0); const int width = inp_size.width; const int height = inp_size.height; + if (width <= 0 || height <= 0) { + return {0, 0}; + } - auto round_by_factor = [f = align_size](float x) { return static_cast(std::round(x / static_cast(f))) * f; }; - auto ceil_by_factor = [f = align_size](float x) { return static_cast(std::ceil(x / static_cast(f))) * f; }; - auto floor_by_factor = [f = align_size](float x) { return static_cast(std::floor(x / static_cast(f))) * f; }; + auto round_by_factor = [f = opts.align_size](float x) { return static_cast(std::round(x / static_cast(f))) * f; }; + auto ceil_by_factor = [f = opts.align_size](float x) { return static_cast(std::ceil(x / static_cast(f))) * f; }; + auto floor_by_factor = [f = opts.align_size](float x) { return static_cast(std::floor(x / static_cast(f))) * f; }; - // always align up first - int h_bar = std::max(align_size, round_by_factor(height)); - int w_bar = std::max(align_size, round_by_factor(width)); + int w_bar, h_bar; + if (opts.longest_edge > 0) { + const float scale = std::min(static_cast(opts.longest_edge) / width, + static_cast(opts.longest_edge) / height); + w_bar = ceil_by_factor(width * scale); + h_bar = ceil_by_factor(height * scale); + } else { + // always align up first + w_bar = std::max(opts.align_size, round_by_factor(width)); + h_bar = std::max(opts.align_size, round_by_factor(height)); + } - if (h_bar * w_bar > max_pixels) { - const auto beta = std::sqrt(static_cast(height * width) / max_pixels); - h_bar = std::max(align_size, floor_by_factor(height / beta)); - w_bar = std::max(align_size, floor_by_factor(width / beta)); - } else if (h_bar * w_bar < min_pixels) { - const auto beta = std::sqrt(static_cast(min_pixels) / (height * width)); + if (opts.max_pixels > 0 && h_bar * w_bar > opts.max_pixels) { + const auto beta = std::sqrt(static_cast(height) * width / opts.max_pixels); + h_bar = std::max(opts.align_size, floor_by_factor(height / beta)); + w_bar = std::max(opts.align_size, floor_by_factor(width / beta)); + } else if (opts.min_pixels > 0 && h_bar * w_bar < opts.min_pixels) { + const auto beta = std::sqrt(static_cast(opts.min_pixels) / (static_cast(height) * width)); h_bar = ceil_by_factor(height * beta); w_bar = ceil_by_factor(width * beta); } @@ -937,9 +933,12 @@ mtmd_image_preproc_out mtmd_image_preprocessor_dyn_size::preprocess(const clip_i const int cur_merge = hparams.n_merge; const clip_image_size target_size = img_tool::calc_size_preserved_ratio( original_size, - hparams.patch_size * cur_merge, - hparams.image_min_pixels, - hparams.image_max_pixels); + { + /* align_size */ hparams.patch_size * cur_merge, + /* min_pixels */ hparams.image_min_pixels, + /* max_pixels */ hparams.image_max_pixels, + /* longest_edge */ 0, + }); img_tool::resize(img, resized_image, target_size, hparams.image_resize_algo, hparams.image_resize_pad, @@ -961,8 +960,12 @@ mtmd_image_preproc_out mtmd_image_preprocessor_longest_edge::preprocess(const cl const int cur_merge = hparams.n_merge == 0 ? 1 : hparams.n_merge; const clip_image_size target_size = img_tool::calc_size_preserved_ratio( original_size, - hparams.patch_size * cur_merge, - hparams.image_longest_edge); + { + /* align_size */ hparams.patch_size * cur_merge, + /* min_pixels */ std::max(0, hparams.image_min_pixels), + /* max_pixels */ std::max(0, hparams.image_max_pixels), + /* longest_edge */ hparams.image_longest_edge, + }); img_tool::resize(img, resized_image, target_size, hparams.image_resize_algo, hparams.image_resize_pad, @@ -1000,8 +1003,8 @@ mtmd_image_preprocessor_llava_uhd::slice_instructions mtmd_image_preprocessor_lf mtmd_image_preprocessor_llava_uhd::slice_instructions inst; const int align_size = hparams.patch_size * hparams.n_merge; inst.overview_size = img_tool::calc_size_preserved_ratio( - original_size, align_size, - hparams.image_min_pixels, hparams.image_max_pixels); + original_size, + { align_size, hparams.image_min_pixels, hparams.image_max_pixels, 0 }); // tile if either dimension exceeds tile_size with tolerance const bool needs_tiling = original_size.width > tile_size * max_pixels_tolerance || original_size.height > tile_size * max_pixels_tolerance; @@ -1109,7 +1112,8 @@ mtmd_image_preproc_out mtmd_image_preprocessor_idefics3::preprocess(const clip_i // CITE: https://github.com/huggingface/transformers/blob/main/src/transformers/models/idefics3/image_processing_idefics3.py#L737 const clip_image_size original_size = img.get_size(); const clip_image_size refined_size = img_tool::calc_size_preserved_ratio( - original_size, hparams.image_size, hparams.image_longest_edge); + original_size, + { hparams.image_size, std::max(0, hparams.image_min_pixels), std::max(0, hparams.image_max_pixels), hparams.image_longest_edge }); // LOG_INF("%s: original size: %d x %d, refined size: %d x %d\n", // __func__, original_size.width, original_size.height, // refined_size.width, refined_size.height); diff --git a/tools/mtmd/mtmd.cpp b/tools/mtmd/mtmd.cpp index ff90d6818cb..6ef4a9d3a1a 100644 --- a/tools/mtmd/mtmd.cpp +++ b/tools/mtmd/mtmd.cpp @@ -22,8 +22,123 @@ #include #include #include +#include #include +// remember to bump this if the serialization format changes +#define MTMD_SERIALIZATION_VERSION 1 + +struct mtmd_serialization { + // note: using 64-bit here for future-proofing + uint64_t version = MTMD_SERIALIZATION_VERSION; + std::vector data; + size_t read_pos = 0; // cursor used when reading + + // for writing + mtmd_serialization(uint64_t version) : version(version) { + write(version); + } + + // for reading + mtmd_serialization(uint64_t version, const char * buf, size_t len) { + // copy buf to data + data.assign(buf, buf + len); + uint64_t ver_in = read(); + if (ver_in != version) { + throw std::runtime_error("version mismatch"); + } + this->version = ver_in; + } + + template + void write(T value) { + static_assert(std::is_trivially_copyable::value && !std::is_same::value, + "T must be trivially copyable and not bool"); + const char * p = reinterpret_cast(&value); + data.insert(data.end(), p, p + sizeof(T)); + } + + template + T read() { + static_assert(std::is_trivially_copyable::value && !std::is_same::value, + "T must be trivially copyable and not bool"); + if (read_pos + sizeof(T) > data.size()) { + throw std::runtime_error("read OOB"); + } + T value; + std::memcpy(&value, data.data() + read_pos, sizeof(T)); + read_pos += sizeof(T); + return value; + } + +}; + +template <> +void mtmd_serialization::write(bool value) { + write(value ? 1 : 0); +} +template <> +bool mtmd_serialization::read() { + return read() != 0; +} + +template <> +void mtmd_serialization::write(std::string value) { + write(value.size()); + data.insert(data.end(), value.begin(), value.end()); +} +template <> +std::string mtmd_serialization::read() { + uint64_t len = read(); + if (read_pos + len > data.size()) { + throw std::runtime_error("read_string OOB"); + } + std::string str(data.data() + read_pos, len); + read_pos += len; + return str; +} + +// only mtmd.cpp needs these, so they're implemented here rather than in clip-impl.h +void clip_image_f32::serialize(mtmd_serialization & ser) const { + // remember to bump MTMD_SERIALIZATION_VERSION if this is changed + // note: buf is intentionally NOT serialized; the loaded clip_image_f32 will always be a placeholder + ser.write(add_viewsep); + ser.write(add_newline); + ser.write((int32_t)nx_); + ser.write((int32_t)ny_); +} +void clip_image_f32::deserialize(mtmd_serialization & ser) { + add_viewsep = ser.read(); + add_newline = ser.read(); + nx_ = ser.read(); + ny_ = ser.read(); + buf.clear(); // always a placeholder after loading +} + +void clip_image_f32_batch::serialize(mtmd_serialization & ser) const { + // remember to bump MTMD_SERIALIZATION_VERSION if this is changed + ser.write(is_audio); + ser.write(entries.size()); + for (const auto & entry : entries) { + entry.serialize(ser); + } +} +void clip_image_f32_batch::deserialize(mtmd_serialization & ser) { + is_audio = ser.read(); + uint64_t n = ser.read(); + constexpr size_t min_entry_bytes = sizeof(uint8_t) * 2 + sizeof(int32_t) * 2; + if (n > (ser.data.size() - ser.read_pos) / min_entry_bytes) { + throw std::runtime_error("entries count exceeds buffer size"); + } + entries.clear(); + entries.reserve(n); + for (uint64_t i = 0; i < n; i++) { + clip_image_f32 entry; + entry.deserialize(ser); + entries.push_back(std::move(entry)); + } +} + // for still image data, layout is RGBRGBRGB... // length of data must be nx * ny * 3 bytes // @@ -83,6 +198,7 @@ enum mtmd_pos_type { MTMD_POS_TYPE_NORMAL, // number of positions equals to number of tokens MTMD_POS_TYPE_MROPE, // qwen-vl mrope style, each image takes max(t,h,w) position indexes MTMD_POS_TYPE_HUNYUANVL, // HunyuanVL mrope + BOI/EOI/newline layout with XD-RoPE dim-3 + MTMD_POS_TYPE_COUNT, // for validation }; struct mtmd_image_tokens { @@ -136,6 +252,30 @@ struct mtmd_image_tokens { id }; } + + void serialize(mtmd_serialization & ser) const { + // remember to bump MTMD_SERIALIZATION_VERSION if this is changed + ser.write(nx); + ser.write(ny); + ser.write((uint32_t)pos); + ser.write(image_idx); + ser.write(n_temporal_merge); + ser.write(id); + batch_f32.serialize(ser); + } + void deserialize(mtmd_serialization & ser) { + nx = ser.read(); + ny = ser.read(); + uint32_t pos_raw = ser.read(); + if (pos_raw >= MTMD_POS_TYPE_COUNT) { + throw std::runtime_error("invalid pos type"); + } + pos = (mtmd_pos_type)pos_raw; + image_idx = ser.read(); + n_temporal_merge = ser.read(); + id = ser.read(); + batch_f32.deserialize(ser); + } }; using mtmd_image_tokens_ptr = std::unique_ptr; @@ -161,6 +301,18 @@ struct mtmd_audio_tokens { id }; } + + void serialize(mtmd_serialization & ser) const { + // remember to bump MTMD_SERIALIZATION_VERSION if this is changed + ser.write(n_tokens); + ser.write(id); + batch_f32.serialize(ser); + } + void deserialize(mtmd_serialization & ser) { + n_tokens = ser.read(); + id = ser.read(); + batch_f32.deserialize(ser); + } }; using mtmd_audio_tokens_ptr = std::unique_ptr; @@ -192,6 +344,66 @@ struct mtmd_input_chunk { } return false; } + + void serialize(mtmd_serialization & ser) const { + // remember to bump MTMD_SERIALIZATION_VERSION if this is changed + ser.write((uint32_t)type); + + ser.write(tokens_text.size()); + for (llama_token tok : tokens_text) { + ser.write((int32_t)tok); + } + + ser.write(tokens_image != nullptr); + if (tokens_image) { + tokens_image->serialize(ser); + } + + ser.write(tokens_audio != nullptr); + if (tokens_audio) { + tokens_audio->serialize(ser); + } + } + void deserialize(mtmd_serialization & ser) { + uint32_t type_raw = ser.read(); + if (type_raw >= MTMD_INPUT_CHUNK_TYPE_COUNT) { + throw std::runtime_error("invalid chunk type"); + } + type = (mtmd_input_chunk_type)type_raw; + + uint64_t n_tokens_text = ser.read(); + // reject before resize() so a tiny corrupted/malicious buffer can't force a huge allocation + if (n_tokens_text > (ser.data.size() - ser.read_pos) / sizeof(int32_t)) { + throw std::runtime_error("tokens_text length exceeds buffer size"); + } + tokens_text.resize(n_tokens_text); + for (uint64_t i = 0; i < n_tokens_text; i++) { + tokens_text[i] = (llama_token)ser.read(); + } + + if (ser.read()) { + tokens_image = std::make_unique(); + tokens_image->deserialize(ser); + } else { + tokens_image.reset(); + } + + if (ser.read()) { + tokens_audio = std::make_unique(); + tokens_audio->deserialize(ser); + } else { + tokens_audio.reset(); + } + + // catch buffers where the declared type doesn't match which payload is actually present, + // so a mismatched chunk can't slip through and null-deref/abort later in an accessor + if (type == MTMD_INPUT_CHUNK_TYPE_IMAGE && !tokens_image) { + throw std::runtime_error("type is IMAGE but tokens_image is missing"); + } + if (type == MTMD_INPUT_CHUNK_TYPE_AUDIO && !tokens_audio) { + throw std::runtime_error("type is AUDIO but tokens_audio is missing"); + } + } }; struct mtmd_input_chunks { @@ -2043,6 +2255,42 @@ void mtmd_input_chunk_free(mtmd_input_chunk * chunk) { } } +int32_t mtmd_input_chunk_save(const mtmd_input_chunk * chunk, char * out_buf, size_t out_len, size_t * expected_out_len) { + try { + mtmd_serialization ser(MTMD_SERIALIZATION_VERSION); + chunk->serialize(ser); + + if (expected_out_len) { + *expected_out_len = ser.data.size(); + } + if (!out_buf) { + // caller is only querying the required size + return 0; + } + if (out_len < ser.data.size()) { + LOG_ERR("%s: out_buf is too small, need %zu bytes, got %zu\n", __func__, ser.data.size(), out_len); + return -1; + } + std::memcpy(out_buf, ser.data.data(), ser.data.size()); + return 0; + } catch (const std::exception & e) { + LOG_ERR("%s: %s\n", __func__, e.what()); + return -1; + } +} + +mtmd_input_chunk * mtmd_input_chunk_load(const char * buf, size_t len) { + try { + mtmd_serialization ser(MTMD_SERIALIZATION_VERSION, buf, len); + mtmd::input_chunk_ptr chunk(new mtmd_input_chunk()); + chunk->deserialize(ser); + return chunk.release(); + } catch (const std::exception & e) { + LOG_ERR("%s: %s\n", __func__, e.what()); + return nullptr; + } +} + // mtmd_image_tokens size_t mtmd_image_tokens_get_n_tokens(const mtmd_image_tokens * image_tokens) { diff --git a/tools/mtmd/mtmd.h b/tools/mtmd/mtmd.h index 84651f8dcd0..e5063d114cc 100644 --- a/tools/mtmd/mtmd.h +++ b/tools/mtmd/mtmd.h @@ -55,6 +55,7 @@ enum mtmd_input_chunk_type { MTMD_INPUT_CHUNK_TYPE_TEXT, MTMD_INPUT_CHUNK_TYPE_IMAGE, MTMD_INPUT_CHUNK_TYPE_AUDIO, + MTMD_INPUT_CHUNK_TYPE_COUNT, // for validation }; // opaque types @@ -232,6 +233,15 @@ MTMD_API llama_pos mtmd_input_chunk_get_n_pos (const mtmd MTMD_API mtmd_input_chunk * mtmd_input_chunk_copy(const mtmd_input_chunk * chunk); MTMD_API void mtmd_input_chunk_free(mtmd_input_chunk * chunk); +// save/load an input chunk to/from a buffer (useful for KV save/load) +// important: only chunk's metadata will be saved, the actual image/audio data will not be saved +// the loaded chunk will always be a placeholder, cannot be used for mtmd_encode() or mtmd_batch_encode() +// out_buf can be nullptr (to query expected_out_len) +// returns 0 on success, non-zero on failure +MTMD_API int32_t mtmd_input_chunk_save(const mtmd_input_chunk * chunk, char * out_buf, size_t out_len, size_t * expected_out_len); +// returns nullptr on failure +MTMD_API mtmd_input_chunk * mtmd_input_chunk_load(const char * buf, size_t len); + // mtmd_image_tokens // diff --git a/tools/server/README-dev.md b/tools/server/README-dev.md index 45bcdcca769..31408f4267c 100644 --- a/tools/server/README-dev.md +++ b/tools/server/README-dev.md @@ -201,6 +201,7 @@ Invoke a tool call, request body is a JSON object with: Headers: - `x-tool-cwd`: optional; if set, use as the CWD for tool; this is not part of tool's params because it's meant to be set by the runtime, not the LLM itself +- `x-tool-runtime`: optional; if set, run the tool inside this isolate instead of on the host. Only `docker-container:` is supported for now, using an already-running container Returns JSON object. There are two response formats (MCP tools use the same two formats: their result content is concatenated into `plain_text_response`, and RPC or tool errors are surfaced as the `error` string): diff --git a/tools/server/README.md b/tools/server/README.md index 4d80f059d54..64f0b03269d 100644 --- a/tools/server/README.md +++ b/tools/server/README.md @@ -71,7 +71,6 @@ For the full list of features, please refer to [server's changelog](https://gith | `-ctk, --cache-type-k TYPE` | KV cache data type for K
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_CACHE_TYPE_K) | | `-ctv, --cache-type-v TYPE` | KV cache data type for V
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_CACHE_TYPE_V) | | `-dt, --defrag-thold N` | KV cache defragmentation threshold (DEPRECATED)
(env: LLAMA_ARG_DEFRAG_THOLD) | -| `--rpc SERVERS` | comma-separated list of RPC servers (host:port)
(env: LLAMA_ARG_RPC) | | `--mlock` | DEPRECATED in favor of `--load-mode`: force system to keep model in RAM rather than swapping or compressing
(env: LLAMA_ARG_MLOCK) | | `--mmap, --no-mmap` | DEPRECATED in favor of `--load-mode`: whether to memory-map model. (if mmap disabled, slower load but may reduce pageouts if not using mlock)
(env: LLAMA_ARG_MMAP) | | `-dio, --direct-io, -ndio, --no-direct-io` | DEPRECATED in favor of `--load-mode`: use DirectIO if available
(env: LLAMA_ARG_DIO) | @@ -198,6 +197,8 @@ For the full list of features, please refer to [server's changelog](https://gith | `--ui-config, --webui-config JSON` | JSON that provides default UI settings (overrides UI defaults)
(env: LLAMA_ARG_UI_CONFIG) | | `--ui-config-file, --webui-config-file PATH` | JSON file that provides default UI settings (overrides UI defaults)
(env: LLAMA_ARG_UI_CONFIG_FILE) | | `--ui-mcp-proxy, --webui-mcp-proxy, --no-ui-mcp-proxy, --no-webui-mcp-proxy` | experimental: whether to enable MCP CORS proxy - do not enable in untrusted environments (default: disabled)
(env: LLAMA_ARG_UI_MCP_PROXY) | +| `--tools TOOL1,TOOL2,...` | experimental: whether to enable built-in tools for AI agents - do not enable in untrusted environments (default: no tools)
specify "all" to enable all tools
available tools: read_file, file_glob_search, grep_search, exec_shell_command, write_file, edit_file, get_datetime
note: for security reasons, this will limit --cors-origins to localhost by default
(env: LLAMA_ARG_TOOLS) | +| `--tools-runtime OPTION` | experimental: run tools in a separate runtime environment (default: none, use host environment)
available options:
'docker:': spin up a new Docker container and reuse it for all invocations, clean up on server exit
'docker-container:': use an existing Docker container by ID, won't stop on server exit

(env: LLAMA_ARG_TOOLS_RUNTIME) | | `--tools TOOL1,TOOL2,...` | experimental: whether to enable built-in tools for AI agents - do not enable in untrusted environments (default: no tools)
specify "all" to enable all tools
available tools: read_file, file_glob_search, grep_search, exec_shell_command, write_file, edit_file, get_datetime, get_info
note: for security reasons, this will limit --cors-origins to localhost by default
(env: LLAMA_ARG_TOOLS) | | `--mcp-servers-config PATH` | experimental: path to JSON file with MCP server definitions (Cursor-compatible format) - do not enable in untrusted environments (default: none)
note: for security reasons, this will limit --cors-origins to localhost by default
(env: LLAMA_ARG_MCP_SERVERS_CONFIG) | | `--mcp-servers-json JSON` | experimental: inline JSON with MCP server definitions (Cursor-compatible format) - do not enable in untrusted environments (default: none)
note: for security reasons, this will limit --cors-origins to localhost by default
(env: LLAMA_ARG_MCP_SERVERS_JSON) | diff --git a/tools/server/server-models.cpp b/tools/server/server-models.cpp index 188a72a3741..93e940951e5 100644 --- a/tools/server/server-models.cpp +++ b/tools/server/server-models.cpp @@ -70,6 +70,188 @@ struct server_subproc { } }; +struct server_lru_sched { + server_lru_sched(server_models & models) : models(models) {} + + bool has_capacity(std::unique_lock & lk) { + check_lock(lk); + return models.base_params.models_max <= 0 + || count_running() < (size_t) models.base_params.models_max; + } + + // returns "" if no model can be given up + std::string pick_victim(std::unique_lock & lk, const std::string & exclude) { + check_lock(lk); + std::string victim; + int64_t victim_last_used = 0; + for (const auto & m : models.mapping) { + if (m.first == exclude) { + continue; + } + // a busy model is mid-request, one still coming up has no request to finish + if (m.second.req_count != 0 || !m.second.meta.is_ready_or_sleep()) { + continue; + } + if (victim.empty() || m.second.meta.last_used < victim_last_used) { + victim = m.first; + victim_last_used = m.second.meta.last_used; + } + } + return victim; + } + + // requests wanting the same model share one entry, so they all need only one slot + // and all get unblocked by the single load that entry performs + void join(std::unique_lock & lk, const std::string & model_id) { + check_lock(lk); + if (entry_t * e = find(model_id)) { + e->n_waiters++; + SRV_INF("request for name=%s joined the queue, %d waiting\n", model_id.c_str(), e->n_waiters); + return; + } + queue.push_back({ model_id, 1, false, false }); + SRV_INF("models_max reached, request for name=%s queued at position %zu\n", + model_id.c_str(), queue.size()); + } + + void leave(std::unique_lock & lk, const std::string & model_id) { + check_lock(lk); + for (auto it = queue.begin(); it != queue.end(); ++it) { + if (it->model_id == model_id) { + if (--it->n_waiters <= 0) { + queue.erase(it); // last one waiting for this model went away + } + return; + } + } + } + + bool queue_empty(std::unique_lock & lk) { + check_lock(lk); + return queue.empty(); + } + + // true if it is this model's turn to load, and nobody is loading it yet + bool try_claim(std::unique_lock & lk, const std::string & model_id) { + check_lock(lk); + if (queue.empty() || queue.front().model_id != model_id || queue.front().loading) { + return false; + } + if (!has_capacity(lk)) { + return false; + } + queue.front().loading = true; + return true; + } + + // ok means the model is up: drop the entry, the other waiters just watch its status now + void claim_done(std::unique_lock & lk, const std::string & model_id, bool ok) { + check_lock(lk); + for (auto it = queue.begin(); it != queue.end(); ++it) { + if (it->model_id == model_id) { + if (ok) { + queue.erase(it); + } else { + it->loading = false; + } + return; + } + } + } + + // a model is on its way out for this entry, so other requests do not also give up one + void mark_slot_pending(std::unique_lock & lk, const std::string & model_id) { + check_lock(lk); + if (entry_t * e = find(model_id)) { + e->slot_pending = true; + } + } + + // model_id went idle: give up its slot if a queued request needs one + // thread-safe, caller must NOT hold models.mutex + void on_model_idle(const std::string & model_id) { + if (models.base_params.models_max <= 0) { + return; // no limit, nothing is ever queued + } + { + std::unique_lock lk(models.mutex); + if (queue.empty()) { + return; + } + size_t promised = 0; + bool has_unserved = false; + for (const auto & e : queue) { + if (e.needs_slot()) { + has_unserved = true; + } else { + promised++; + } + } + if (!has_unserved) { + return; + } + if ((int) count_running() - (int) promised < models.base_params.models_max) { + return; // a slot is already on its way + } + // never give up a model that a queued request wants + for (const auto & e : queue) { + if (e.model_id == model_id) { + return; + } + } + auto it = models.mapping.find(model_id); + if (it == models.mapping.end() || it->second.req_count != 0 || !it->second.meta.is_ready_or_sleep()) { + return; + } + for (auto & e : queue) { + if (!e.slot_pending) { + e.slot_pending = true; + break; + } + } + } + SRV_INF("model name=%s went idle, giving up its slot to a queued request\n", model_id.c_str()); + models.unload(model_id); + } + + private: + struct entry_t { + std::string model_id; + int n_waiters; // requests waiting for this model + bool slot_pending; // a model is already being evicted for this entry + bool loading; // one of the waiters is doing the load right now + + // a slot is already coming, or already taken by the load in flight + bool needs_slot() const { return !slot_pending && !loading; } + }; + + entry_t * find(const std::string & model_id) { + for (auto & e : queue) { + if (e.model_id == model_id) { + return &e; + } + } + return nullptr; + } + + void check_lock(std::unique_lock & lk) { + GGML_ASSERT(lk.owns_lock() && lk.mutex() == &models.mutex); + } + + size_t count_running() { + size_t count = 0; + for (const auto & m : models.mapping) { + if (m.second.meta.is_running()) { + count++; + } + } + return count; + } + + server_models & models; + std::deque queue; +}; + // short loopback budget for the resumable stream router to child JSON calls (probe, lookup, // delete). distinct from params.timeout_read/write which only applies to the generation proxy static constexpr int STREAM_LOOKUP_TIMEOUT_MS = 250; @@ -229,7 +411,8 @@ server_models::server_models( : ctx_preset(LLAMA_EXAMPLE_SERVER), base_params(params), base_env(get_environment()), - base_preset(ctx_preset.load_from_args(argc, argv)) { + base_preset(ctx_preset.load_from_args(argc, argv)), + sched(std::make_unique(*this)) { // clean up base preset unset_reserved_args(base_preset, true); // set binary path @@ -241,8 +424,11 @@ server_models::server_models( LOG_WRN("using original argv[0] as fallback: %s\n", argv[0]); } load_models(); + debug_fake_timing = !common_get_env("LLAMA_SERVER_DEBUG_FAKE_TIMING").empty(); } +server_models::~server_models() = default; + void server_models::add_model(server_model_meta && meta) { if (mapping.find(meta.name) != mapping.end()) { throw std::runtime_error(string_format("model '%s' appears multiple times", meta.name.c_str())); @@ -713,22 +899,15 @@ void server_models::unload_lru() { return; // no limit } // remove one of the servers if we passed the models_max (least recently used - LRU) - std::string lru_model_name = ""; - int64_t lru_last_used = ggml_time_ms(); - size_t count_active = 0; + std::string lru_model_name; { std::unique_lock lk(mutex); - for (const auto & m : mapping) { - if (m.second.meta.is_running()) { - count_active++; - if (m.second.meta.last_used < lru_last_used) { - lru_model_name = m.first; - lru_last_used = m.second.meta.last_used; - } - } + if (sched->has_capacity(lk)) { + return; } + lru_model_name = sched->pick_victim(lk, ""); } - if (!lru_model_name.empty() && count_active >= (size_t)base_params.models_max) { + if (!lru_model_name.empty()) { SRV_INF("models_max limit reached, removing LRU name=%s\n", lru_model_name.c_str()); unload(lru_model_name); // wait for unload to complete @@ -746,6 +925,11 @@ void server_models::load(const std::string & name) { } void server_models::load(const std::string & name, const load_options & opts) { + if (debug_fake_timing) { + // do not hold the mutex here, other requests must keep making progress + std::this_thread::sleep_for(std::chrono::seconds(2)); + } + if (!opts.custom_meta.has_value()) { if (!has_model(name)) { throw std::runtime_error("model name=" + name + " is not found"); @@ -1138,7 +1322,7 @@ void server_models::wait(std::unique_lock & lk, const std::string & }); } -bool server_models::ensure_model_ready(const std::string & name) { +bool server_models::ensure_model_ready(const std::string & name, const std::function & should_stop) { auto meta = get_meta(name); if (!meta.has_value()) { throw std::runtime_error("model name=" + name + " is not found"); @@ -1149,25 +1333,112 @@ bool server_models::ensure_model_ready(const std::string & name) { if (meta->status == SERVER_MODEL_STATUS_SLEEPING) { return false; // child is sleeping but still running; new request will wake it up } - if (meta->status == SERVER_MODEL_STATUS_UNLOADED) { - SRV_INF("model name=%s is not loaded, loading...\n", name.c_str()); - load(name); + + bool queued = false; + bool did_load = false; + std::string victim; + { + std::unique_lock lk(mutex); + auto it = mapping.find(name); + if (it != mapping.end() && it->second.meta.status == SERVER_MODEL_STATUS_UNLOADED) { + bool has_capacity = sched->has_capacity(lk); + if (has_capacity && sched->queue_empty(lk)) { + lk.unlock(); + SRV_INF("model name=%s is not loaded, loading...\n", name.c_str()); + load(name); + did_load = true; + } else { + // also queue when a slot looks free but others wait already, else they starve + sched->join(lk, name); + queued = true; + if (!has_capacity) { + // an idle model may sit here right now, do not wait for a request to end + victim = sched->pick_victim(lk, name); + if (!victim.empty()) { + sched->mark_slot_pending(lk, name); + } + } + } + } + } + if (!victim.empty()) { + SRV_INF("evicting idle LRU name=%s to make room for name=%s\n", victim.c_str(), name.c_str()); + unload(victim); } - // wait for loading to complete + // while queued, this is also where the load happens: the head of the queue does it SRV_INF("waiting until model name=%s is fully loaded...\n", name.c_str()); - wait(name, [&meta](const server_model_meta & new_meta) { - if (new_meta.status != SERVER_MODEL_STATUS_LOADING) { - meta = new_meta; // update meta for final check after wait - return true; + std::unique_lock lk(mutex); + auto leave_queue = [this, &queued, &lk, &name]() { + if (queued) { + sched->leave(lk, name); + queued = false; } - return false; - }); + }; + + try { + bool saw_loading = false; + while (true) { + auto it = mapping.find(name); + if (it == mapping.end()) { + break; // removed by another code path, nothing to wait for + } + const server_model_status status = it->second.meta.status; + + if (status == SERVER_MODEL_STATUS_LOADED || status == SERVER_MODEL_STATUS_SLEEPING) { + break; + } + if (status == SERVER_MODEL_STATUS_DOWNLOADING || status == SERVER_MODEL_STATUS_DOWNLOADED) { + break; // do not wait on a download child + } + if (status == SERVER_MODEL_STATUS_LOADING) { + saw_loading = true; + } else if (status == SERVER_MODEL_STATUS_UNLOADED) { + if (did_load || saw_loading) { + // a spawn happened and the instance came back down + if (it->second.meta.is_failed()) { + throw std::runtime_error("model name=" + name + " failed to load"); + } + break; // unloaded by another code path, caller reports "not running" + } + if (!queued) { + break; // not queued, and the load someone else started fell over + } + } - // check final status - if (!meta.has_value() || meta->is_failed()) { - throw std::runtime_error("model name=" + name + " failed to load"); + if (should_stop && should_stop()) { + // if a model was evicted for us, the free slot goes to the next waiter + throw std::runtime_error("request cancelled while waiting for model name=" + name); + } + + // our turn: our model is at the head, and a slot really did free up + if (status == SERVER_MODEL_STATUS_UNLOADED && sched->try_claim(lk, name)) { + lk.unlock(); + bool ok = true; + try { + SRV_INF("slot available, loading queued model name=%s\n", name.c_str()); + load(name); + did_load = true; + } catch (const std::exception & e) { + // lost a race for the slot, stay in line and retry + SRV_WRN("queued load of name=%s did not go through: %s\n", name.c_str(), e.what()); + ok = false; + } + lk.lock(); + sched->claim_done(lk, name, ok); + if (ok) { + queued = false; // entry is gone, the other waiters watch the status now + } + continue; + } + + cv.wait_for(lk, std::chrono::milliseconds(200)); + } + } catch (...) { + leave_queue(); + throw; } + leave_queue(); return true; } @@ -1180,9 +1451,16 @@ server_http_res_ptr server_models::proxy_request(const server_http_req & req, co if (!meta->is_running()) { throw std::invalid_argument("model name=" + name + " is not running"); } - if (update_last_used) { + { std::unique_lock lk(mutex); - mapping[name].meta.last_used = ggml_time_ms(); + if (update_last_used) { + mapping[name].meta.last_used = ggml_time_ms(); + } + mapping[name].req_count++; + } + if (debug_fake_timing) { + // sleep after req_count++, so the model counts as busy while we wait here + std::this_thread::sleep_for(std::chrono::seconds(2)); } SRV_INF("proxying request to model %s on port %d\n", name.c_str(), meta->port); std::string proxy_path = req.path; @@ -1198,13 +1476,29 @@ server_http_res_ptr server_models::proxy_request(const server_http_req & req, co req.headers, req.body, req.files, - // a detached request belongs to a replay session that outlives the client socket: - // it reaches the child even when the downstream died during the load wait, the - // session buffer is the recipient and DELETE remains the stop - detached ? std::function([]() { return false; }) : req.should_stop, + // a detached request belongs to a replay session + detached + ? std::function([]() { return false; }) + : req.should_stop, base_params.timeout_read, base_params.timeout_write ); + + proxy->cleanup = [this, name]() { + bool went_idle = false; + { + std::unique_lock lk(mutex); + auto it = mapping.find(name); + if (it != mapping.end() && it->second.req_count > 0) { + it->second.req_count--; + went_idle = it->second.req_count == 0; + } + } + if (went_idle) { + sched->on_model_idle(name); + } + }; + return proxy; } @@ -1568,7 +1862,7 @@ void server_models_routes::init_routes() { return error_res; } if (autoload) { - models.ensure_model_ready(name); + models.ensure_model_ready(name, req.should_stop); } return models.proxy_request(req, method, name, false); }; @@ -1588,7 +1882,9 @@ void server_models_routes::init_routes() { // this request instead of leaving an orphan generation std::string conv_id = server_stream_conv_id_from_headers(req.headers); uint64_t ticket = models.conv_models.remember(conv_id, name); - bool waited = autoload && models.ensure_model_ready(name); + // a dead socket must not cancel a session request, only a stop does (checked right below) + auto should_stop = ticket == 0 ? req.should_stop : nullptr; + bool waited = autoload && models.ensure_model_ready(name, should_stop); if (ticket != 0 && !models.conv_models.alive(conv_id, ticket)) { SRV_INF("request for conv_id=%s cancelled while model name=%s was loading\n", conv_id.c_str(), name.c_str()); @@ -2064,7 +2360,7 @@ server_http_proxy::server_http_proxy( cli->set_write_timeout(timeout_read, 0); // reversed for cli (client) vs srv (server) cli->set_read_timeout(timeout_write, 0); this->status = 500; // to be overwritten upon response - this->cleanup = [pipe]() { + this->cleanup_pipes = [pipe]() { pipe->close_read(); pipe->close_write(); }; @@ -2079,9 +2375,8 @@ server_http_proxy::server_http_proxy( return has_next; // false if EOF or pipe broken }; - // wire up the HTTP client - // note: do NOT capture `this` pointer, as it may be destroyed before the thread ends - httplib::ResponseHandler response_handler = [pipe, cli](const httplib::Response & response) { + // build the header message forwarded to the reader thread, stripping internal proxy headers + auto make_header_msg = [](const httplib::Response & response) { msg_t msg; msg.status = response.status; for (const auto & [key, value] : response.headers) { @@ -2095,7 +2390,17 @@ server_http_proxy::server_http_proxy( } msg.headers[key] = value; } - return pipe->write(std::move(msg)); // send headers first + return msg; + }; + + // true once response_handler has already forwarded the headers + auto headers_sent = std::make_shared>(false); + + // wire up the HTTP client + // note: do NOT capture `this` pointer, as it may be destroyed before the thread ends + httplib::ResponseHandler response_handler = [pipe, headers_sent, make_header_msg](const httplib::Response & response) { + headers_sent->store(true); + return pipe->write(make_header_msg(response)); // send headers first }; httplib::ContentReceiverWithProgress content_receiver = [pipe](const char * data, size_t data_length, size_t, size_t) { // send data chunks @@ -2169,13 +2474,16 @@ server_http_proxy::server_http_proxy( // start the proxy thread SRV_DBG("start proxy thread %s %s\n", req.method.c_str(), req.path.c_str()); - this->thread = std::thread([cli, pipe, req]() { + this->thread = std::thread([cli, pipe, req, headers_sent, make_header_msg]() { auto result = cli->send(std::move(req)); if (result.error() != httplib::Error::Success) { auto err_str = httplib::to_string(result.error()); SRV_ERR("http client error: %s\n", err_str.c_str()); pipe->write({{}, 500, "", ""}); // header pipe->write({{}, 0, "proxy error: " + err_str, ""}); // body + } else if (!headers_sent->load()) { + // httplib skips response_handler for bodyless statuses like 204, send headers here instead + pipe->write(make_header_msg(*result)); } pipe->close_write(); // signal EOF to reader SRV_DBG("%s", "client request thread ended\n"); diff --git a/tools/server/server-models.h b/tools/server/server-models.h index 614798186cf..615acb577bd 100644 --- a/tools/server/server-models.h +++ b/tools/server/server-models.h @@ -84,7 +84,6 @@ struct server_model_meta { int exit_code = 0; // exit code of the model instance process (only valid if status == FAILED) int stop_timeout = 0; // seconds to wait before force-killing the model instance during shutdown mtmd_caps multimodal; // multimodal capabilities - // bool need_download = false; // whether the model needs to be downloaded before loading // TODO @ngxson: implement this bool is_ready() const { return status == SERVER_MODEL_STATUS_LOADED; @@ -94,6 +93,10 @@ struct server_model_meta { return status == SERVER_MODEL_STATUS_LOADED || status == SERVER_MODEL_STATUS_LOADING || status == SERVER_MODEL_STATUS_SLEEPING; } + bool is_ready_or_sleep() const { + return status == SERVER_MODEL_STATUS_LOADED || status == SERVER_MODEL_STATUS_SLEEPING; + } + bool is_failed() const { return status == SERVER_MODEL_STATUS_UNLOADED && exit_code != 0; } @@ -103,16 +106,19 @@ struct server_model_meta { }; struct server_models_routes; -struct server_subproc; // defined in server-models.cpp +struct server_subproc; // defined in server-models.cpp +struct server_lru_sched; // defined in server-models.cpp struct server_models { friend struct server_models_routes; + friend struct server_lru_sched; private: struct instance_t { std::shared_ptr subproc; // shared between main thread and monitoring thread std::thread th; server_model_meta meta; + int req_count = 0; // number of active proxy requests }; std::mutex mutex; @@ -191,6 +197,12 @@ struct server_models { std::vector base_env; common_preset base_preset; // base preset from llama-server CLI args + // queue of requests waiting for a models_max slot + std::unique_ptr sched; + + // if true, add some delay to simulate works (useful for testing) + bool debug_fake_timing = false; + void update_meta(const std::string & name, const server_model_meta & meta); // unload least recently used models if the limit is reached @@ -207,6 +219,7 @@ struct server_models { conv_model_tracker conv_models; server_models(const common_params & params, int argc, char ** argv); + ~server_models(); server_response sse; // for real-time updates via SSE endpoint @@ -263,7 +276,9 @@ struct server_models { // ensure the model is in ready state (thread-safe) // return false if model is ready // otherwise, load the model and blocking wait until it's ready, then return true (meta may need to be refreshed) - bool ensure_model_ready(const std::string & name); + // if models_max is reached, the request waits in a queue until a slot frees up + // throws if the load fails, or if should_stop fires while waiting + bool ensure_model_ready(const std::string & name, const std::function & should_stop = nullptr); // proxy an HTTP request to the model instance server_http_res_ptr proxy_request(const server_http_req & req, const std::string & method, const std::string & name, bool update_last_used, bool detached = false); @@ -343,7 +358,6 @@ struct server_models_routes { */ struct server_http_proxy : server_http_res { std::function cleanup = nullptr; -public: server_http_proxy(const std::string & method, const std::string & scheme, const std::string & host, @@ -357,11 +371,15 @@ struct server_http_proxy : server_http_res { int32_t timeout_write ); ~server_http_proxy() { + if (cleanup_pipes) { + cleanup_pipes(); + } if (cleanup) { cleanup(); } } private: + std::function cleanup_pipes = nullptr; std::thread thread; struct msg_t { std::map headers; diff --git a/tools/server/server-schema.cpp b/tools/server/server-schema.cpp index 5cef3908faa..5d7fa6ae6ec 100644 --- a/tools/server/server-schema.cpp +++ b/tools/server/server-schema.cpp @@ -519,7 +519,7 @@ task_params eval_llama_cmpl_schema( const json & data) { task_params params; - // Sampling parameter defaults are loaded from the global server context (but individual requests can still them) + // Sampling parameter defaults are loaded from the global server context (but individual requests can still override them) params.sampling = params_base.sampling; params.speculative = params_base.speculative; params.n_keep = params_base.n_keep; diff --git a/tools/server/server-tools.cpp b/tools/server/server-tools.cpp index 2fcb2a3c88a..27c663fdd25 100644 --- a/tools/server/server-tools.cpp +++ b/tools/server/server-tools.cpp @@ -10,12 +10,15 @@ #include #include #include +#include #include #include +#include #include #include #include #include +#include #if defined(_WIN32) # ifndef NOMINMAX @@ -71,6 +74,7 @@ json server_tool::to_json() const { {"permissions", json{ {"write", permission_write} }}, + {"uses_cwd", uses_cwd}, {"definition", get_definition()}, }; } @@ -127,6 +131,13 @@ static int entry_depth(const std::string & rel) { return 1 + (int) std::count(rel.begin(), rel.end(), '/'); } +// directories that a listing reports but never descends into: they can be enormous +// lowercase only, the local walker case-folds a name before the lookup +static const char * const SERVER_TOOL_JUNK_DIR_NAMES[] = { + ".git", ".svn", ".hg", "node_modules", "__pycache__", + ".venv", "venv", "dist", "build", "target", ".cache", ".idea", ".vscode", +}; + class tools_io { public: struct exec_result { @@ -165,6 +176,85 @@ class tools_io { const std::function & on_chunk = nullptr) const = 0; }; +// shared subprocess execution helper, used by both the local and the docker-backed tools_io implementations. +// combine_stderr=false when the raw stdout bytes must not be tainted by stderr, e.g. reading file contents. +static tools_io::exec_result run_subprocess( + const std::vector & args, + size_t max_output, + int timeout_secs, + const std::function & on_chunk, + bool combine_stderr, + const std::string & cwd = "") { + tools_io::exec_result res; + + common_subproc proc; + + int options = subprocess_option_no_window + | subprocess_option_inherit_environment + | subprocess_option_search_user_path; + if (combine_stderr) { + options |= subprocess_option_combined_stdout_stderr; + } + + if (!proc.create(args, options, {}, cwd.empty() ? nullptr : cwd.c_str())) { + res.output = "failed to spawn process"; + return res; + } + + std::atomic done{false}; + std::atomic timed_out{false}; + + std::thread timeout_thread([&]() { + auto deadline = std::chrono::steady_clock::now() + std::chrono::seconds(timeout_secs); + while (!done.load()) { + if (std::chrono::steady_clock::now() >= deadline) { + timed_out.store(true); + proc.terminate(); + return; + } + std::this_thread::sleep_for(std::chrono::milliseconds(100)); + } + }); + + FILE * f = proc.stdout_file(); + std::string output; + bool truncated = false; + if (f) { + char buf[4096]; + while (fgets(buf, sizeof(buf), f) != nullptr) { + if (!truncated) { + size_t len = strlen(buf); + if (output.size() + len <= max_output) { + output.append(buf, len); + if (on_chunk && !on_chunk(console_output_to_utf8(std::string(buf, len)))) { + proc.terminate(); + break; + } + } else { + size_t remaining = max_output - output.size(); + output.append(buf, remaining); + if (on_chunk && remaining > 0) on_chunk(console_output_to_utf8(std::string(buf, remaining))); + truncated = true; + } + } + } + } + + done.store(true); + if (timeout_thread.joinable()) { + timeout_thread.join(); + } + + res.exit_code = proc.join(); + + res.output = console_output_to_utf8(output); + res.timed_out = timed_out.load(); + if (truncated) { + res.output += "\n[output truncated]"; + } + return res; +} + class tools_io_basic : public tools_io { public: // cwd, if non-empty, is used to resolve relative paths and as the working directory for run() @@ -276,72 +366,7 @@ class tools_io_basic : public tools_io { size_t max_output, int timeout_secs, const std::function & on_chunk = nullptr) const override { - exec_result res; - - common_subproc proc; - - int options = subprocess_option_no_window - | subprocess_option_combined_stdout_stderr - | subprocess_option_inherit_environment - | subprocess_option_search_user_path; - - if (!proc.create(args, options, {}, cwd.empty() ? nullptr : cwd.c_str())) { - res.output = "failed to spawn process"; - return res; - } - - std::atomic done{false}; - std::atomic timed_out{false}; - - std::thread timeout_thread([&]() { - auto deadline = std::chrono::steady_clock::now() + std::chrono::seconds(timeout_secs); - while (!done.load()) { - if (std::chrono::steady_clock::now() >= deadline) { - timed_out.store(true); - proc.terminate(); - return; - } - std::this_thread::sleep_for(std::chrono::milliseconds(100)); - } - }); - - FILE * f = proc.stdout_file(); - std::string output; - bool truncated = false; - if (f) { - char buf[4096]; - while (fgets(buf, sizeof(buf), f) != nullptr) { - if (!truncated) { - size_t len = strlen(buf); - if (output.size() + len <= max_output) { - output.append(buf, len); - if (on_chunk && !on_chunk(console_output_to_utf8(std::string(buf, len)))) { - proc.terminate(); - break; - } - } else { - size_t remaining = max_output - output.size(); - output.append(buf, remaining); - if (on_chunk && remaining > 0) on_chunk(console_output_to_utf8(std::string(buf, remaining))); - truncated = true; - } - } - } - } - - done.store(true); - if (timeout_thread.joinable()) { - timeout_thread.join(); - } - - res.exit_code = proc.join(); - - res.output = console_output_to_utf8(output); - res.timed_out = timed_out.load(); - if (truncated) { - res.output += "\n[output truncated]"; - } - return res; + return run_subprocess(args, max_output, timeout_secs, on_chunk, /*combine_stderr=*/true, cwd); } private: @@ -384,10 +409,8 @@ class tools_io_basic : public tools_io { } static const std::unordered_set & junk_dir_names() { - static const std::unordered_set names = { - ".git", ".svn", ".hg", "node_modules", "__pycache__", - ".venv", "venv", "dist", "build", "target", ".cache", ".idea", ".vscode", - }; + static const std::unordered_set names( + std::begin(SERVER_TOOL_JUNK_DIR_NAMES), std::end(SERVER_TOOL_JUNK_DIR_NAMES)); return names; } @@ -450,9 +473,274 @@ class tools_io_basic : public tools_io { } }; +// timeout for auxiliary isolate calls (stat/mkdir/ls/cp helpers); exec_shell_command uses its own +// caller-controlled timeout instead, enforced separately in run() +static constexpr int SERVER_TOOL_ISOLATE_EXEC_TIMEOUT = 15; // seconds +static constexpr size_t SERVER_TOOL_ISOLATE_READ_FILE_MAX_SIZE = 64 * 1024 * 1024; // 64 MB + +// runs every tools_io operation as a command inside an isolate: a container, a remote host, ... +// the isolate is created, mounted, and torn down externally by the caller +// it must provide a POSIX environment: sh, cat, wc, mkdir, dirname, find, timeout +class tools_io_isolate : public tools_io { +public: + // cwd, if non-empty, is used to resolve relative paths and as the working directory for run() + explicit tools_io_isolate(std::string cwd = "") : cwd(std::move(cwd)) {} + + // resolves `path` against `cwd` if `path` is relative and `cwd` is set; otherwise returns `path` unchanged. + // isolate paths are always POSIX-style ('/'), regardless of host OS. + std::string resolve(const std::string & path) const override { + if (cwd.empty() || (!path.empty() && path[0] == '/')) { + return path; + } + return cwd + "/" + path; + } + + bool is_directory(const std::string & path) const override { + return shell_test("-d", resolve(path)); + } + + bool is_regular_file(const std::string & path) const override { + return shell_test("-f", resolve(path)); + } + + bool file_size(const std::string & path, uintmax_t & out_size) const override { + auto res = exec({"sh", "-c", "wc -c < \"$1\"", "_", resolve(path)}, 64, true); + if (res.exit_code != 0 || res.timed_out) return false; + try { + size_t pos; + out_size = (uintmax_t) std::stoull(res.output, &pos); + } catch (...) { + return false; + } + return true; + } + + bool read_file(const std::string & path, std::string & out) const override { + // combine_stderr=false: stderr must not be spliced into raw file bytes + auto res = exec({"cat", "--", resolve(path)}, SERVER_TOOL_ISOLATE_READ_FILE_MAX_SIZE, false); + if (res.exit_code != 0 || res.timed_out) return false; + out = res.output; + return true; + } + + bool write_file(const std::string & path, const std::string & content) const override { + std::string abs_path = resolve(path); + + std::error_code ec; + fs::path tmp_dir = fs::temp_directory_path(ec); + if (ec) return false; + + static std::atomic tmp_counter{0}; + fs::path tmp = tmp_dir / string_format( + "llama-tools-io-isolate-%zu-%llu.tmp", + std::hash{}(std::this_thread::get_id()), + (unsigned long long) tmp_counter.fetch_add(1)); + + { + std::ofstream f(tmp, std::ios::binary); + if (!f) return false; + f << content; + if (!f) return false; + } + + bool ok = shell_run({"sh", "-c", "mkdir -p \"$(dirname \"$1\")\"", "_", abs_path}); + if (ok) { + ok = upload(tmp.string(), abs_path); + } + + std::error_code rm_ec; + fs::remove(tmp, rm_ec); + return ok; + } + + list_result list_entries(const std::string & base, int max_depth, list_kind kind) const override { + list_result out; + + const std::string abs_base = resolve(base); + if (!is_directory(base)) { + out.err = "path does not exist or is not a directory"; + return out; + } + + // git ls-files cannot list directories; use the walker when they are requested + if (kind == list_kind::files) { + auto res = exec( + {"sh", "-c", "cd \"$1\" && git ls-files --cached --others --exclude-standard", "_", abs_base}, + SERVER_TOOL_GIT_LS_FILES_MAX_OUTPUT, true); + + if (res.exit_code == 0 && !res.timed_out) { + for (const auto & rel : split_lines(res.output, /*strip_dot_slash=*/false)) { + if (max_depth > 0 && entry_depth(rel) > max_depth) continue; + out.entries.push_back({rel, false}); + } + return out; + } + } + + if (kind == list_kind::dirs || kind == list_kind::all) { + for (auto & rel : find_entries(abs_base, max_depth, /*dirs=*/true, out.truncated)) { + out.entries.push_back({std::move(rel), true}); + } + } + if (kind == list_kind::files || kind == list_kind::all) { + for (auto & rel : find_entries(abs_base, max_depth, /*dirs=*/false, out.truncated)) { + out.entries.push_back({std::move(rel), false}); + } + } + + return out; + } + + // wraps the command with an in-isolate `timeout`, since killing the host-side client + // does not kill the process tree running inside the isolate + exec_result run( + const std::vector & args, + size_t max_output, + int timeout_secs, + const std::function & on_chunk = nullptr) const override { + std::vector inner = {"timeout", std::to_string(timeout_secs) + "s"}; + inner.insert(inner.end(), args.begin(), args.end()); + // small buffer over timeout_secs so the in-isolate `timeout` has a chance to exit cleanly + // before the host-side supervisory timeout forcibly kills the client + return run_subprocess( + build_argv(with_cwd(inner), /*needs_stdin=*/true), + max_output, timeout_secs + 5, on_chunk, true); + } + +protected: + // wrap `inner` (a complete POSIX argv) into the host-side argv that runs it in the isolate + // a transport that re-parses its args in a remote shell (ssh) must join `inner` with shell_quote_join() + virtual std::vector build_argv(const std::vector & inner, bool needs_stdin) const = 0; + + // copy a host file into the isolate, `isolate_path` is absolute and its parent already exists + virtual bool upload(const std::string & host_path, const std::string & isolate_path) const = 0; + + // quote `argv` into a single string that a POSIX shell re-parses into exactly `argv` + static std::string shell_quote_join(const std::vector & argv) { + std::string out; + for (const auto & arg : argv) { + if (!out.empty()) out += ' '; + out += '\''; + for (const char c : arg) { + // a single quote cannot be escaped inside single quotes: close, escape, reopen + if (c == '\'') out += "'\\''"; + else out += c; + } + out += '\''; + } + return out; + } + +private: + std::string cwd; + + // set the working directory in the command itself, docker's `-w` has no equivalent on every transport + // auxiliary calls do not need this, they use the absolute paths from resolve() + std::vector with_cwd(const std::vector & inner) const { + if (cwd.empty()) { + return inner; + } + // 127 is what a shell reports for a command it could not run + std::vector out = {"sh", "-c", "cd \"$1\" || exit 127; shift; exec \"$@\"", "_", cwd}; + out.insert(out.end(), inner.begin(), inner.end()); + return out; + } + + exec_result exec(const std::vector & inner, size_t max_output, bool combine_stderr) const { + return run_subprocess( + build_argv(inner, /*needs_stdin=*/false), + max_output, SERVER_TOOL_ISOLATE_EXEC_TIMEOUT, nullptr, combine_stderr); + } + + bool shell_run(const std::vector & inner) const { + auto res = exec(inner, 4096, true); + return res.exit_code == 0 && !res.timed_out; + } + + bool shell_test(const char * flag, const std::string & path) const { + return shell_run({"sh", "-c", std::string("[ ") + flag + " \"$1\" ]", "_", path}); + } + + static std::vector split_lines(const std::string & text, bool strip_dot_slash) { + std::vector result; + std::istringstream iss(text); + std::string line; + while (std::getline(iss, line)) { + if (!line.empty() && line.back() == '\r') line.pop_back(); + if (line.empty()) continue; + if (strip_dot_slash && line.rfind("./", 0) == 0) line = line.substr(2); + std::replace(line.begin(), line.end(), '\\', '/'); + result.push_back(line); + } + return result; + } + + // one `find` pass in the isolate. junk directories stay selectable but are never descended into, + // and -mindepth/-maxdepth keep a busybox image working as well as a GNU one + std::vector find_entries(const std::string & abs_base, int max_depth, bool dirs, bool & truncated) const { + std::string prune_expr; + for (const char * n : SERVER_TOOL_JUNK_DIR_NAMES) { + if (!prune_expr.empty()) prune_expr += " -o "; + prune_expr += std::string("-name ") + n; + } + + std::string cmd = "cd \"$1\" && find . -mindepth 1"; + if (max_depth > 0) { + cmd += " -maxdepth " + std::to_string(max_depth); + } + cmd += " \\( " + prune_expr + " \\) -prune"; + cmd += dirs ? " -print -o -type d -print" : " -o -type f -print"; + + auto res = exec({"sh", "-c", cmd, "_", abs_base}, SERVER_TOOL_GIT_LS_FILES_MAX_OUTPUT, true); + truncated = truncated || res.timed_out; + return split_lines(res.output, /*strip_dot_slash=*/true); + } +}; + +// an already-running docker container, driven through `docker exec` and `docker cp` +class tools_io_docker : public tools_io_isolate { +public: + tools_io_docker(std::string container_id, std::string cwd = "") + : tools_io_isolate(std::move(cwd)), container_id(std::move(container_id)) {} + +protected: + std::vector build_argv(const std::vector & inner, bool needs_stdin) const override { + std::vector argv = {"docker", "exec"}; + if (needs_stdin) { + argv.push_back("-i"); + } + argv.push_back(container_id); + argv.insert(argv.end(), inner.begin(), inner.end()); + return argv; + } + + bool upload(const std::string & host_path, const std::string & isolate_path) const override { + auto res = run_subprocess( + {"docker", "cp", host_path, container_id + ":" + isolate_path}, + 4096, SERVER_TOOL_ISOLATE_EXEC_TIMEOUT, nullptr, true); + return res.exit_code == 0 && !res.timed_out; + } + +private: + std::string container_id; +}; + +// runtime spec used by --tools-runtime and the x-tool-runtime header +// this is the only scheme for now, ssh: and podman: can be added next to it +static const std::string SERVER_TOOL_RUNTIME_DOCKER_CONTAINER = "docker-container:"; + +// an empty runtime runs the tools on the host static std::unique_ptr make_tools_io(const json & params) { - std::string cwd = json_value(params, "cwd", std::string()); - return std::make_unique(cwd); + std::string cwd = json_value(params, "cwd", std::string()); + std::string runtime = json_value(params, "runtime", std::string()); + if (runtime.empty()) { + return std::make_unique(cwd); + } + if (runtime.rfind(SERVER_TOOL_RUNTIME_DOCKER_CONTAINER, 0) == 0) { + return std::make_unique(runtime.substr(SERVER_TOOL_RUNTIME_DOCKER_CONTAINER.size()), cwd); + } + // do not fall back to the host, the caller asked for an isolate + throw std::runtime_error("unknown tool runtime: " + runtime); } // no '/' in pattern -> match basename at any depth; else match full relative path @@ -476,6 +764,7 @@ struct server_tool_read_file : server_tool { server_tool_read_file() { name = "read_file"; display_name = "Read file"; + uses_cwd = true; permission_write = false; } @@ -564,6 +853,7 @@ struct server_tool_file_glob_search : server_tool { server_tool_file_glob_search() { name = "file_glob_search"; display_name = "File search"; + uses_cwd = true; permission_write = false; } @@ -678,6 +968,7 @@ struct server_tool_grep_search : server_tool { server_tool_grep_search() { name = "grep_search"; display_name = "Grep search"; + uses_cwd = true; permission_write = false; } @@ -830,6 +1121,7 @@ struct server_tool_exec_shell_command : server_tool { server_tool_exec_shell_command() { name = "exec_shell_command"; display_name = "Execute shell command"; + uses_cwd = true; permission_write = true; support_stream = true; } @@ -861,8 +1153,11 @@ struct server_tool_exec_shell_command : server_tool { timeout = std::min(timeout, SERVER_TOOL_EXEC_SHELL_COMMAND_MAX_TIMEOUT); max_output = std::min(max_output, SERVER_TOOL_EXEC_SHELL_COMMAND_MAX_OUTPUT_SIZE); + // an isolate is always POSIX regardless of host OS, so it always gets `sh -c` #ifdef _WIN32 - std::vector args = {"cmd", "/c", command}; + std::vector args = !json_value(params, "runtime", std::string()).empty() + ? std::vector{"sh", "-c", command} + : std::vector{"cmd", "/c", command}; #else std::vector args = {"sh", "-c", command}; #endif @@ -905,6 +1200,7 @@ struct server_tool_write_file : server_tool { server_tool_write_file() { name = "write_file"; display_name = "Write file"; + uses_cwd = true; permission_write = true; } @@ -947,6 +1243,7 @@ struct server_tool_edit_file : server_tool { server_tool_edit_file() { name = "edit_file"; display_name = "Edit file"; + uses_cwd = true; permission_write = true; } @@ -1335,6 +1632,7 @@ struct server_tool_get_info : server_tool { server_tool_get_info() { name = "get_info"; display_name = "Get Runtime Info"; + uses_cwd = true; permission_write = false; } @@ -1355,19 +1653,29 @@ struct server_tool_get_info : server_tool { json invoke(json params, server_tool::stream *) const override { auto io = make_tools_io(params); + // inside an isolate, we always use the linux command #ifdef _WIN32 - auto res = io->run({"cmd", "/c", "ver"}, SERVER_TOOL_GET_INFO_MAX_OUTPUT, SERVER_TOOL_GET_INFO_TIMEOUT); + std::vector args = !json_value(params, "runtime", std::string()).empty() + ? std::vector{"uname", "-a"} + : std::vector{"cmd", "/c", "ver"}; #else - auto res = io->run({"uname", "-a"}, SERVER_TOOL_GET_INFO_MAX_OUTPUT, SERVER_TOOL_GET_INFO_TIMEOUT); + std::vector args = {"uname", "-a"}; #endif + + auto res = io->run(args, SERVER_TOOL_GET_INFO_MAX_OUTPUT, SERVER_TOOL_GET_INFO_TIMEOUT); // "ver" prints a blank line before the version, so the output is stripped on both ends; // a failed spawn or a timeout leaves a diagnostic in res.output, which is not an OS name std::string os_info = res.exit_code == 0 && !res.timed_out ? string_strip(res.output) : "unknown"; std::string cwd = json_value(params, "cwd", std::string()); if (cwd.empty()) { - std::error_code ec; - cwd = path_to_utf8(fs::current_path(ec)); + if (json_value(params, "runtime", std::string()).empty()) { + std::error_code ec; + cwd = path_to_utf8(fs::current_path(ec)); + } else { + auto pwd = io->run({"pwd"}, SERVER_TOOL_GET_INFO_MAX_OUTPUT, SERVER_TOOL_GET_INFO_TIMEOUT); + cwd = pwd.exit_code == 0 && !pwd.timed_out ? string_strip(pwd.output) : "unknown"; + } } return { @@ -1461,6 +1769,103 @@ struct server_mcp_tool : server_tool { } }; +// owns the docker container used as the sandboxed runtime for tool invocations, as configured by +// --tools-runtime. "spawned" mode starts and stops the container itself; "existing" mode just reuses +// a container id the user already has running and never stops it. +struct server_tools_docker_runtime { + server_tools_docker_runtime(const server_tools_docker_runtime &) = delete; + + explicit server_tools_docker_runtime(const std::string & spec) { + static const std::string docker_prefix = "docker:"; + if (spec.rfind(docker_prefix, 0) == 0) { + spawned = true; + image = spec.substr(docker_prefix.size()); + if (image.empty()) { + throw std::runtime_error("--tools-runtime docker: requires an image name"); + } + spawn(); + } else if (spec.rfind(SERVER_TOOL_RUNTIME_DOCKER_CONTAINER, 0) == 0) { + spawned = false; + container_id = spec.substr(SERVER_TOOL_RUNTIME_DOCKER_CONTAINER.size()); + if (container_id.empty()) { + throw std::runtime_error("--tools-runtime docker-container: requires a container id"); + } + } else { + throw std::runtime_error("unknown --tools-runtime option: " + spec); + } + } + + ~server_tools_docker_runtime() { + if (spawned && !container_id.empty()) { + // closing stdin signals the container's shell (its pid 1) to exit; --rm then removes it + proc.close_stdin(); + proc.join(); + } + } + + // container id to use for the next tool call; respawns a spawned container that died on its own, + // or throws if an externally-managed one is no longer reachable + std::string get_container_id() { + std::lock_guard lock(mutex); + if (!spawned) { + if (!is_running(container_id)) { + throw std::runtime_error(string_format( + "docker container \"%s\" is no longer running, restart it to keep using tools", + container_id.c_str())); + } + return container_id; + } + + if (!proc.alive()) { + SRV_WRN("docker tools runtime container \"%s\" died, respawning\n", container_id.c_str()); + spawn(); + } + return container_id; + } + +private: + bool spawned = false; + std::string image; // spawned mode only + std::string container_id; + common_subproc proc; // spawned mode only: `docker run` client that keeps the container alive + std::mutex mutex; + + // spawns "docker run --rm -i sh" and keeps its stdin open; the shell blocks reading stdin, + // so the container stays alive until we close it (see destructor) or it is killed from the outside + void spawn() { + std::error_code ec; + fs::path cidfile = fs::temp_directory_path(ec) / string_format( + "llama-tools-runtime-cid-%zu.tmp", std::hash{}(std::this_thread::get_id())); + fs::remove(cidfile, ec); + + std::vector args = {"docker", "run", "--rm", "-i", "--cidfile", cidfile.string(), image, "sh"}; + int options = subprocess_option_no_window + | subprocess_option_inherit_environment + | subprocess_option_search_user_path; + if (!proc.create(args, options)) { + throw std::runtime_error("failed to spawn docker container for tools runtime (image: " + image + ")"); + } + + std::string cid; + for (int i = 0; i < 100 && cid.empty(); i++) { + std::ifstream f(cidfile); + if (f) std::getline(f, cid); + if (cid.empty()) std::this_thread::sleep_for(std::chrono::milliseconds(100)); + } + fs::remove(cidfile, ec); + if (cid.empty()) { + proc.terminate(); + throw std::runtime_error("timed out waiting for docker container to start (image: " + image + ")"); + } + container_id = cid; + } + + static bool is_running(const std::string & id) { + auto res = run_subprocess({"docker", "inspect", "-f", "{{.State.Running}}", id}, 16, 5, nullptr, true); + return res.exit_code == 0 && !res.timed_out && res.output.rfind("true", 0) == 0; + } +}; + static server_tool & find_tool(std::vector> & tools, const std::string & name, bool require_stream) { for (auto & t : tools) { if (t->name == name) { @@ -1506,8 +1911,16 @@ static std::string get_header(const std::map & headers return default_value; } +server_tools::server_tools() = default; +server_tools::~server_tools() = default; + void server_tools::setup(const std::vector & enabled_tools, - server_mcp & mcp_mgr) { + server_mcp & mcp_mgr, + const std::string & tools_runtime) { + if (!tools_runtime.empty()) { + docker_runtime = std::make_unique(tools_runtime); + } + if (!enabled_tools.empty()) { if (!common_subproc::is_supported()) { throw std::runtime_error("subprocess is not enabled on this build"); @@ -1590,11 +2003,26 @@ void server_tools::setup(const std::vector & enabled_tools, bool stream = body.value("stream", false); // accept x-tool-cwd header to override of the process + if (params.contains("cwd")) { + params.erase("cwd"); + } auto cwd = get_header(req.headers, "x-tool-cwd"); if (!cwd.empty()) { params["cwd"] = cwd; } + // accept x-tool-runtime header to route tool I/O through an isolate, e.g. "docker-container:"; + // falls back to the --tools-runtime isolate, if configured + if (params.contains("runtime")) { + params.erase("runtime"); + } + auto runtime = get_header(req.headers, "x-tool-runtime"); + if (!runtime.empty()) { + params["runtime"] = runtime; + } else if (docker_runtime) { + params["runtime"] = SERVER_TOOL_RUNTIME_DOCKER_CONTAINER + docker_runtime->get_container_id(); + } + server_tool & tool = find_tool(tools, tool_name, stream); if (stream) { diff --git a/tools/server/server-tools.h b/tools/server/server-tools.h index 601399ee939..ede303181b6 100644 --- a/tools/server/server-tools.h +++ b/tools/server/server-tools.h @@ -14,6 +14,7 @@ struct server_tool { std::string display_name; bool permission_write = false; bool support_stream = false; // if true, output can be streamed + bool uses_cwd = false; // if true, the tool resolves paths and runs against the working directory virtual ~server_tool() = default; virtual json get_definition() const = 0; @@ -30,6 +31,8 @@ struct server_tool { json to_json() const; }; +struct server_tools_docker_runtime; // impl detail, defined in server-tools.cpp + struct server_tools { std::vector> tools; @@ -37,9 +40,16 @@ struct server_tools { server_response queue_res; std::atomic res_id{0}; + // set when --tools-runtime is configured; owns the docker container used to run tools, if any + std::unique_ptr docker_runtime; + void setup(const std::vector & enabled_tools, - server_mcp & mcp_mgr); + server_mcp & mcp_mgr, + const std::string & tools_runtime); server_http_context::handler_t handle_get; server_http_context::handler_t handle_post; + + server_tools(); + ~server_tools(); }; diff --git a/tools/server/server.cpp b/tools/server/server.cpp index aafb1f30796..1b2e6edb4ed 100644 --- a/tools/server/server.cpp +++ b/tools/server/server.cpp @@ -338,7 +338,7 @@ int llama_server(common_params & params, int argc, char ** argv) { if (!params.server_tools.empty() || !mcp_mgr.empty()) { try { - tools.setup(params.server_tools, mcp_mgr); + tools.setup(params.server_tools, mcp_mgr, params.server_tools_runtime); } catch (const std::exception & e) { SRV_ERR("tools setup failed: %s\n", e.what()); return 1; @@ -348,6 +348,9 @@ int llama_server(common_params & params, int argc, char ** argv) { if (!params.server_tools.empty()) { warn_names.push_back("built-in tools (experimental)"); } + if (!params.server_tools_runtime.empty()) { + warn_names.push_back("tools runtime (experimental)"); + } if (!mcp_mgr.empty()) { warn_names.push_back("MCP servers (experimental)"); } diff --git a/tools/server/tests/conftest.py b/tools/server/tests/conftest.py index c7ed775968b..5dfde407967 100644 --- a/tools/server/tests/conftest.py +++ b/tools/server/tests/conftest.py @@ -15,7 +15,7 @@ def stop_server_after_each_test(): server.stop() -@pytest.fixture(scope="module", autouse=True) -def do_something(): +@pytest.fixture(scope="session", autouse=True) +def load_server_presets(): # this will be run once per test session, before any tests ServerPreset.load_all() diff --git a/tools/server/tests/tests.sh b/tools/server/tests/tests.sh index 709b5841aa4..8d6681193db 100755 --- a/tools/server/tests/tests.sh +++ b/tools/server/tests/tests.sh @@ -14,10 +14,10 @@ fi if [ $# -lt 1 ] then if [[ "${SLOW_TESTS:-0}" == 1 ]]; then - pytest -v -x + pytest --durations=30 -v -x else - pytest -v -x -m "not slow" + pytest --durations=30 -v -x -m "not slow" fi else - pytest "$@" + pytest --durations=30 "$@" fi diff --git a/tools/server/tests/unit/test_proxy.py b/tools/server/tests/unit/test_proxy.py index 0fed536e59a..cb439b7a456 100644 --- a/tools/server/tests/unit/test_proxy.py +++ b/tools/server/tests/unit/test_proxy.py @@ -1,5 +1,7 @@ import pytest from utils import * +import threading +from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer server = ServerPreset.tinyllama2() @@ -39,3 +41,31 @@ def test_mcp_proxy_custom_port(): res = server.make_request("GET", f"/cors-proxy?url=http://{server.server_host}:{server.server_port}/models") assert res.status_code == 200 assert "data" in res.body + + +def test_mcp_proxy_no_content(): + # note: see issue #26598 + class NoContentHandler(BaseHTTPRequestHandler): + def do_POST(self): + self.send_response(204) + self.end_headers() + + def log_message(self, format, *args): + pass + + target = ThreadingHTTPServer(("127.0.0.1", 0), NoContentHandler) + target_thread = threading.Thread(target=target.serve_forever, daemon=True) + target_thread.start() + + try: + global server + server.ui_mcp_proxy = True + server.start() + + res = server.make_request("POST", f"/cors-proxy?url=http://127.0.0.1:{target.server_port}/", data={}) + assert res.status_code == 204 + assert res.body in (None, b"", "") + finally: + target.shutdown() + target.server_close() + diff --git a/tools/server/tests/unit/test_router.py b/tools/server/tests/unit/test_router.py index 94165e520e6..5ab62666ce1 100644 --- a/tools/server/tests/unit/test_router.py +++ b/tools/server/tests/unit/test_router.py @@ -85,7 +85,7 @@ def _wait_for_model_status(model_id: str, desired: set[str], timeout: int = 60) last_status = _get_model_status(model_id) if last_status in desired: return last_status - time.sleep(1) + time.sleep(0.01) raise AssertionError( f"Timed out waiting for {model_id} to reach {desired}, last status: {last_status}" ) @@ -145,6 +145,156 @@ def test_router_models_max_evicts_lru(): assert _get_model_status(first) == "unloaded" +# server_lru_sched tests (relying on LLAMA_SERVER_DEBUG_FAKE_TIMING) + +MODEL_A = "ggml-org/tinygemma3-GGUF:Q8_0" +MODEL_B = "ggml-org/test-model-stories260K:F32" +MODEL_C = "ggml-org/test-model-stories260K-infill:F32" + + +def _tokenize(model_id: str, timeout: float | None = DEFAULT_REQUEST_TIMEOUT) -> ServerResponse: + return server.make_request( + "POST", "/tokenize", data={"model": model_id, "content": "hello world"}, timeout=timeout + ) + + +class _Bg: + """runs one request in a thread, keeps its result, error and finish time""" + + def __init__(self, fn): + self.result = None + self.error: Exception | None = None + self.done_at: float = 0.0 + self._thread = threading.Thread(target=self._run, args=(fn,), daemon=True) + + def _run(self, fn): + try: + self.result = fn() + except Exception as e: + self.error = e + self.done_at = time.time() + + def start(self): + self._thread.start() + return self + + def join(self, timeout: int = 180): + self._thread.join(timeout) + assert not self._thread.is_alive(), "background request did not finish in time" + return self + + def assert_ok(self, what: str): + assert self.error is None, f"{what} raised {self.error!r}" + assert self.result is not None and self.result.status_code == 200, \ + f"{what} failed: {self.result.status_code if self.result else None} {self.result.body if self.result else None}" + + +def test_router_queue_does_not_evict_busy_model(): + """a request that finds no free slot waits, and the model serving a request survives it""" + global server + server.models_max = 1 + server.start() + + _load_model_and_wait(MODEL_A, timeout=120) + + busy = _Bg(lambda: _tokenize(MODEL_A)).start() + time.sleep(0.5) # let the request reach the child and take the only slot + + # no slot free and MODEL_A is busy, so this queues instead of evicting mid-request + queued = _Bg(lambda: _tokenize(MODEL_B)).start() + + busy.join() + queued.join() + + # had MODEL_A been evicted while serving, its own request would have died + busy.assert_ok("request against the busy model") + queued.assert_ok("queued request") + + _wait_for_model_status(MODEL_B, {"loaded"}, timeout=120) + assert _get_model_status(MODEL_A) == "unloaded" + + +def test_router_queue_coalesces_requests_for_same_model(): + """many requests for one missing model share a slot, so only one model is given up""" + global server + server.models_max = 2 + server.start() + + _load_model_and_wait(MODEL_A, timeout=120) + _load_model_and_wait(MODEL_B, timeout=120) + + # keep MODEL_A busy so MODEL_B is the only model that can be given up + busy = _Bg(lambda: _tokenize(MODEL_A)).start() + time.sleep(0.5) + + waiters = [_Bg(lambda: _tokenize(MODEL_C)).start() for _ in range(3)] + + busy.join() + for w in waiters: + w.join() + + busy.assert_ok("request against the busy model") + for i, w in enumerate(waiters): + w.assert_ok(f"queued request {i}") + + _wait_for_model_status(MODEL_C, {"loaded"}, timeout=120) + # one entry for 3 requests means one eviction: MODEL_B goes, MODEL_A is left alone. + # without coalescing the leftover entries still ask for a slot, + # and MODEL_A is taken too as soon as it goes idle + assert _get_model_status(MODEL_A) == "loaded" + assert _get_model_status(MODEL_B) == "unloaded" + + +def test_router_queue_client_disconnect_keeps_model(): + """a client that leaves while queued must not cost a running model its slot""" + global server + server.models_max = 1 + server.start() + + _load_model_and_wait(MODEL_A, timeout=120) + + busy = _Bg(lambda: _tokenize(MODEL_A)).start() + time.sleep(0.5) + + # queues behind MODEL_A, then gives up long before MODEL_A goes idle + with pytest.raises(requests.exceptions.RequestException): + _tokenize(MODEL_B, timeout=1) + + busy.join() + busy.assert_ok("request against the busy model") + + # nobody is waiting anymore, so MODEL_A keeps its slot + time.sleep(3) + assert _get_model_status(MODEL_A) == "loaded" + assert _get_model_status(MODEL_B) == "unloaded" + + +def test_router_queue_is_fifo(): + """the queue is served in arrival order""" + global server + server.models_max = 1 + server.start() + + _load_model_and_wait(MODEL_A, timeout=120) + + busy = _Bg(lambda: _tokenize(MODEL_A)).start() + time.sleep(0.5) + + first = _Bg(lambda: _tokenize(MODEL_B)).start() + time.sleep(1) # keep the arrival order unambiguous + second = _Bg(lambda: _tokenize(MODEL_C)).start() + + busy.join() + first.join() + second.join() + + busy.assert_ok("request against the busy model") + first.assert_ok("first queued request") + second.assert_ok("second queued request") + + assert first.done_at < second.done_at, "queue was not served in arrival order" + + def test_router_no_models_autoload(): global server server.no_models_autoload = True @@ -310,7 +460,7 @@ def _wait_for_sse_event(collected: list, event_type: str, model: str, timeout: i while time.time() < deadline: if any(e.get("event") == event_type and e.get("model") == model for e in collected): return True - time.sleep(0.5) + time.sleep(0.01) return False diff --git a/tools/server/tests/unit/test_tools_builtin.py b/tools/server/tests/unit/test_tools_builtin.py index 11c82e690ad..c651e8e72db 100755 --- a/tools/server/tests/unit/test_tools_builtin.py +++ b/tools/server/tests/unit/test_tools_builtin.py @@ -1,4 +1,6 @@ import os +import shutil +import subprocess import pytest from utils import * @@ -146,6 +148,95 @@ def test_tools_builtin_cwd_header(): os.remove(marker_path) +def _docker_unavailable_reason() -> str | None: + """None if docker can be used to run a container, otherwise the reason it can't.""" + docker_bin = shutil.which("docker") + if docker_bin is None: + return "docker is not installed" + try: + subprocess.run([docker_bin, "info"], capture_output=True, timeout=5, check=True) + except Exception as e: + return f"docker daemon is not usable: {e}" + return None + + +@pytest.fixture +def docker_container(): + reason = _docker_unavailable_reason() + if reason is not None: + pytest.skip(reason) # ty: ignore[too-many-positional-arguments, invalid-argument-type] + + proc = subprocess.run( + ["docker", "run", "-d", "--rm", "busybox", "sleep", "300"], + capture_output=True, text=True, + ) + if proc.returncode != 0: + pytest.skip(f"failed to start docker container: {proc.stderr.strip()}") # ty: ignore[too-many-positional-arguments, invalid-argument-type] + + container_id = proc.stdout.strip() + try: + yield container_id + finally: + subprocess.run(["docker", "rm", "-f", container_id], capture_output=True) + + +def test_tools_builtin_runtime_header(docker_container: str): + global server + server.start() + + headers = {"x-tool-runtime": f"docker-container:{docker_container}", "x-tool-cwd": "/tmp"} + + write_res = call_tool("write_file", {"path": "test.log", "content": "hello docker\n"}, headers=headers) + assert write_res["result"] == "file written successfully" + + read_res = call_tool("read_file", {"path": "test.log"}, headers=headers) + assert read_res["plain_text_response"] == "hello docker\n" + + exec_res = call_tool("exec_shell_command", {"command": "cat test.log"}, headers=headers) + assert "hello docker" in exec_res["plain_text_response"] + + +def test_tools_builtin_runtime_header_unknown_scheme(): + global server + server.start() + + # an unknown runtime must fail, never silently fall back to running on the host + res = server.make_request("POST", "/tools", + data={"tool": "exec_shell_command", "params": {"command": "echo hi"}}, + headers={"x-tool-runtime": "ssh:example.com"}) + assert res.status_code == 500, res.body + assert "unknown tool runtime" in str(res.body) + + +def test_tools_builtin_docker_runtime_cleans_up_spawned_container(): + reason = _docker_unavailable_reason() + if reason is not None: + pytest.skip(reason) # ty: ignore[too-many-positional-arguments, invalid-argument-type] + + global server + server.server_tools_runtime = "docker:busybox" + server.start() + + # exec_shell_command runs inside the container spawned for --tools-runtime; docker sets + # the container's hostname to its own short id, so this also tells us which one to check + res = call_tool("exec_shell_command", {"command": "hostname"}) + container_id = res["plain_text_response"].splitlines()[0].strip() + assert len(container_id) >= 8, res + + running = subprocess.run( + ["docker", "inspect", "-f", "{{.State.Running}}", container_id], + capture_output=True, text=True, + ) + assert running.returncode == 0 and running.stdout.strip() == "true", running.stderr + + server.stop() + + # a clean server shutdown must stop and remove the container it spawned (it runs with --rm), + # not leave it behind as an abandoned child + leftover = subprocess.run(["docker", "inspect", container_id], capture_output=True, text=True) + assert leftover.returncode != 0, f"container {container_id} was not cleaned up after server exit" + + def test_tools_builtin_edit_file_rejects_overlapping_edits(): global server server.start() diff --git a/tools/server/tests/utils.py b/tools/server/tests/utils.py index ae56bc70a15..fffe07a6711 100644 --- a/tools/server/tests/utils.py +++ b/tools/server/tests/utils.py @@ -115,6 +115,7 @@ class ServerProcess: backend_sampling: bool = False gcp_compat: bool = False server_tools: str | None = None + server_tools_runtime: str | None = None mcp_servers_config: str | None = None mcp_servers_json: str | None = None cors_origins: str | None = None @@ -132,7 +133,10 @@ def __init__(self): self.external_server = "DEBUG_EXTERNAL" in os.environ def start(self, timeout_seconds: int = DEFAULT_HTTP_TIMEOUT) -> None: - env = {**os.environ} + env = { + **os.environ, + "LLAMA_SERVER_DEBUG_FAKE_TIMING": "1", + } if "LLAMA_CACHE" not in os.environ: env["LLAMA_CACHE"] = "tmp" if self.external_server: @@ -267,6 +271,8 @@ def start(self, timeout_seconds: int = DEFAULT_HTTP_TIMEOUT) -> None: server_args.append("--ui-mcp-proxy") if self.server_tools: server_args.extend(["--tools", self.server_tools]) + if self.server_tools_runtime: + server_args.extend(["--tools-runtime", self.server_tools_runtime]) if self.mcp_servers_config: server_args.extend(["--mcp-servers-config", self.mcp_servers_config]) if self.mcp_servers_json: @@ -303,6 +309,7 @@ def start(self, timeout_seconds: int = DEFAULT_HTTP_TIMEOUT) -> None: # wait for server to start start_time = time.time() + last_print_time = start_time while time.time() - start_time < timeout_seconds: try: response = self.make_request("GET", "/health", headers={ @@ -317,8 +324,10 @@ def start(self, timeout_seconds: int = DEFAULT_HTTP_TIMEOUT) -> None: if self.process.poll() is not None: raise RuntimeError(f"Server process died with return code {self.process.returncode}") - print(f"Waiting for server to start...") - time.sleep(0.5) + if time.time() - last_print_time >= 1.0: + print(f"Waiting for server to start...") + last_print_time = time.time() + time.sleep(0.01) raise TimeoutError(f"Server did not start within {timeout_seconds} seconds") def stop(self) -> None: diff --git a/tools/tts/tts.cpp b/tools/tts/tts.cpp index b68edcaf575..49c405e1478 100644 --- a/tools/tts/tts.cpp +++ b/tools/tts/tts.cpp @@ -179,17 +179,20 @@ int main(int argc, char ** argv) { const char * data = nullptr; size_t data_len = 0; int64_t n_samples = 0; + const int64_t t_wav_start_us = ggml_time_us(); if (gen.get_output(&sample_rate, &data, &data_len, &n_samples) != 0) { LOG_ERR("get_output failed\n"); return 1; } + const double t_wav_s = (ggml_time_us() - t_wav_start_us) / 1e6; LOG_INF("generated %d frames, %zu bytes of WAV audio (%d Hz)\n", n_frames, data_len, sample_rate); const double t_prompt_s = (t_gen_start_us - t_prompt_start_us) / 1e6; - const double t_total_s = t_prompt_s + t_gen_s; + const double t_total_s = t_prompt_s + t_gen_s + t_wav_s; const double audio_s = sample_rate > 0 ? (double) n_samples / sample_rate : 0.0; - LOG_INF("timings: prompt eval %.2fs + generation %.2fs = total %.2fs\n", t_prompt_s, t_gen_s, t_total_s); + LOG_INF("timings: prompt eval %.2fs + generation %.2fs + vocoder %.2fs = total %.2fs\n", + t_prompt_s, t_gen_s, t_wav_s, t_total_s); LOG_INF(" output audio = %.2fs (audio time = %.2fx process time)\n", audio_s, t_total_s > 0 ? audio_s / t_total_s : 0.0); FILE * f = fopen(params.out_file.c_str(), "wb"); if (!f) { diff --git a/tools/ui/.npmrc b/tools/ui/.npmrc index 32e6012709b..0a690322a45 100644 --- a/tools/ui/.npmrc +++ b/tools/ui/.npmrc @@ -1,2 +1,3 @@ engine-strict=true ignore-scripts=true +min-release-age=7 diff --git a/tools/ui/src/app.d.ts b/tools/ui/src/app.d.ts index b9484d95031..814fcf5231d 100644 --- a/tools/ui/src/app.d.ts +++ b/tools/ui/src/app.d.ts @@ -143,10 +143,8 @@ declare global { idxThemeStyle?: number; idxCodeBlock?: number; - // File System Access API - missing from older DOM lib versions. - // Used by ChatFormWorkingDirectory's native folder picker. Feature availability - // is gated at runtime via `typeof window.showDirectoryPicker === 'function'`. - showDirectoryPicker: (options?: { + // File System Access API - not in the DOM lib and unavailable in some browsers + showDirectoryPicker?: (options?: { id?: string; mode?: 'read' | 'readwrite'; startIn?: FileSystemHandle | string; diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatForm.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatForm.svelte index 105e414fe78..2d70c302cb6 100644 --- a/tools/ui/src/lib/components/app/chat/ChatForm/ChatForm.svelte +++ b/tools/ui/src/lib/components/app/chat/ChatForm/ChatForm.svelte @@ -2,6 +2,7 @@ import { ChatAttachmentsList, ChatFormActions, + ChatFormContenteditable, ChatFormFileInputInvisible, ChatFormMcpResourcesList, ChatFormPickers, @@ -14,9 +15,7 @@ INPUT_CLASSES, SETTING_CONFIG_DEFAULT, INITIAL_FILE_SIZE, - PROMPT_CONTENT_SEPARATOR, - PROMPT_TRIGGER_PREFIX, - RESOURCE_TRIGGER_PREFIX + PROMPT_CONTENT_SEPARATOR } from '$lib/constants'; import { ContentPartType, @@ -39,8 +38,25 @@ activeConversation, pendingCwd } from '$lib/stores/conversations.svelte'; - import type { GetPromptResult, MCPPromptInfo, MCPResourceInfo, PromptMessage } from '$lib/types'; - import { isIMEComposing, parseClipboardContent, uuid } from '$lib/utils'; + import type { + FileMentionEntry, + GetPromptResult, + MCPPromptInfo, + MCPResourceInfo, + PromptMessage + } from '$lib/types'; + import { + buildMentionInsertion, + containsCodeSpan, + containsFileMentionLink, + findCommandToken, + findMentionToken, + isIMEComposing, + isOffsetInCodeBlock, + parseClipboardContent, + uuid + } from '$lib/utils'; + import { useChatFormPickers } from '$lib/hooks/use-chat-form-pickers.svelte'; import { AudioRecorder, convertToWav, @@ -97,29 +113,67 @@ }: Props = $props(); // Component References + // Shared handle of the two input renderers (textarea + contenteditable). + type ChatInputHandle = { + focus(): void; + resetHeight(): void; + getElement(): HTMLElement | undefined; + getCaretOffset(): number; + setCaretOffset(offset: number): void; + }; + let audioRecorder: AudioRecorder | undefined; let chatFormActionsRef: ChatFormActions | undefined = $state(undefined); let fileInputRef: ChatFormFileInputInvisible | undefined = $state(undefined); let pickersRef: { handleKeydown: (event: KeyboardEvent) => boolean } | undefined = $state(undefined); - let textareaRef: ChatFormTextarea | undefined = $state(undefined); + let inputRef: ChatInputHandle | undefined = $state(undefined); + + // Render-mode gate: the plain textarea by default, the contenteditable + // while the buffer carries a `file://` mention link or a complete code + // span (badges and code chips need a DOM the textarea cannot provide). + // Demotes back once neither remains. + let useContenteditable = $state(false); // Audio Recording State let isRecording = $state(false); let recordingSupported = $state(false); - // Picker State - let isPromptPickerOpen = $state(false); - let promptSearchQuery = $state(''); - let isInlineResourcePickerOpen = $state(false); - let resourceSearchQuery = $state(''); + // Invisible anchor at the form's top edge so the mention/WD popovers + // float above the box. + let mentionAnchor: HTMLDivElement | null = $state(null); let cwd = $derived(activeConversation()?.cwd ?? pendingCwd()); - async function handleWorkingDirectoryChange(value: string | null) { - await conversationsStore.setCwd(value); + const pickers = useChatFormPickers({ + getValue: () => value, + setValue: (v) => { + value = v; + onValueChange?.(v); + }, + getCaretOffset: () => inputRef?.getCaretOffset(), + setCaretOffset: (offset) => inputRef?.setCaretOffset(offset), + focusInput: refocusInput, + getShowModelSelector: () => showModelSelector, + hasPrompts: () => mcpStore.hasPromptsCapability(conversationsStore.getAllMcpServerOverrides()), + hasCwdTools: () => toolsStore.hasEnabledCwdTools, + getCwd: () => cwd, + getServerHome: () => toolsStore.serverHome ?? null, + openModelSelector: () => chatFormActionsRef?.openModelSelector(), + getPickersRef: () => pickersRef + }); + + async function handleWorkingDirectoryChange(newDir: string | null) { + // Committing a directory consumes the `/cwd` token; the chip's + // clear-X path has no token to consume. + const token = findCommandToken(value); + if (token && token.name === 'cwd') { + value = ''; + onValueChange?.(''); + } + await conversationsStore.setCwd(newDir); if (conversationsStore.activeConversation) { - await chatStore.recordCwdChange(value?.trim() || null); + await chatStore.recordCwdChange(newDir?.trim() || null); } } @@ -166,23 +220,45 @@ ); let canSubmit = $derived(value.trim().length > 0 || hasAttachments); + // Caret offset restored after a renderer swap. Callers that mutate + // `value` themselves (e.g. the mention picker) pin the target offset + // BEFORE the assignment; otherwise the swap effect snapshots the + // current caret. + let pendingCaretOffset = 0; + let caretOffsetPinned = false; + + function queueCaretRestore() { + queueMicrotask(() => { + inputRef?.focus(); + inputRef?.setCaretOffset(pendingCaretOffset); + caretOffsetPinned = false; + }); + } + + $effect(() => { + const wantContenteditable = + containsFileMentionLink(value ?? '') || containsCodeSpan(value ?? ''); + if (useContenteditable === wantContenteditable) return; + + if (!caretOffsetPinned) { + pendingCaretOffset = inputRef?.getCaretOffset() ?? (value ?? '').length; + } + + useContenteditable = wantContenteditable; + queueCaretRestore(); + }); + onMount(() => { recordingSupported = isAudioRecordingSupported(); audioRecorder = new AudioRecorder(); }); - // Defer so the closing popover's focus scope tears down first - bits-ui - // yanks a synchronous focus() back into the still-mounted popover. - function refocusInput() { - queueMicrotask(() => textareaRef?.focus()); - } - export function focus() { - textareaRef?.focus(); + inputRef?.focus(); } export function resetTextareaHeight() { - textareaRef?.resetHeight(); + inputRef?.resetHeight(); } export function openModelSelector() { @@ -216,46 +292,10 @@ } } - function handleInput() { - const perChatOverrides = conversationsStore.getAllMcpServerOverrides(); - const hasServers = mcpStore.hasEnabledServers(perChatOverrides); - - if (value.startsWith(PROMPT_TRIGGER_PREFIX) && hasServers) { - isPromptPickerOpen = true; - promptSearchQuery = value.slice(1); - isInlineResourcePickerOpen = false; - resourceSearchQuery = ''; - } else if ( - value.startsWith(RESOURCE_TRIGGER_PREFIX) && - hasServers && - mcpStore.hasResourcesCapability(perChatOverrides) - ) { - isInlineResourcePickerOpen = true; - resourceSearchQuery = value.slice(1); - isPromptPickerOpen = false; - promptSearchQuery = ''; - } else { - isPromptPickerOpen = false; - promptSearchQuery = ''; - isInlineResourcePickerOpen = false; - resourceSearchQuery = ''; - } - } - function handleKeydown(event: KeyboardEvent) { - if (pickersRef?.handleKeydown(event)) { - return; - } - - if (event.key === KeyboardKey.ESCAPE && isPromptPickerOpen) { - isPromptPickerOpen = false; - promptSearchQuery = ''; - return; - } - - if (event.key === KeyboardKey.ESCAPE && isInlineResourcePickerOpen) { - isInlineResourcePickerOpen = false; - resourceSearchQuery = ''; + // Pickers consume navigation/escape keys first; when consumed, skip + // the enter-to-submit logic below. + if (pickers.handleKeydown(event)) { return; } @@ -263,6 +303,15 @@ const isModifier = event.ctrlKey || event.metaKey; const sendOnEnter = currentConfig.sendOnEnter !== false; + // Caret inside a fenced code block (closed, or still open + // while being typed): Enter adds a line, never submits. The + // contenteditable consumes this case locally; this gate + // covers the plain textarea, where skipping submit lets the + // native newline through. + if (!isModifier && isOffsetInCodeBlock(value ?? '', inputRef?.getCaretOffset() ?? 0)) { + return; + } + if (sendOnEnter || isModifier) { event.preventDefault(); @@ -332,7 +381,7 @@ } setTimeout(() => { - textareaRef?.focus(); + inputRef?.focus(); }, 10); return; @@ -359,13 +408,7 @@ promptInfo: MCPPromptInfo, args?: Record ) { - // Only clear the value if the prompt was triggered by typing '/' - if (value.startsWith(PROMPT_TRIGGER_PREFIX)) { - value = ''; - onValueChange?.(''); - } - isPromptPickerOpen = false; - promptSearchQuery = ''; + pickers.closePromptPicker(); const promptName = promptInfo.title || promptInfo.name; const placeholder: ChatUploadedFile = { @@ -384,7 +427,7 @@ uploadedFiles = [...uploadedFiles, placeholder]; onUploadedFilesChange?.(uploadedFiles); - textareaRef?.focus(); + inputRef?.focus(); } function handlePromptLoadComplete(placeholderId: string, result: GetPromptResult) { @@ -426,39 +469,36 @@ onUploadedFilesChange?.(uploadedFiles); } - function handlePromptPickerClose() { - isPromptPickerOpen = false; - promptSearchQuery = ''; - textareaRef?.focus(); - } - - function handleInlineResourcePickerClose() { - isInlineResourcePickerOpen = false; - resourceSearchQuery = ''; - textareaRef?.focus(); - } - - function handleInlineResourceSelect() { - if (value.startsWith(RESOURCE_TRIGGER_PREFIX)) { - value = ''; - onValueChange?.(''); - } - - isInlineResourcePickerOpen = false; - resourceSearchQuery = ''; - textareaRef?.focus(); + // Deferred so the closing popover's focus scope tears down first - + // bits-ui yanks a synchronous focus() back into the still-mounted popover. + function refocusInput() { + queueMicrotask(() => inputRef?.focus()); } - function handleBrowseResources() { - isInlineResourcePickerOpen = false; - resourceSearchQuery = ''; - - if (value.startsWith(RESOURCE_TRIGGER_PREFIX)) { - value = ''; - onValueChange?.(''); + // Splice the mention link in place of the `@` token. Uses the + // live cursor, not a stale snapshot - the token may have been edited. + function handleMentionSelect(entry: FileMentionEntry) { + const cursor = inputRef?.getCaretOffset() ?? value.length; + const token = findMentionToken(value, cursor); + if (!token) return; + + const built = buildMentionInsertion(entry, value, token); + if (!built) return; + + // Pin the post-insertion caret BEFORE the swap effect runs; + // otherwise the effect clobbers it with the textarea's selection + // at promotion time (browser-dependent: usually reset to 0). + pendingCaretOffset = built.caretOffset; + caretOffsetPinned = true; + + value = built.newValue; + onValueChange?.(built.newValue); + + // Already in contenteditable mode: no renderer flip, so the swap + // effect's caret restore never runs. + if (useContenteditable) { + queueCaretRestore(); } - - isResourceDialogOpen = true; } async function handleMicClick() { @@ -503,19 +543,32 @@ > inputRef?.focus()} + onMentionSelect={handleMentionSelect} onPromptLoadStart={handlePromptLoadStart} onPromptLoadComplete={handlePromptLoadComplete} onPromptLoadError={handlePromptLoadError} - onInlineResourceBrowse={handleBrowseResources} /> + +
- { - handleInput(); - onValueChange?.(value); - }} - {disabled} - {placeholder} - /> + {#if useContenteditable} + { + pickers.handleInput(); + onValueChange?.(value); + }} + onPaste={handlePaste} + {disabled} + {placeholder} + /> + {:else} + { + pickers.handleInput(); + onValueChange?.(value); + }} + onPaste={handlePaste} + {disabled} + {placeholder} + /> + {/if} {#if mcpHasResourceAttachments()} onSystemPromptClick?.({ message: value, files: uploadedFiles })} - onMcpPromptClick={showMcpPromptButton ? () => (isPromptPickerOpen = true) : undefined} + onMcpPromptClick={showMcpPromptButton ? () => pickers.openPromptPicker() : undefined} onMcpResourcesClick={() => (isResourceDialogOpen = true)} />
@@ -582,11 +651,15 @@ - {#if toolsStore.builtinTools.length > 0} + {#if toolsStore.hasEnabledCwdTools} {/if} diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormContenteditable.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormContenteditable.svelte new file mode 100644 index 00000000000..18fd24302e3 --- /dev/null +++ b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormContenteditable.svelte @@ -0,0 +1,788 @@ + + +
+
+
+ + diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormCommandPicker.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormCommandPicker.svelte new file mode 100644 index 00000000000..5feaaf35aa1 --- /dev/null +++ b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormCommandPicker.svelte @@ -0,0 +1,135 @@ + + + + command.name} + scrollTrigger={nav.scrollTrigger} + > + {#snippet item(command, index, isSelected)} + {@const Icon = commandIcon[command.action]} + handleSelect(command)} + onmouseenter={() => { + if (!command.disabled) nav.setHover(index); + }} + > + +
+ /{command.name} + + {command.description} + +
+ + {/snippet} + + diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormMentionPicker.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormMentionPicker.svelte new file mode 100644 index 00000000000..07cbaf492ce --- /dev/null +++ b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormMentionPicker.svelte @@ -0,0 +1,269 @@ + + + { + if (!open) onClose(); + }} +> + + + + event.preventDefault()} + onCloseAutoFocus={(event) => event.preventDefault()} + class={[ + 'w-[var(--bits-popover-anchor-width)] max-w-none rounded-xl border-border/50 p-0 shadow-xl', + className + ]} + > + entry.type + ':' + entry.path} + scrollTrigger={nav.scrollTrigger} + > + {#snippet item(entry, index, isSelected)} + handleSelect(entry)} + onmouseenter={() => nav.setHover(index)} + > + {@const Icon = entry.type === FileMentionEntryType.DIRECTORY ? Folder : File} + +
+
+ {#if showTooltip} + + + {#snippet child({ props })} + {entry.name} + {/snippet} + + +

{entry.path}

+ + + {:else} + {entry.name} + {/if} + + {entry.type} + +
+ + + +
+ + {/snippet} + + + diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPicker/ChatFormPickerList.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPicker/ChatFormPickerList.svelte index 6647928b2bf..04b85b24b23 100644 --- a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPicker/ChatFormPickerList.svelte +++ b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPicker/ChatFormPickerList.svelte @@ -2,6 +2,7 @@ import type { Snippet } from 'svelte'; import { SearchInput } from '$lib/components/app'; import ScrollArea from '$lib/components/ui/scroll-area/scroll-area.svelte'; + import { useScrollActiveRow } from '$lib/hooks/use-scroll-active-row.svelte'; import { CHAT_FORM_POPOVER_MAX_HEIGHT } from '$lib/constants'; interface Props { @@ -11,11 +12,19 @@ searchQuery: string; showSearchInput: boolean; searchPlaceholder?: string; + // Omit to distinguish "haven't searched yet" from "search returned nothing". emptyMessage?: string; + autofocus?: boolean; + inputRef?: HTMLInputElement | null; + onSearchClose?: () => void; itemKey: (item: T, index: number) => string; item: Snippet<[T, number, boolean]>; skeleton?: Snippet; + skeletonCount?: number; footer?: Snippet; + // Counter bumped by the picker on keyboard nav; scrolls the selected + // row into view without scrolling on hover or result replacement. + scrollTrigger?: number; } let { @@ -25,49 +34,69 @@ searchQuery = $bindable(), showSearchInput, searchPlaceholder = 'Search...', - emptyMessage = 'No items available', + emptyMessage, + autofocus = false, + inputRef = $bindable(null), + onSearchClose, itemKey, item, skeleton, - footer + skeletonCount = 6, + footer, + scrollTrigger }: Props = $props(); let listContainer = $state(null); - $effect(() => { - if (listContainer && selectedIndex >= 0 && selectedIndex < items.length) { - const selectedElement = listContainer.querySelector( - `[data-picker-index="${selectedIndex}"]` - ) as HTMLElement; + let listPaddingTop = $derived( + showSearchInput ? (isLoading || items.length > 0 ? 'pt-13' : 'pt-10') : '' + ); - if (selectedElement) { - selectedElement.scrollIntoView({ - behavior: 'smooth', - block: 'center', - inline: 'nearest' - }); - } - } + // selectedIndex/items.length are untracked so hover and result replacement + // never re-fire the scroll; keyboard nav is the only path that bumps the trigger. + useScrollActiveRow({ + getTrigger: () => scrollTrigger, + getContainer: () => listContainer, + getIndex: () => selectedIndex, + getCount: () => items.length, + dataIndex: 'picker' }); {#if showSearchInput}
- +
{/if} -
+
{#if isLoading} {#if skeleton} {@render skeleton()} + {:else} +
+ {#each { length: skeletonCount } as _, rowIndex (rowIndex)} +
+
+
+
+
+
+
+ {/each} +
+ {/if} + {:else if items && items.length === 0} + {#if emptyMessage} +
{emptyMessage}
{/if} - {:else if items.length === 0} -
{emptyMessage}
{:else} {#each items as itemData, index (itemKey(itemData, index))} {@render item(itemData, index, index === selectedIndex)} diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPicker/ChatFormPickerListItem.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPicker/ChatFormPickerListItem.svelte index 4d82c6b5849..0fb0ea0c008 100644 --- a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPicker/ChatFormPickerListItem.svelte +++ b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPicker/ChatFormPickerListItem.svelte @@ -3,21 +3,34 @@ interface Props { isSelected?: boolean; + disabled?: boolean; onclick: () => void; + onmouseenter?: () => void; dataIndex?: number; children: Snippet; + class?: string; } - let { isSelected = false, onclick, dataIndex, children }: Props = $props(); + let { + class: className = '', + isSelected = false, + disabled = false, + onclick, + onmouseenter, + dataIndex, + children + }: Props = $props(); diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPicker/ChatFormPickerPopover.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPicker/ChatFormPickerPopover.svelte index c43a002e695..24ea8619f57 100644 --- a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPicker/ChatFormPickerPopover.svelte +++ b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPicker/ChatFormPickerPopover.svelte @@ -42,6 +42,7 @@ align="start" sideOffset={12} class="w-[var(--bits-popover-anchor-width)] max-w-none rounded-xl border-border/50 p-0 shadow-xl {className}" + preventScroll={false} onkeydown={onKeydown} onOpenAutoFocus={(event) => event.preventDefault()} > diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPickerMcpPrompts/ChatFormPickerMcpPrompts.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPickerMcpPrompts/ChatFormPickerMcpPrompts.svelte index f35d816de92..22ec5311947 100644 --- a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPickerMcpPrompts/ChatFormPickerMcpPrompts.svelte +++ b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPickerMcpPrompts/ChatFormPickerMcpPrompts.svelte @@ -45,6 +45,9 @@ let promptArgs = $state>({}); let selectedIndex = $state(0); let internalSearchQuery = $state(''); + // Bumped on ArrowUp/ArrowDown only, so the list scrolls on keyboard + // nav but not on hover or result changes. + let scrollTrigger = $state(0); let promptError = $state(null); let selectedIndexBeforeArgumentForm = $state(null); @@ -295,6 +298,7 @@ event.preventDefault(); if (filteredPrompts.length > 0) { selectedIndex = (selectedIndex + 1) % filteredPrompts.length; + scrollTrigger++; } return true; @@ -304,6 +308,7 @@ event.preventDefault(); if (filteredPrompts.length > 0) { selectedIndex = selectedIndex === 0 ? filteredPrompts.length - 1 : selectedIndex - 1; + scrollTrigger++; } return true; @@ -400,6 +405,7 @@ searchPlaceholder="Search prompts..." emptyMessage="No MCP prompts available" itemKey={(prompt) => prompt.serverName + ':' + prompt.name} + {scrollTrigger} > {#snippet item(prompt, index, isSelected)} {@const server = serverSettingsMap.get(prompt.serverName)} diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPickerMcpResources.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPickerMcpResources.svelte deleted file mode 100644 index ed97e1fc7e5..00000000000 --- a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPickerMcpResources.svelte +++ /dev/null @@ -1,237 +0,0 @@ - - - - resource.serverName + ':' + resource.uri} - > - {#snippet item(resource, index, isSelected)} - {@const server = serverSettingsMap.get(resource.serverName)} - {@const serverLabel = server ? mcpStore.getServerLabel(server) : resource.serverName} - - handleResourceClick(resource)} - > - - {#snippet titleExtra()} - {#if isResourceAttached(resource.uri)} - - attached - - {/if} - {/snippet} - - {#snippet subtitle()} -

- {resource.uri} -

- {/snippet} - - - {/snippet} - - {#snippet skeleton()} - - {/snippet} - - {#snippet footer()} - {#if onBrowse && resources.length > 3} - - {/if} - {/snippet} - - diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPickers.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPickers.svelte index 7c5dc85b2a0..0d6cdcbfd68 100644 --- a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPickers.svelte +++ b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormPickers/ChatFormPickers.svelte @@ -1,16 +1,30 @@ + {})} + onSelect={onCommandSelect ?? (() => {})} +/> + - {})} + onOpened={onMentionOpened} + onSelect={onMentionSelect ?? (() => {})} /> diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormTextarea.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormTextarea.svelte index 3e683389f18..8ef56d7ee79 100644 --- a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormTextarea.svelte +++ b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormTextarea.svelte @@ -28,11 +28,10 @@ onMount(() => { if (textareaElement) { autoResizeTextarea(textareaElement); - textareaElement.focus(); + textareaElement.focus({ preventScroll: true }); } }); - // Expose the textarea element for external access export function getElement() { return textareaElement; } @@ -48,6 +47,17 @@ textareaElement.style.height = '1rem'; } } + + // Plain-text caret offsets, shared with the contenteditable variant so + // the picker/paste flows can address either renderer through one handle. + export function getCaretOffset(): number { + if (!textareaElement) return 0; + return textareaElement.selectionStart ?? textareaElement.value.length; + } + + export function setCaretOffset(offset: number) { + textareaElement?.setSelectionRange(offset, offset); + }
diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormWorkingDirectory.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormWorkingDirectory.svelte index f6ac9e0e863..f8069c93e5f 100644 --- a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormWorkingDirectory.svelte +++ b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormWorkingDirectory.svelte @@ -1,7 +1,5 @@ -
- - - + + + + + + event.preventDefault()} + onCloseAutoFocus={(event) => event.preventDefault()} + class="w-[var(--bits-popover-anchor-width)] max-w-none rounded-xl border-border/50 p-0 shadow-xl" + > +
+ - - - event.preventDefault()} - > -
- - {#if inputValue.trim() && (isSearching || queryResults.length > 0 || searchError)} - (hoveredIndex = index)} - /> - {/if} - - {#if pickerSupported} - + {/if} + + {#if homeBase} + + + + Searching in: + + {abbreviateHome(searchScope, homeBase)} - - Browse - - {/if} - - {#if homeBase} - - - - Searching in: - - {abbreviateHome(searchScope, homeBase)} - - {/if} -
- - -
+ + {/if} +
+ + diff --git a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormWorkingDirectoryChip.svelte b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormWorkingDirectoryChip.svelte index 4f8d0f7f7d7..2882f557c84 100644 --- a/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormWorkingDirectoryChip.svelte +++ b/tools/ui/src/lib/components/app/chat/ChatForm/ChatFormWorkingDirectoryChip.svelte @@ -1,6 +1,7 @@ + +{#each segments as seg, i (i)} + {#if seg.match} + {seg.text} + {:else} + {seg.text} + {/if} +{/each} diff --git a/tools/ui/src/lib/components/app/forms/index.ts b/tools/ui/src/lib/components/app/forms/index.ts index 4cf56cdc9d0..87594d7e351 100644 --- a/tools/ui/src/lib/components/app/forms/index.ts +++ b/tools/ui/src/lib/components/app/forms/index.ts @@ -42,3 +42,11 @@ export { default as KeyValuePairs } from './KeyValuePairs.svelte'; * Supports placeholder, autofocus, and change callbacks. */ export { default as SearchInput } from './SearchInput.svelte'; + +/** + * **HighlightedMatch** - Substring-match text highlight + * + * Renders `text` with each case-insensitive occurrence of `query` wrapped + * in ``. + */ +export { default as HighlightedMatch } from './HighlightedMatch.svelte'; diff --git a/tools/ui/src/lib/components/app/models/ModelsSelectorDropdown.svelte b/tools/ui/src/lib/components/app/models/ModelsSelectorDropdown.svelte index 720963a8db9..415e5164d82 100644 --- a/tools/ui/src/lib/components/app/models/ModelsSelectorDropdown.svelte +++ b/tools/ui/src/lib/components/app/models/ModelsSelectorDropdown.svelte @@ -1,8 +1,9 @@ + + diff --git a/tools/ui/tests/client/components/ChatFormPickersHarness.svelte b/tools/ui/tests/client/components/ChatFormPickersHarness.svelte new file mode 100644 index 00000000000..8e5e56c20b0 --- /dev/null +++ b/tools/ui/tests/client/components/ChatFormPickersHarness.svelte @@ -0,0 +1,51 @@ + diff --git a/tools/ui/tests/client/components/ChatFormTestWrapper.svelte b/tools/ui/tests/client/components/ChatFormTestWrapper.svelte new file mode 100644 index 00000000000..78a431157c4 --- /dev/null +++ b/tools/ui/tests/client/components/ChatFormTestWrapper.svelte @@ -0,0 +1,12 @@ + + + + + diff --git a/tools/ui/tests/client/components/PickerListScrollHarness.svelte b/tools/ui/tests/client/components/PickerListScrollHarness.svelte new file mode 100644 index 00000000000..87746979f32 --- /dev/null +++ b/tools/ui/tests/client/components/PickerListScrollHarness.svelte @@ -0,0 +1,43 @@ + + +
conversation
+ +{#if open} +
+ it.id} + > + {#snippet item(it, index, isSelected)} + {}}> + {it.label} + + {/snippet} + +
+{/if} diff --git a/tools/ui/tests/client/picker-list-scroll.svelte.test.ts b/tools/ui/tests/client/picker-list-scroll.svelte.test.ts new file mode 100644 index 00000000000..1ce01998514 --- /dev/null +++ b/tools/ui/tests/client/picker-list-scroll.svelte.test.ts @@ -0,0 +1,29 @@ +// Regression test: opening a chat-form picker must not scroll the +// conversation to the top. Root cause: the list's scroll effect fired +// scrollIntoView on the initial mount, before the popover was positioned, +// so the browser scrolled every scrollable ancestor to reveal the row. + +import { describe, it, expect } from 'vitest'; +import { render } from 'vitest-browser-svelte'; +import { tick } from 'svelte'; +import PickerListScrollHarness from './components/PickerListScrollHarness.svelte'; + +describe('ChatFormPickerList mount scroll', () => { + it('does not scroll documentElement when the picker mounts', async () => { + const screen = render(PickerListScrollHarness); + await tick(); + + document.documentElement.scrollTop = document.documentElement.scrollHeight; + await tick(); + const before = document.documentElement.scrollTop; + expect(before).toBeGreaterThan(0); + + screen.component.openPicker(); + await tick(); + await new Promise((r) => setTimeout(r, 100)); + await tick(); + + const after = document.documentElement.scrollTop; + expect(after).toBe(before); + }); +}); diff --git a/tools/ui/tests/client/settings-raw-text-migration.svelte.test.ts b/tools/ui/tests/client/settings-raw-text-migration.svelte.test.ts new file mode 100644 index 00000000000..601ebc2b3f4 --- /dev/null +++ b/tools/ui/tests/client/settings-raw-text-migration.svelte.test.ts @@ -0,0 +1,65 @@ +// Guards the legacy render-key migration: `renderUserContentAsMarkdown` +// and `renderThinkingAsMarkdown` (opt-INTO markdown) fold into the single +// `renderContentAsRawText` setting, with any explicit raw-text preference +// winning when the legacy keys disagree. Legacy keys are removed from the +// persisted config so they do not stay orphaned in localStorage. + +import { beforeEach, describe, expect, it } from 'vitest'; +import { settingsStore, config } from '$lib/stores/settings.svelte'; +import { CONFIG_LOCALSTORAGE_KEY } from '$lib/constants/storage'; + +function seedConfig(stored: Record) { + localStorage.setItem(CONFIG_LOCALSTORAGE_KEY, JSON.stringify(stored)); + settingsStore.initialize(); +} + +function persisted(): Record { + return JSON.parse(localStorage.getItem(CONFIG_LOCALSTORAGE_KEY) ?? '{}'); +} + +describe('renderContentAsRawText migration', () => { + beforeEach(() => { + localStorage.removeItem(CONFIG_LOCALSTORAGE_KEY); + settingsStore.initialize(); + }); + + it('maps renderUserContentAsMarkdown=false to raw text', () => { + seedConfig({ renderUserContentAsMarkdown: false }); + expect(config().renderContentAsRawText).toBe(true); + }); + + it('maps renderUserContentAsMarkdown=true to markdown', () => { + seedConfig({ renderUserContentAsMarkdown: true }); + expect(config().renderContentAsRawText).toBe(false); + }); + + it('maps renderThinkingAsMarkdown=false to raw text', () => { + seedConfig({ renderThinkingAsMarkdown: false }); + expect(config().renderContentAsRawText).toBe(true); + }); + + it('lets any explicit raw-text preference win when the legacy keys disagree', () => { + seedConfig({ renderUserContentAsMarkdown: true, renderThinkingAsMarkdown: false }); + expect(config().renderContentAsRawText).toBe(true); + }); + + it('honors the intermediate renderUserContentAsRawText key from the PR branch', () => { + seedConfig({ renderUserContentAsRawText: true }); + expect(config().renderContentAsRawText).toBe(true); + }); + + it('keeps an already-migrated value and cleans up the legacy keys', () => { + seedConfig({ renderContentAsRawText: false, renderUserContentAsMarkdown: false }); + expect(config().renderContentAsRawText).toBe(false); + + const stored = persisted(); + expect(stored.renderUserContentAsMarkdown).toBeUndefined(); + expect(stored.renderThinkingAsMarkdown).toBeUndefined(); + expect(stored.renderUserContentAsRawText).toBeUndefined(); + }); + + it('defaults to markdown when no legacy key exists', () => { + seedConfig({}); + expect(config().renderContentAsRawText).toBe(false); + }); +}); diff --git a/tools/ui/tests/unit/code.test.ts b/tools/ui/tests/unit/code.test.ts index 7820c980725..99fad60446d 100644 --- a/tools/ui/tests/unit/code.test.ts +++ b/tools/ui/tests/unit/code.test.ts @@ -1,5 +1,5 @@ import { describe, expect, it } from 'vitest'; -import { highlightCode, trimCodePadding } from '$lib/utils/code'; +import { highlightCode, splitGluedClosingCodeFences, trimCodePadding } from '$lib/utils/code'; describe('trimCodePadding', () => { it('removes a single leading newline', () => { @@ -101,3 +101,38 @@ describe('highlightCode', () => { expect(html).toBe('<script>a && b</script>'); }); }); + +describe('splitGluedClosingCodeFences', () => { + it('splits text glued to a closing fence onto its own line', () => { + const input = "```ts\nlet foo = 'bar';\n```create this file on [Desktop](file:///a/b/)"; + expect(splitGluedClosingCodeFences(input)).toBe( + "```ts\nlet foo = 'bar';\n```\ncreate this file on [Desktop](file:///a/b/)" + ); + }); + + it('leaves a well-formed code block untouched', () => { + const input = "```ts\nlet foo = 'bar';\n```\ncreate this file on [Desktop](file:///a/b/)"; + expect(splitGluedClosingCodeFences(input)).toBe(input); + }); + + it('leaves content without fences untouched', () => { + expect(splitGluedClosingCodeFences('hello world')).toBe('hello world'); + }); + + it('keeps nested markdown fences inside a block intact', () => { + const input = '```md\n# Example\n```python\nprint(1)\n```\n```'; + expect(splitGluedClosingCodeFences(input)).toBe(input); + }); + + it('splits every glued closing fence when several blocks are present', () => { + const input = '```ts\na\n```first words\n\n```js\nb\n```second words'; + expect(splitGluedClosingCodeFences(input)).toBe( + '```ts\na\n```\nfirst words\n\n```js\nb\n```\nsecond words' + ); + }); + + it('leaves a still-open fence untouched', () => { + const input = '```ts\nlet foo = 1;'; + expect(splitGluedClosingCodeFences(input)).toBe(input); + }); +}); diff --git a/tools/ui/tests/unit/command-token.test.ts b/tools/ui/tests/unit/command-token.test.ts new file mode 100644 index 00000000000..f52097de5d0 --- /dev/null +++ b/tools/ui/tests/unit/command-token.test.ts @@ -0,0 +1,51 @@ +import { describe, expect, it } from 'vitest'; +import { findCommandToken, takeCommandDismissSnapshot } from '$lib/utils'; + +describe('findCommandToken', () => { + it('returns null when the value does not start with a slash', () => { + expect(findCommandToken('hello /prompt')).toBeNull(); + expect(findCommandToken('')).toBeNull(); + expect(findCommandToken('prompt')).toBeNull(); + }); + + it('parses a bare slash', () => { + expect(findCommandToken('/')).toEqual({ name: '', args: '', end: 1 }); + }); + + it('parses a command name with no args', () => { + expect(findCommandToken('/prompt')).toEqual({ name: 'prompt', args: '', end: 7 }); + }); + + it('parses a command name followed by a space', () => { + expect(findCommandToken('/prompt ')).toEqual({ name: 'prompt', args: '', end: 8 }); + }); + + it('parses args after the command name', () => { + expect(findCommandToken('/prompt rev')).toEqual({ name: 'prompt', args: 'rev', end: 11 }); + }); + + it('parses multi-word args', () => { + expect(findCommandToken('/prompt review code ')).toEqual({ + name: 'prompt', + args: ' review code ', + end: 22 + }); + }); + + it('treats the whole run as the name when there is no space', () => { + expect(findCommandToken('/promptx')).toEqual({ name: 'promptx', args: '', end: 8 }); + }); +}); + +describe('takeCommandDismissSnapshot', () => { + it('returns null when there is no command token', () => { + expect(takeCommandDismissSnapshot('hello')).toBeNull(); + }); + + it('captures the name and args', () => { + expect(takeCommandDismissSnapshot('/prompt rev')).toEqual({ + name: 'prompt', + args: 'rev' + }); + }); +}); diff --git a/tools/ui/tests/unit/contenteditable-tokenizer.test.ts b/tools/ui/tests/unit/contenteditable-tokenizer.test.ts new file mode 100644 index 00000000000..8752415f024 --- /dev/null +++ b/tools/ui/tests/unit/contenteditable-tokenizer.test.ts @@ -0,0 +1,205 @@ +import { describe, expect, it } from 'vitest'; +import { containsCodeSpan, isOffsetInCodeBlock, tokenizeContent } from '$lib/utils'; + +describe('tokenizeContent', () => { + it('tokenizes a plain text buffer with no badges', () => { + expect(tokenizeContent('hello world')).toEqual([{ kind: 'text', text: 'hello world' }]); + }); + + it('tokenizes a single badge', () => { + expect(tokenizeContent('[docs](file:///a/b)')).toEqual([ + { kind: 'badge', name: 'docs', path: '/a/b' } + ]); + }); + + it('tokenizes text around a single badge', () => { + expect(tokenizeContent('hello [docs](file:///a/b) world')).toEqual([ + { kind: 'text', text: 'hello ' }, + { kind: 'badge', name: 'docs', path: '/a/b' }, + { kind: 'text', text: ' world' } + ]); + }); + + it('tokenizes adjacent badges as separate tokens', () => { + expect(tokenizeContent('[a](file:///x)[b](file:///y)')).toEqual([ + { kind: 'badge', name: 'a', path: '/x' }, + { kind: 'badge', name: 'b', path: '/y' } + ]); + }); + + it('leaves non-file links untouched in the stream', () => { + expect(tokenizeContent('see [foo](https://example.com) for details')).toEqual([ + { kind: 'text', text: 'see [foo](https://example.com) for details' } + ]); + }); + + it('recognizes badges whose path contains spaces (macOS screenshots)', () => { + const path = '/Users/allozaur/Desktop/Screenshot 2026-07-28 at 17.21.50.png'; + const source = `[Screenshot 2026-07-28 at 17.21.50.png](file://${path}) `; + expect(tokenizeContent(source)).toEqual([ + { kind: 'badge', name: 'Screenshot 2026-07-28 at 17.21.50.png', path }, + { kind: 'text', text: ' ' } + ]); + }); + + it('recognizes badges whose path lives in the macOS temp folder', () => { + const path = + '/var/folders/78/j28m7pn57wb34bfjwlskh62h0000gn/T/TemporaryItems/NSIRD_screencaptureui_GD0A2R/Screenshot 2026-07-28 at 17.23.28.png'; + const source = `[Screenshot 2026-07-28 at 17.23.28.png](file://${path}) `; + expect(tokenizeContent(source)).toEqual([ + { kind: 'badge', name: 'Screenshot 2026-07-28 at 17.23.28.png', path }, + { kind: 'text', text: ' ' } + ]); + }); + + it('keeps text around a badge with spaces in the path', () => { + const path = '/Users/allozaur/Desktop/Screenshot 2026-07-28 at 17.21.50.png'; + const source = `see [Screenshot 2026-07-28 at 17.21.50.png](file://${path}) done`; + expect(tokenizeContent(source)).toEqual([ + { kind: 'text', text: 'see ' }, + { kind: 'badge', name: 'Screenshot 2026-07-28 at 17.21.50.png', path }, + { kind: 'text', text: ' done' } + ]); + }); + + it('recognizes badges whose path contains a close parenthesis (macOS duplicate files)', () => { + const path = '/Users/foo/Screenshot (1).png'; + const source = `[Screenshot (1).png](file://${path}) `; + expect(tokenizeContent(source)).toEqual([ + { kind: 'badge', name: 'Screenshot (1).png', path }, + { kind: 'text', text: ' ' } + ]); + }); + + it('recognizes badges whose folder name is wrapped in parentheses', () => { + const path = '/Users/foo/Project (Stuff)/main.rs'; + const source = `[main.rs](file://${path}) `; + expect(tokenizeContent(source)).toEqual([ + { kind: 'badge', name: 'main.rs', path }, + { kind: 'text', text: ' ' } + ]); + }); + + it('recognizes adjacent badges back-to-back with no separator', () => { + const source = '[a](file:///p)[b](file:///q)'; + expect(tokenizeContent(source)).toEqual([ + { kind: 'badge', name: 'a', path: '/p' }, + { kind: 'badge', name: 'b', path: '/q' } + ]); + }); + + it('tokenizes inline code with the backticks included', () => { + expect(tokenizeContent('run `npm test` now')).toEqual([ + { kind: 'text', text: 'run ' }, + { kind: 'inlineCode', text: '`npm test`' }, + { kind: 'text', text: ' now' } + ]); + }); + + it('tokenizes a fenced code block without a language', () => { + const source = 'before\n```\nconst a = 1;\n```\nafter'; + expect(tokenizeContent(source)).toEqual([ + { kind: 'text', text: 'before\n' }, + { kind: 'codeBlock', text: '```\nconst a = 1;\n```' }, + { kind: 'text', text: '\nafter' } + ]); + }); + + it('tokenizes a fenced code block with a language', () => { + const source = '```js\nconst a = 1;\n```'; + expect(tokenizeContent(source)).toEqual([ + { kind: 'codeBlock', text: '```js\nconst a = 1;\n```' } + ]); + }); + + it('prefers the fenced block over inline spans at triple backticks', () => { + expect(tokenizeContent('```a``` ```b```')).toEqual([ + { kind: 'codeBlock', text: '```a```' }, + { kind: 'text', text: ' ' }, + { kind: 'codeBlock', text: '```b```' } + ]); + }); + + it('leaves an unclosed fence as plain text', () => { + expect(tokenizeContent('```js\nconst a = 1;')).toEqual([ + { kind: 'text', text: '```js\nconst a = 1;' } + ]); + }); + + it('leaves an unclosed inline backtick as plain text', () => { + expect(tokenizeContent('run `npm test')).toEqual([{ kind: 'text', text: 'run `npm test' }]); + }); + + it('does not recognize badges inside code spans', () => { + expect(tokenizeContent('`[a](file:///p)`')).toEqual([ + { kind: 'inlineCode', text: '`[a](file:///p)`' } + ]); + }); + + it('tokenizes badges and code spans side by side', () => { + expect(tokenizeContent('[a](file:///p) `x`')).toEqual([ + { kind: 'badge', name: 'a', path: '/p' }, + { kind: 'text', text: ' ' }, + { kind: 'inlineCode', text: '`x`' } + ]); + }); +}); + +describe('containsCodeSpan', () => { + it('detects inline code', () => { + expect(containsCodeSpan('run `npm test` now')).toBe(true); + }); + + it('detects a fenced block with a language', () => { + expect(containsCodeSpan('```js\nconst a = 1;\n```')).toBe(true); + }); + + it('detects a fenced block without a language', () => { + expect(containsCodeSpan('```\ncode\n```')).toBe(true); + }); + + it('ignores unclosed fences and lone backticks', () => { + expect(containsCodeSpan('```js\nconst a = 1;')).toBe(false); + expect(containsCodeSpan('run `npm test')).toBe(false); + expect(containsCodeSpan('``')).toBe(false); + }); + + it('ignores plain text and mention links', () => { + expect(containsCodeSpan('hello world')).toBe(false); + expect(containsCodeSpan('[a](file:///p)')).toBe(false); + }); +}); + +describe('isOffsetInCodeBlock', () => { + const BLOCK = '```js\nconst a = 1;\n```'; + + it('is false with no fences in the buffer', () => { + expect(isOffsetInCodeBlock('hello world', 5)).toBe(false); + expect(isOffsetInCodeBlock('run `npm test` now', 10)).toBe(false); + }); + + it('is true right after the opening fence, before any content', () => { + expect(isOffsetInCodeBlock('```', 3)).toBe(true); + expect(isOffsetInCodeBlock('```js', 5)).toBe(true); + }); + + it('is true inside a still-open block while it is being typed', () => { + const open = '```js\nconst a = 1;'; + expect(isOffsetInCodeBlock(open, open.length)).toBe(true); + }); + + it('is true inside a closed block and false outside it', () => { + expect(isOffsetInCodeBlock(BLOCK, 6)).toBe(true); + expect(isOffsetInCodeBlock(BLOCK, 0)).toBe(false); + expect(isOffsetInCodeBlock(BLOCK, BLOCK.length)).toBe(false); + expect(isOffsetInCodeBlock(BLOCK + '\nafter', BLOCK.length + 5)).toBe(false); + }); + + it('toggles per fence across multiple blocks', () => { + const two = BLOCK + '\ntext\n' + BLOCK; + const secondBlock = two.lastIndexOf(BLOCK); + expect(isOffsetInCodeBlock(two, secondBlock - 2)).toBe(false); + expect(isOffsetInCodeBlock(two, secondBlock + 6)).toBe(true); + expect(isOffsetInCodeBlock(two, two.length)).toBe(false); + }); +}); diff --git a/tools/ui/tests/unit/contenteditable-word-jump.test.ts b/tools/ui/tests/unit/contenteditable-word-jump.test.ts new file mode 100644 index 00000000000..8e68950d489 --- /dev/null +++ b/tools/ui/tests/unit/contenteditable-word-jump.test.ts @@ -0,0 +1,80 @@ +import { describe, expect, it } from 'vitest'; +import { badgeAwareWordJump, leadingBadgeEdgeOffset } from '$lib/utils'; + +// Layout of `hello [docs](file:///a/b) world foo`: +// "hello" 0-4, " " 5, badge 6-24 (length 19), " " 25, "world" 26-30, " " 31, "foo" 32-34 +const BADGE = '[docs](file:///a/b)'; +const SOURCE = `hello ${BADGE} world foo`; +const BADGE_START = 6; +const BADGE_END = 25; + +describe('badgeAwareWordJump', () => { + it('returns null when the buffer has no badge', () => { + expect(badgeAwareWordJump('hello world', 0, 'forward')).toBeNull(); + expect(badgeAwareWordJump('hello world', 11, 'backward')).toBeNull(); + }); + + it('jumps forward onto a badge landing at its end, not the next word', () => { + expect(badgeAwareWordJump(SOURCE, BADGE_START, 'forward')).toBe(BADGE_END); + }); + + it('jumps forward from the space before a badge landing at its end', () => { + expect(badgeAwareWordJump(SOURCE, BADGE_START - 1, 'forward')).toBe(BADGE_END); + }); + + it('jumps backward over a badge landing at its start', () => { + expect(badgeAwareWordJump(SOURCE, BADGE_END, 'backward')).toBe(BADGE_START); + }); + + it('jumps backward from the next word onto the badge start', () => { + // caret at the start of "world" + expect(badgeAwareWordJump(SOURCE, BADGE_END + 1, 'backward')).toBe(BADGE_START); + }); + + it('returns null for jumps that cross no badge', () => { + // forward over "hello" only + expect(badgeAwareWordJump(SOURCE, 0, 'forward')).toBeNull(); + // backward over "foo" only + expect(badgeAwareWordJump(SOURCE, SOURCE.length, 'backward')).toBeNull(); + // backward away from the badge (over "hello") + expect(badgeAwareWordJump(SOURCE, BADGE_START, 'backward')).toBeNull(); + }); + + it('treats a leading badge as one word in both directions', () => { + const source = `${BADGE} rest`; + expect(badgeAwareWordJump(source, 0, 'forward')).toBe(BADGE.length); + expect(badgeAwareWordJump(source, BADGE.length, 'backward')).toBe(0); + }); + + it('treats adjacent badges as separate words', () => { + // each badge is 14 chars: "[a](file:///x)" / "[b](file:///y)" + const source = '[a](file:///x)[b](file:///y)'; + expect(badgeAwareWordJump(source, 0, 'forward')).toBe(14); + expect(badgeAwareWordJump(source, 14, 'forward')).toBe(28); + expect(badgeAwareWordJump(source, 28, 'backward')).toBe(14); + expect(badgeAwareWordJump(source, 14, 'backward')).toBe(0); + }); + + it('jumps over a badge following punctuation', () => { + // "foo," 0-3, " " 4, badge 5-23 (end 24), " bar" 24-27 + const source = `foo, ${BADGE} bar`; + expect(badgeAwareWordJump(source, 0, 'forward')).toBeNull(); + expect(badgeAwareWordJump(source, 3, 'forward')).toBe(24); + }); +}); + +describe('leadingBadgeEdgeOffset', () => { + it('returns 0 when the caret sits exactly at a leading badge end', () => { + expect(leadingBadgeEdgeOffset(`${BADGE} rest`, BADGE.length)).toBe(0); + }); + + it('returns null when the caret is anywhere else', () => { + expect(leadingBadgeEdgeOffset(`${BADGE} rest`, 0)).toBeNull(); + expect(leadingBadgeEdgeOffset(`${BADGE} rest`, BADGE.length + 2)).toBeNull(); + }); + + it('returns null when the buffer does not start with a badge', () => { + expect(leadingBadgeEdgeOffset(SOURCE, BADGE_END)).toBeNull(); + expect(leadingBadgeEdgeOffset('', 0)).toBeNull(); + }); +}); diff --git a/tools/ui/tests/unit/glob-search-children.test.ts b/tools/ui/tests/unit/glob-search-children.test.ts new file mode 100644 index 00000000000..46b7caa4c6a --- /dev/null +++ b/tools/ui/tests/unit/glob-search-children.test.ts @@ -0,0 +1,119 @@ +import { beforeEach, describe, expect, it, vi } from 'vitest'; + +vi.mock('$lib/services/tools.service', () => ({ + ToolsService: { executeToolRaw: vi.fn() } +})); + +import { ToolsService } from '$lib/services/tools.service'; +import { GlobSearchType } from '$lib/enums'; +import { runGlobSearchWithChildren } from '$lib/utils'; + +const mockExecute = vi.mocked(ToolsService.executeToolRaw); + +// Distinct roots per test so the module-level search cache never serves a +// prior test's result under the same (type, path, glob, depth) key. +beforeEach(() => { + mockExecute.mockReset(); +}); + +describe('runGlobSearchWithChildren', () => { + it('returns ranked outer entries as absolute paths without descending', async () => { + mockExecute.mockResolvedValueOnce({ + base: '/Users/rootA', + entries: [ + { path: 'note.md', type: 'file' }, + { path: 'src', type: 'dir' } + ] + }); + const res = await runGlobSearchWithChildren( + 'note', + '/Users/rootA', + 3, + 50, + new AbortController().signal + ); + expect(res.error).toBeUndefined(); + expect(res.entries.map((e) => e.path)).toEqual(['/Users/rootA/note.md', '/Users/rootA/src']); + expect(res.exactDir).toBeUndefined(); + expect(mockExecute).toHaveBeenCalledTimes(1); + }); + + it('appends a matched directorys children when the query ends with a separator', async () => { + mockExecute + .mockResolvedValueOnce({ base: '/Users/rootB', entries: [{ path: 'src', type: 'dir' }] }) + .mockResolvedValueOnce({ + base: '/Users/rootB/src', + entries: [ + { path: 'a.txt', type: 'file' }, + { path: 'sub', type: 'dir' } + ] + }); + const res = await runGlobSearchWithChildren( + '/Users/rootB/src/', + '/Users/rootB', + 3, + 50, + new AbortController().signal, + { type: GlobSearchType.ALL, descendOnTrailingSeparator: true } + ); + expect(res.error).toBeUndefined(); + expect(res.exactDir).toBe('/Users/rootB/src'); + expect(res.entries.map((e) => e.path)).toEqual([ + '/Users/rootB/src', + '/Users/rootB/src/a.txt', + '/Users/rootB/src/sub' + ]); + expect(mockExecute).toHaveBeenCalledTimes(2); + }); + + it('does not descend without a trailing separator in mention mode', async () => { + mockExecute.mockResolvedValueOnce({ + base: '/Users/rootC', + entries: [{ path: 'src', type: 'dir' }] + }); + const res = await runGlobSearchWithChildren( + '/Users/rootC/src', + '/Users/rootC', + 3, + 50, + new AbortController().signal, + { type: GlobSearchType.ALL, descendOnTrailingSeparator: true } + ); + expect(res.exactDir).toBeUndefined(); + expect(mockExecute).toHaveBeenCalledTimes(1); + }); + + it('descends on an exact directory match in WD mode', async () => { + mockExecute + .mockResolvedValueOnce({ base: '/Users/rootD', entries: [{ path: 'src', type: 'dir' }] }) + .mockResolvedValueOnce({ + base: '/Users/rootD/src', + entries: [{ path: 'a.txt', type: 'file' }] + }); + const res = await runGlobSearchWithChildren( + '/Users/rootD/src', + '/Users/rootD', + 3, + 50, + new AbortController().signal, + { type: GlobSearchType.DIR } + ); + expect(res.exactDir).toBe('/Users/rootD/src'); + expect(res.entries.map((e) => e.path)).toEqual(['/Users/rootD/src', '/Users/rootD/src/a.txt']); + expect(mockExecute).toHaveBeenCalledTimes(2); + }); + + it('surfaces a server error without attempting a child walk', async () => { + mockExecute.mockResolvedValueOnce({ error: 'boom' }); + const res = await runGlobSearchWithChildren( + 'src', + '/Users/rootE', + 3, + 50, + new AbortController().signal + ); + expect(res.error).toBe('boom'); + expect(res.entries).toEqual([]); + expect(mockExecute).toHaveBeenCalledTimes(1); + }); +}); diff --git a/tools/ui/tests/unit/mention-badge.test.ts b/tools/ui/tests/unit/mention-badge.test.ts new file mode 100644 index 00000000000..f2c00418290 --- /dev/null +++ b/tools/ui/tests/unit/mention-badge.test.ts @@ -0,0 +1,174 @@ +import { describe, expect, it } from 'vitest'; +import { + MENTION_BADGE_FILE_ICON_PATHS, + MENTION_BADGE_FOLDER_ICON_PATHS, + buildMentionInsertion, + containsFileMentionLink, + decodeFileLinkPath, + encodeFileLinkPath, + fileMentionLinkRe, + getMentionBadgeIconPaths, + getMentionBadgeLabel +} from '$lib/utils'; +import { FileMentionEntryType } from '$lib/enums'; + +describe('encodeFileLinkPath', () => { + it('leaves a clean path unchanged', () => { + expect(encodeFileLinkPath('/Users/foo/bar.txt')).toBe('/Users/foo/bar.txt'); + }); + + it('encodes spaces per path segment', () => { + expect( + encodeFileLinkPath('/Users/allozaur/Desktop/Screenshot 2026-08-05 at 11.33.45.png') + ).toBe('/Users/allozaur/Desktop/Screenshot%202026-08-05%20at%2011.33.45.png'); + }); + + it('preserves the leading and trailing slash (directory marker)', () => { + expect(encodeFileLinkPath('/Users/foo/bar/')).toBe('/Users/foo/bar/'); + }); + + it('encodes parentheses in macOS screenshot names', () => { + expect(encodeFileLinkPath('/Users/foo/Pic (1).png')).toBe('/Users/foo/Pic%20(1).png'); + }); +}); + +describe('fileMentionLinkRe', () => { + it('matches a standard mention link', () => { + expect(fileMentionLinkRe().test('[docs](file:///a/b)')).toBe(true); + expect(containsFileMentionLink('[docs](file:///a/b)')).toBe(true); + }); + + it('does not match non-file links', () => { + expect(fileMentionLinkRe().test('[foo](https://example.com)')).toBe(false); + expect(fileMentionLinkRe().test('plain text')).toBe(false); + }); + + it('admits a close paren in a macOS-style file name', () => { + const match = fileMentionLinkRe().exec( + '[Screenshot (1).png](file:///Users/foo/Screenshot (1).png)' + ); + expect(match).not.toBeNull(); + expect(match?.[1]).toBe('Screenshot (1).png'); + expect(match?.[2]).toBe('/Users/foo/Screenshot (1).png'); + }); + + it('admits a parenthesized folder segment', () => { + expect( + fileMentionLinkRe().exec('[main.rs](file:///Users/foo/Project (Stuff)/main.rs)')?.[2] + ).toBe('/Users/foo/Project (Stuff)/main.rs'); + }); + + it('stops at the closing paren of an adjacent badge', () => { + expect(fileMentionLinkRe().exec('[a](file:///p)[b](file:///q)')?.[0]).toBe('[a](file:///p)'); + }); +}); + +describe('getMentionBadgeIconPaths', () => { + it('returns the folder glyphs for a trailing-separator path', () => { + expect(getMentionBadgeIconPaths('/Users/foo/bar/')).toBe(MENTION_BADGE_FOLDER_ICON_PATHS); + }); + + it('returns the file glyphs otherwise', () => { + expect(getMentionBadgeIconPaths('/Users/foo/bar.txt')).toBe(MENTION_BADGE_FILE_ICON_PATHS); + }); +}); + +describe('getMentionBadgeLabel', () => { + it('returns the name by default', () => { + expect(getMentionBadgeLabel('bar', '/Users/foo/bar/', false)).toBe('bar'); + }); + + it('renders the decoded full path without the trailing separator', () => { + expect(getMentionBadgeLabel('bar', '/Users/foo/bar/', true)).toBe('/Users/foo/bar'); + expect(getMentionBadgeLabel('shot', '/Users/foo/Screenshot%20(1).png', true)).toBe( + '/Users/foo/Screenshot (1).png' + ); + }); + + it('abbreviates a known home prefix to a tilde', () => { + expect(getMentionBadgeLabel('main.rs', '/home/user/src/main.rs', true, '/home/user')).toBe( + '~/src/main.rs' + ); + }); + + it('falls back to the name when the decoded path is empty', () => { + expect(getMentionBadgeLabel('root', '/', true)).toBe('root'); + }); +}); + +describe('decodeFileLinkPath', () => { + it('decodes encoded segments back to the original path', () => { + expect( + decodeFileLinkPath('/Users/allozaur/Desktop/Screenshot%202026-08-05%20at%2011.33.45.png') + ).toBe('/Users/allozaur/Desktop/Screenshot 2026-08-05 at 11.33.45.png'); + }); + + it('is the inverse of encodeFileLinkPath', () => { + for (const path of [ + '/a/b.txt', + '/Users/foo/Desktop/Screenshot 2026-08-05 at 11.33.45.png', + '/Users/foo/bar (1)/dir/', + '/sp ace/pa%th.txt' + ]) { + expect(decodeFileLinkPath(encodeFileLinkPath(path))).toBe(path); + } + }); + + it('falls back to the input on malformed percent sequences', () => { + expect(decodeFileLinkPath('/a/%zz.txt')).toBe('/a/%zz.txt'); + }); +}); + +describe('buildMentionInsertion', () => { + const file = (path: string, name: string) => ({ + path, + name, + type: FileMentionEntryType.FILE + }); + const dir = (path: string, name: string) => ({ + path, + name, + type: FileMentionEntryType.DIRECTORY + }); + + it('splices a root-anchored file link in place of the token', () => { + const value = 'hello @repo'; + const result = buildMentionInsertion(file('/Users/foo/myRepo', 'myRepo'), value, { + start: 6, + end: 11 + }); + expect(result).not.toBeNull(); + const { newValue, caretOffset } = result!; + expect(newValue).toBe('hello [myRepo](file:///Users/foo/myRepo) '); + expect(caretOffset).toBe(6 + '[myRepo](file:///Users/foo/myRepo) '.length); + }); + + it('keeps the trailing slash on the directory marker', () => { + const value = 'see @src'; + const { newValue } = buildMentionInsertion(dir('/Users/foo/myRepo/src/', 'src'), value, { + start: 4, + end: 8 + })!; + expect(newValue).toBe('see [src](file:///Users/foo/myRepo/src/) '); + }); + + it('escapes spaces and parens in the target', () => { + const value = '@pic'; + const { newValue } = buildMentionInsertion( + file('/Users/foo/Desktop/Pic (1).png', 'Pic (1).png'), + value, + { start: 0, end: 4 } + )!; + expect(newValue).toBe('[Pic (1).png](file:///Users/foo/Desktop/Pic%20(1).png) '); + }); + + it('re-adds the directory marker when the cleaned path empties', () => { + const { newValue } = buildMentionInsertion(dir('/', 'root'), '/', { start: 0, end: 1 })!; + expect(newValue).toBe('[root](file:///) '); + }); + + it('returns null for an out-of-range token', () => { + expect(buildMentionInsertion(file('/a/b.txt', 'b.txt'), 'x', { start: 0, end: 5 })).toBeNull(); + expect(buildMentionInsertion(file('/a/b.txt', 'b.txt'), 'x', { start: 2, end: 1 })).toBeNull(); + }); +}); diff --git a/tools/ui/tests/unit/mention-token.test.ts b/tools/ui/tests/unit/mention-token.test.ts new file mode 100644 index 00000000000..fd21a94db1f --- /dev/null +++ b/tools/ui/tests/unit/mention-token.test.ts @@ -0,0 +1,64 @@ +import { describe, expect, it } from 'vitest'; +import { findMentionToken, takeMentionDismissSnapshot } from '$lib/utils'; + +describe('findMentionToken', () => { + it('returns null for an empty/bare cursor', () => { + expect(findMentionToken('', 0)).toBeNull(); + expect(findMentionToken('text', 0)).toBeNull(); + }); + + it('recognizes a mention at the start of the value', () => { + expect(findMentionToken('@pr', 3)).toEqual({ start: 0, end: 3, query: 'pr' }); + }); + + it('recognizes a mention after a word boundary', () => { + expect(findMentionToken('hello @pr', 9)).toEqual({ start: 6, end: 9, query: 'pr' }); + }); + + it('returns null when the @ is mid-identifier', () => { + expect(findMentionToken('em@', 3)).toBeNull(); + expect(findMentionToken('text@pr', 7)).toBeNull(); + }); + + it('returns null when the cursor is past the whitespace break', () => { + expect(findMentionToken('@pr hello', 9)).toBeNull(); + }); + + it('treats boundary characters (parens, brackets, comma) as token starts', () => { + expect(findMentionToken('(@pr', 4)).toEqual({ start: 1, end: 4, query: 'pr' }); + expect(findMentionToken('[@pr', 4)).toEqual({ start: 1, end: 4, query: 'pr' }); + expect(findMentionToken('a,@pr', 5)).toEqual({ start: 2, end: 5, query: 'pr' }); + }); + + it('does not treat an identifier character as a boundary', () => { + expect(findMentionToken('user@abc', 8)).toBeNull(); + }); + + it('extracts the whole token up to the trailing boundary as the query', () => { + expect(findMentionToken('@', 1)).toEqual({ start: 0, end: 1, query: '' }); + expect(findMentionToken('@hello', 6)).toEqual({ start: 0, end: 6, query: 'hello' }); + }); + + it('keeps the whole token as the query when the caret is mid-token', () => { + expect(findMentionToken('@hello', 4)).toEqual({ start: 0, end: 6, query: 'hello' }); + expect(findMentionToken('@hello world', 4)).toEqual({ start: 0, end: 6, query: 'hello' }); + }); + + it('ignores a boundary @ and keeps the most recent token', () => { + expect(findMentionToken('a @foo @bar', 11)).toEqual({ start: 7, end: 11, query: 'bar' }); + }); +}); + +describe('takeMentionDismissSnapshot', () => { + it('returns null when there is no valid mention at the cursor', () => { + expect(takeMentionDismissSnapshot('plain text', 5)).toBeNull(); + expect(takeMentionDismissSnapshot('user@abc', 8)).toBeNull(); + }); + + it('captures start and query of the current mention', () => { + expect(takeMentionDismissSnapshot('hello @proj', 11)).toEqual({ + start: 6, + query: 'proj' + }); + }); +}); diff --git a/tools/ui/tests/unit/source-history.test.ts b/tools/ui/tests/unit/source-history.test.ts new file mode 100644 index 00000000000..b83030941b4 --- /dev/null +++ b/tools/ui/tests/unit/source-history.test.ts @@ -0,0 +1,65 @@ +import { describe, expect, it } from 'vitest'; +import { SourceHistory } from '$lib/utils'; + +describe('SourceHistory', () => { + it('coalesces pushes inside the group window into one undo step', () => { + const h = new SourceHistory(100, 800); + h.push({ value: '', caret: 0 }, 1000); + h.push({ value: 'a', caret: 1 }, 1200); + h.push({ value: 'ab', caret: 2 }, 1500); + + expect(h.undo({ value: 'abc', caret: 3 })).toEqual({ value: '', caret: 0 }); + expect(h.undo({ value: '', caret: 0 })).toBeNull(); + }); + + it('starts a new group once the window has passed', () => { + const h = new SourceHistory(100, 800); + h.push({ value: '', caret: 0 }, 1000); + h.push({ value: 'abc', caret: 3 }, 2000); + + expect(h.undo({ value: 'abcdef', caret: 6 })).toEqual({ value: 'abc', caret: 3 }); + expect(h.undo({ value: 'abc', caret: 3 })).toEqual({ value: '', caret: 0 }); + }); + + it('newGroup forces a separate entry even inside the window', () => { + const h = new SourceHistory(100, 800); + h.push({ value: '', caret: 0 }, 1000); + h.push({ value: 'abc', caret: 3 }, 1100, true); + + expect(h.undo({ value: 'abc\n', caret: 4 })).toEqual({ value: 'abc', caret: 3 }); + expect(h.undo({ value: 'abc', caret: 3 })).toEqual({ value: '', caret: 0 }); + }); + + it('redo round-trips and a fresh push clears the redo stack', () => { + const h = new SourceHistory(100, 800); + h.push({ value: '', caret: 0 }, 1000); + + const undone = h.undo({ value: 'abc', caret: 3 }); + expect(undone).toEqual({ value: '', caret: 0 }); + expect(h.redo({ value: '', caret: 0 })).toEqual({ value: 'abc', caret: 3 }); + + h.undo({ value: 'abc', caret: 3 }); + h.push({ value: '', caret: 0 }, 5000); + expect(h.redo({ value: 'x', caret: 1 })).toBeNull(); + }); + + it('starts a new group on the first edit after an undo', () => { + const h = new SourceHistory(100, 800); + h.push({ value: '', caret: 0 }, 1000); + h.undo({ value: 'abc', caret: 3 }); + + h.push({ value: '', caret: 0 }, 1200); + expect(h.undo({ value: 'x', caret: 1 })).toEqual({ value: '', caret: 0 }); + }); + + it('evicts the oldest entry past the limit', () => { + const h = new SourceHistory(2, 800); + h.push({ value: 'one', caret: 0 }, 1000); + h.push({ value: 'two', caret: 0 }, 2000); + h.push({ value: 'three', caret: 0 }, 3000); + + expect(h.undo({ value: 'cur', caret: 0 })).toEqual({ value: 'three', caret: 0 }); + expect(h.undo({ value: 'three', caret: 0 })).toEqual({ value: 'two', caret: 0 }); + expect(h.undo({ value: 'two', caret: 0 })).toBeNull(); + }); +}); diff --git a/tools/ui/tests/unit/working-directory.test.ts b/tools/ui/tests/unit/working-directory.test.ts index f7858e29bf2..7481c154d06 100644 --- a/tools/ui/tests/unit/working-directory.test.ts +++ b/tools/ui/tests/unit/working-directory.test.ts @@ -2,10 +2,12 @@ import { describe, expect, it } from 'vitest'; import { splitPathQuery, buildCaseInsensitiveGlob, + buildGlobSearchArgs, rankEntries, joinPath, highlightMatch } from '$lib/utils'; +import { GLOB_WILDCARD, PATH_NAV_MAX_DEPTH } from '$lib/constants'; describe('splitPathQuery', () => { it('treats a plain query as a home-relative glob (not navigation)', () => { @@ -124,3 +126,41 @@ describe('highlightMatch', () => { expect(highlightMatch('abc', 'z')).toEqual([{ text: 'abc', match: false }]); }); }); + +describe('buildGlobSearchArgs', () => { + const DEPTH = 6; + + it('glob-matches home-relative within the scope path', () => { + const args = buildGlobSearchArgs('docs', '/home', DEPTH); + expect(args.path).toBe('/home'); + expect(args.include).toBe(buildCaseInsensitiveGlob('docs')); + expect(args.maxDepth).toBe(DEPTH); + expect(args.rankQuery).toBe('docs'); + expect(args.last).toBeUndefined(); + }); + + it('navigates home for a `~` path query', () => { + const args = buildGlobSearchArgs('~/proj', '/home', DEPTH); + expect(args.path).toBe('~'); + expect(args.include).toBe(buildCaseInsensitiveGlob('proj')); + expect(args.maxDepth).toBe(PATH_NAV_MAX_DEPTH); + expect(args.rankQuery).toBe('proj'); + expect(args.last).toBe('proj'); + }); + + it('lists the scope root when a path query has no last segment', () => { + const args = buildGlobSearchArgs('~/', '/home', DEPTH); + expect(args.path).toBe('~'); + expect(args.include).toBe(GLOB_WILDCARD); + expect(args.maxDepth).toBe(PATH_NAV_MAX_DEPTH); + }); + + it('navigates an absolute path under its root', () => { + const args = buildGlobSearchArgs('/usr/local/bin', '/home', DEPTH); + expect(args.path).toBe('/usr/local'); + expect(args.include).toBe(buildCaseInsensitiveGlob('bin')); + expect(args.maxDepth).toBe(PATH_NAV_MAX_DEPTH); + expect(args.rankQuery).toBe('bin'); + expect(args.last).toBe('bin'); + }); +}); From 75afc97dcde79788954c154dbecefa204577e214 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 10 Aug 2026 01:32:04 +0300 Subject: [PATCH 52/61] expert tier: pin 30 default, sidecar no-freeze, ram-pressure eviction --- src/llama-context.cpp | 14 +++--------- src/llama-expert-heatmap.cpp | 7 +++++- src/llama-expert-heatmap.h | 1 + src/llama-expert-hotstore.cpp | 3 --- src/llama-expert-hotstore.h | 1 - src/llama-expert-pin.cpp | 41 +++++++++++++++++++++++++++++++++++ src/llama-expert-pin.h | 4 ++-- 7 files changed, 53 insertions(+), 18 deletions(-) diff --git a/src/llama-context.cpp b/src/llama-context.cpp index b15bc91dd09..bb5a0da223b 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -478,16 +478,12 @@ llama_context::llama_context( params.expert_hot_s); } - // expert sidecar: restore the heatmap from .tier if present; freeze - // store adaptation so the run measures the pre-warmed store + // expert sidecar: restore the heatmap from .tier if present; the + // store starts pre-warmed and keeps adapting from there expert_sidecar_enabled = params.expert_sidecar; expert_sidecar_path = std::string(params.model_path ? params.model_path : "") + ".tier"; - bool sidecar_loaded = false; if (expert_heatmap && params.expert_sidecar) { - const std::string sc = expert_sidecar_path; - if (expert_heatmap->load(sc.c_str())) { - sidecar_loaded = true; - } + expert_heatmap->load(expert_sidecar_path.c_str()); } if (hparams.n_expert > 0 && !cparams.warmup && params.expert_hot_s != 0) { @@ -519,10 +515,6 @@ llama_context::llama_context( expert_hotstore->log(); } - if (sidecar_loaded && expert_hotstore) { - expert_hotstore->frozen = true; - } - // Initialize the full vocabulary token ids for backend samplers. { const int n_vocab = model.vocab.n_tokens(); diff --git a/src/llama-expert-heatmap.cpp b/src/llama-expert-heatmap.cpp index 8caf77426dd..899f5083f56 100644 --- a/src/llama-expert-heatmap.cpp +++ b/src/llama-expert-heatmap.cpp @@ -17,7 +17,8 @@ llama_expert_heatmap::llama_expert_heatmap( log_period(log_period), tokens_total(0), generated_tokens_count(0), - heat(n_layers * n_experts, 0.0f) { + heat(n_layers * n_experts, 0.0f), + last_reuse(n_layers * n_experts, 0) { } void llama_expert_heatmap::update_counts(const std::vector & per_layer, int n_tokens) { @@ -28,9 +29,11 @@ void llama_expert_heatmap::update_counts(const std::vector & pe continue; } float * layer_heat = &heat[il * n_experts]; + int64_t * layer_reuse = &last_reuse[il * n_experts]; for (int e = 0; e < n_experts; e++) { if (cnt[e] > 0) { layer_heat[e] += (float) cnt[e]; + layer_reuse[e] = tokens_total; } } } @@ -57,11 +60,13 @@ void llama_expert_heatmap::update_ids(int layer_idx, const int32_t * expert_ids, return; } float * layer_heat = &heat[layer_idx * n_experts]; + int64_t * layer_reuse = &last_reuse[layer_idx * n_experts]; for (int t = 0; t < n_tokens; t++) { for (int e = 0; e < n_ids; e++) { const int32_t id = expert_ids[t * n_ids + e]; if (id >= 0 && id < n_experts) { layer_heat[id] += 1.0f; + layer_reuse[id] = tokens_total; } } } diff --git a/src/llama-expert-heatmap.h b/src/llama-expert-heatmap.h index d4e28cde8fe..c5937dd7c22 100644 --- a/src/llama-expert-heatmap.h +++ b/src/llama-expert-heatmap.h @@ -15,6 +15,7 @@ struct llama_expert_heatmap { int64_t generated_tokens_count; // decode tokens seen; drives first-fill deferral int update_counter = 1; // batched decay every 2 updates; start at 1 for early stability std::vector heat; + std::vector last_reuse; // last token each expert was routed (dwell gate) llama_expert_heatmap(int n_layers, int n_experts, float decay_rate = 0.99f, diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 4a5a099b51e..707d75f8d4e 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -978,9 +978,6 @@ bool llama_expert_hotstore::maybe_resync(const llama_expert_heatmap & heatmap, b if (multi_slot || heatmap.tokens_total <= 0) { return false; } - if (frozen) { - return false; - } // adaptive cadence: floor 10 (5 in copy mode: host-pool moves are half // the bandwidth), stretching to 32 as the hit rate climbs toward 6x target float ratio = hit_rate_valid ? hit_rate / target_hit_rate() : 0.0f; diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index a318d19708d..01659fff1c2 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -98,7 +98,6 @@ struct llama_expert_hotstore { float hyst = 0.0f; // 0 = gate off (swap freely) int dwell = 0; // minimum syncs a resident must keep; 0 = off bool copy_mode = false; // keep the RAM copy of promoted experts (copy), else move - bool frozen = false; // sidecar loaded: store is pre-warmed, skip adaptation // max concurrent transfers in flight per layer, per direction (eviction // queue + promotion queue). higher = faster store adaptation, at the cost // of more slots temporarily in transition (not counted). diff --git a/src/llama-expert-pin.cpp b/src/llama-expert-pin.cpp index 8f013f5d608..40b24712dd4 100644 --- a/src/llama-expert-pin.cpp +++ b/src/llama-expert-pin.cpp @@ -101,6 +101,24 @@ static void hint_experts(const llama_model * model, const int n_layers = heatmap.n_layers; const int n_experts = heatmap.n_experts; + // RAM-pressure gate: only evict cold pages when the system is genuinely + // tight (MemAvailable under 10% of total). + bool ram_tight = false; + int64_t mem_total = 0, mem_avail = 0; + FILE * f = fopen("/proc/meminfo", "r"); + if (f) { + char line[256]; + while (fgets(line, sizeof(line), f)) { + if (sscanf(line, "MemTotal: %lld kB", &mem_total) == 1) { + mem_total *= 1024; + } else if (sscanf(line, "MemAvailable: %lld kB", &mem_avail) == 1) { + mem_avail *= 1024; + } + } + fclose(f); + } + ram_tight = mem_total > 0 && mem_avail * 10 < mem_total; + // group the exps tensors by layer std::vector> per_layer(n_layers); for (const auto & [name, tensor] : llama_internal_get_tensor_map(model)) { @@ -174,6 +192,29 @@ static void hint_experts(const llama_model * model, } } } + + // RAM pressure: evict the bottom 10% of total heat that is resident + // in the mmap pool and has not been reused for a full dwell cycle. + if (ram_tight) { + std::vector all(n_experts); + for (int e = 0; e < n_experts; e++) { + all[e] = e; + } + std::sort(all.begin(), all.end(), by_score); + const int n_evict = std::max(1, (int) (0.10f * (float) n_experts)); + for (int i = 0; i < n_evict; i++) { + const int e = all[i]; + if (is_gpu_resident && is_gpu_resident(ud, il, e)) { + continue; // on GPU: its mmap pages are already dropped + } + if (heatmap.tokens_total - heatmap.last_reuse[il * n_experts + e] < 8) { + continue; // reused within the dwell cycle: keep it + } + for (const ggml_tensor * w : per_layer[il]) { + hint_expert(w, e, false); + } + } + } } } diff --git a/src/llama-expert-pin.h b/src/llama-expert-pin.h index 77ced1ef342..760f37ce574 100644 --- a/src/llama-expert-pin.h +++ b/src/llama-expert-pin.h @@ -11,11 +11,11 @@ namespace llama_expert_pin { // dials, all env-overridable with these defaults struct config { - int period = 32; // tokens between passes + int period = 24; // tokens between passes int start_tokens = 128; // first pass at this many tokens float dontneed_gpu = 0.20f; // top fraction of GPU experts to drop float willneed_gpu = 0.20f; // bottom fraction of GPU experts to warm - float willneed_cold = 0.70f; // top fraction of cold experts to warm + float willneed_cold = 0.30f; // top fraction of cold experts to warm }; const config & get_config(); From f2b29ef517d1bb6b10cd1000859504944067559c Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 10 Aug 2026 01:50:47 +0300 Subject: [PATCH 53/61] ggml: bump rpc patch version, fix msvc prefetch in cold op --- ggml/include/ggml-rpc.h | 4 ++-- ggml/src/ggml-cpu/ggml-cpu-moe-cold.c | 12 ++++++++++-- 2 files changed, 12 insertions(+), 4 deletions(-) diff --git a/ggml/include/ggml-rpc.h b/ggml/include/ggml-rpc.h index a88eab44011..4b4f3ba07c8 100644 --- a/ggml/include/ggml-rpc.h +++ b/ggml/include/ggml-rpc.h @@ -8,10 +8,10 @@ extern "C" { #define RPC_PROTO_MAJOR_VERSION 5 #define RPC_PROTO_MINOR_VERSION 0 -#define RPC_PROTO_PATCH_VERSION 1 +#define RPC_PROTO_PATCH_VERSION 2 #ifdef __cplusplus -static_assert(GGML_OP_COUNT == 102, "GGML_OP_COUNT has changed - update RPC_PROTO_PATCH_VERSION"); +static_assert(GGML_OP_COUNT == 103, "GGML_OP_COUNT has changed - update RPC_PROTO_PATCH_VERSION"); #endif #define GGML_RPC_MAX_SERVERS 16 diff --git a/ggml/src/ggml-cpu/ggml-cpu-moe-cold.c b/ggml/src/ggml-cpu/ggml-cpu-moe-cold.c index 74239125b2f..4af91baf976 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-moe-cold.c +++ b/ggml/src/ggml-cpu/ggml-cpu-moe-cold.c @@ -50,6 +50,14 @@ static LONG atomic_fetch_add_explicit(atomic_int * ptr, LONG inc, memory_order m #include #endif +// __builtin_prefetch is a GCC/Clang builtin; MSVC has no equivalent, so +// compile it to a no-op there +#if defined(_MSC_VER) && !defined(__clang__) +#define PREFETCH(p) ((void) 0) +#else +#define PREFETCH(p) __builtin_prefetch(p, 0, 3) +#endif + // resolve a cold expert's weight slice through the registered hook, else the // tensor's own data (mmap or the model buffer) static const char * moe_cold_slice(const struct ggml_tensor * w, int64_t e, const char * fallback) { @@ -210,8 +218,8 @@ void ggml_compute_forward_moe_cold( float * gout = gate_out + (col0[cur_a] + c)*n_ff; float * uout = up_out + (col0[cur_a] + c)*n_ff; for (int64_t i = ir0_start; i < ir0_end; i++) { - __builtin_prefetch(wg + (i + 1)*w_gate->nb[1], 0, 3); - __builtin_prefetch(wu + (i + 1)*w_up->nb[1], 0, 3); + PREFETCH(wg + (i + 1)*w_gate->nb[1]); + PREFETCH(wu + (i + 1)*w_up->nb[1]); vec_dot_g(ne_embd, &gout[i], 0, wg + i*w_gate->nb[1], 0, xcol, 0, 1); vec_dot_g(ne_embd, &uout[i], 0, wu + i*w_up->nb[1], 0, xcol, 0, 1); } From 813353fe16404d81ba66f4d09849bee19dd7ef99 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 10 Aug 2026 01:58:26 +0300 Subject: [PATCH 54/61] expert tier: windows portability for hotstore and preload --- src/llama-expert-hotstore.cpp | 10 ++++++++++ src/llama-expert-preload.cpp | 20 ++++++++++++++++---- 2 files changed, 26 insertions(+), 4 deletions(-) diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 707d75f8d4e..2487988d4ae 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -13,7 +13,10 @@ #include #include #include + +#if !defined(_WIN32) #include +#endif #ifdef _WIN32 #include @@ -123,6 +126,12 @@ llama_expert_hotstore::llama_expert_hotstore( // available RAM: MemAvailable includes reclaimable page cache; // _SC_AVPHYS_PAGES only counts truly-free pages and underreports int64_t free_ram = 0; +#if defined(_WIN32) + MEMORYSTATUSEX ms = { sizeof(ms) }; + if (GlobalMemoryStatusEx(&ms)) { + free_ram = (int64_t) ms.ullAvailPhys; + } +#else FILE * f = fopen("/proc/meminfo", "r"); if (f) { char line[256]; @@ -138,6 +147,7 @@ llama_expert_hotstore::llama_expert_hotstore( const long page = sysconf(_SC_PAGESIZE); free_ram = (int64_t) sysconf(_SC_AVPHYS_PAGES) * page; } +#endif if (exps_bytes > 0 && free_ram > exps_bytes * 2) { copy_mode = true; fprintf(stderr, "hotstore: copy mode: exps (%d MiB) fit in RAM (%d MiB free)\n", diff --git a/src/llama-expert-preload.cpp b/src/llama-expert-preload.cpp index 4414f7a20e7..14850418a77 100644 --- a/src/llama-expert-preload.cpp +++ b/src/llama-expert-preload.cpp @@ -12,6 +12,19 @@ #ifdef _WIN32 #include +#include +#include +#include +// MSVC POSIX layer: map open/close to _open/_close and emulate pread +#define open _open +#define close _close +#define O_RDONLY _O_RDONLY +static long long pread(int fd, void * buf, size_t n, long long off) { + if (_lseeki64(fd, off, SEEK_SET) < 0) { + return -1; + } + return _read(fd, buf, (unsigned int) n); +} #else #include #include @@ -71,7 +84,6 @@ void set_model_path(const char * path) { } g_fd = open(g_path.c_str(), O_RDONLY); } - void set_slots(int s) { g_slots = s; } @@ -210,9 +222,9 @@ bool read_expert(size_t idx, int expert, void * out, size_t n) { if (n > e.plane_bytes) { return false; } - const ssize_t got = pread(g_fd >= 0 ? g_fd : e.fd, out, n, - (off_t) (e.file_off + (size_t) expert * e.plane_bytes)); - return got == (ssize_t) n; + const long long got = pread(g_fd >= 0 ? g_fd : e.fd, out, n, + (long long) (e.file_off + (size_t) expert * e.plane_bytes)); + return got == (long long) n; } bool write_cold(size_t idx, const uint8_t * data, size_t nbytes) { From efa09e531f0eda3998c5f7a1f4762acfce054b36 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 10 Aug 2026 02:01:42 +0300 Subject: [PATCH 55/61] server: document expert tier flags --- tools/server/README.md | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/tools/server/README.md b/tools/server/README.md index 64f0b03269d..4339c72b7ac 100644 --- a/tools/server/README.md +++ b/tools/server/README.md @@ -115,6 +115,22 @@ For the full list of features, please refer to [server's changelog](https://gith | `--spec-draft-type-k, -ctkd, --cache-type-k-draft TYPE` | KV cache data type for K for the draft model
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_SPEC_DRAFT_CACHE_TYPE_K) | | `--spec-draft-type-v, -ctvd, --cache-type-v-draft TYPE` | KV cache data type for V for the draft model
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_SPEC_DRAFT_CACHE_TYPE_V) | +### Expert tier params + +| Argument | Explanation | +| -------- | ----------- | +| `-ehs, --expert-hot-s N` | expert hot store slots: -1 = autofit from free VRAM, 0 = disabled, N = manual top-N slots
(env: LLAMA_ARG_EXPERT_HOT_S) | +| `--expert-pin N` | fraction (percent) of cold experts to keep pinned in RAM via madvise, 0 = off, -1 = auto
(env: LLAMA_ARG_EXPERT_PIN) | +| `--expert-copy` | copy experts to the GPU store (keep the RAM copy). default: move (GPU store replaces the RAM copy; frees RAM)
(env: LLAMA_ARG_EXPERT_COPY) | +| `--expert-sidecar` | load the expert heatmap sidecar (`.tier`) at start, save it at exit
(env: LLAMA_ARG_EXPERT_SIDECAR) | +| `--expert-gpu N` | put the expert store on this GPU index (default: -1 = all GPUs)
(env: LLAMA_ARG_EXPERT_GPU) | +| `--expert-sync-period N` | expert hot store re-sync cadence in tokens (default: 1)
(env: LLAMA_ARG_EXPERT_SYNC_PERIOD) | +| `--expert-hyst F` | expert hot store hysteresis ratio (default: 1.3, 0 = off)
(env: LLAMA_ARG_EXPERT_HYST) | +| `--expert-dwell N` | expert hot store minimum dwell updates before swap (default: 0 = off)
(env: LLAMA_ARG_EXPERT_DWELL) | +| `--expert-heat-decay F` | expert heatmap decay rate per update (default: 0.999)
(env: LLAMA_ARG_EXPERT_HEAT_DECAY) | +| `--expert-heat-log-period N` | print the expert heatmap at generation end (default: 0, 0 = off)
(env: LLAMA_ARG_EXPERT_HEAT_LOG_PERIOD) | +| `--expert-no-evict` | never evict experts from the hot store (fill-only, no move-back) | + ### Sampling params From 5e5a498d83e52b024b3854390112d83d0e71ac8b Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 10 Aug 2026 02:21:07 +0300 Subject: [PATCH 56/61] expert tier: fix werror issues, revert expert-gpu list, cli docs --- common/arg.cpp | 7 +++++++ common/common.cpp | 1 + common/common.h | 1 + include/llama.h | 1 + src/llama-context.cpp | 4 ++++ src/llama-expert-hotstore.cpp | 8 +++++--- src/llama-expert-pin.cpp | 8 ++++++-- src/llama-expert-preload.cpp | 5 ++++- tools/cli/README.md | 16 ++++++++++++++++ 9 files changed, 45 insertions(+), 6 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index 67ec8a6550e..f07a21e0512 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2773,6 +2773,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex params.expert_sidecar = value; } ).set_env("LLAMA_ARG_EXPERT_SIDECAR")); + add_opt(common_arg( + {"--expert-gpu"}, "N", + "put the expert store on this GPU index (default: -1 = all GPUs)", + [](common_params & params, int value) { + params.expert_gpu = value; + } + ).set_env("LLAMA_ARG_EXPERT_GPU")); GGML_ASSERT(params.n_gpu_layers < 0); // string_format would need to be extended for a default >= 0 add_opt(common_arg( {"-ngl", "--gpu-layers", "--n-gpu-layers"}, "N", diff --git a/common/common.cpp b/common/common.cpp index 133416feaf5..abeb84b62ba 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1712,6 +1712,7 @@ struct llama_context_params common_context_params_to_llama(const common_params & cparams.expert_pin_pct = params.expert_pin_pct; cparams.expert_copy = params.expert_copy; cparams.expert_sidecar = params.expert_sidecar; + cparams.expert_gpu = params.expert_gpu; cparams.model_path = params.model.path.c_str(); return cparams; diff --git a/common/common.h b/common/common.h index d33ef2001ec..80b94350f70 100644 --- a/common/common.h +++ b/common/common.h @@ -533,6 +533,7 @@ struct common_params { int expert_pin_pct = -1; // percent of cold experts to keep pinned (madvise); -1 = auto bool expert_copy = false; // copy experts to GPU (keep RAM copy); default move bool expert_sidecar = false; // load/save the expert heatmap sidecar (.tier) + int expert_gpu = -1; // expert store GPU index (-1 = all GPUs) bool offline = false; int32_t ppl_stride = 0; // stride for perplexity calculations. If left at 0, the pre-existing approach will be used. diff --git a/include/llama.h b/include/llama.h index 537471f9570..9c69aa8b65c 100644 --- a/include/llama.h +++ b/include/llama.h @@ -415,6 +415,7 @@ extern "C" { int expert_pin_pct; // percent of cold experts to keep pinned (madvise); -1 = auto bool expert_copy; // copy experts to GPU (keep RAM copy); default move bool expert_sidecar; // load/save the expert heatmap sidecar (.tier) + int expert_gpu; // put the expert store on this GPU index (-1 = all GPUs) // a source/target/parent context // can be utilized in various ways, for example by sharing results or llama_memory between 2 contexts diff --git a/src/llama-context.cpp b/src/llama-context.cpp index bb5a0da223b..3faefb659d9 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -502,6 +502,9 @@ llama_context::llama_context( if (type == GGML_BACKEND_DEVICE_TYPE_CPU || type == GGML_BACKEND_DEVICE_TYPE_ACCEL) { continue; } + if (params.expert_gpu >= 0 && (int) gpu_bufts.size() != params.expert_gpu) { + continue; // store pinned to a specific GPU: skip the others + } gpu_bufts.push_back(ggml_backend_get_default_buffer_type(backend.get())); } if (!gpu_bufts.empty()) { @@ -3647,6 +3650,7 @@ llama_context_params llama_context_default_params() { /*.expert_pin_pct =*/ -1, /*.expert_copy =*/ false, /*.expert_sidecar =*/ false, + /*.expert_gpu =*/ -1, /*.ctx_other =*/ nullptr, }; diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index 2487988d4ae..dbc867bc1e5 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -10,6 +10,7 @@ #include "ggml-cpu.h" #include +#include #include #include #include @@ -19,6 +20,9 @@ #endif #ifdef _WIN32 +#ifndef NOMINMAX +#define NOMINMAX +#endif #include #endif @@ -136,7 +140,7 @@ llama_expert_hotstore::llama_expert_hotstore( if (f) { char line[256]; while (fgets(line, sizeof(line), f)) { - if (sscanf(line, "MemAvailable: %lld kB", &free_ram) == 1) { + if (sscanf(line, "MemAvailable: %" PRId64 " kB", &free_ram) == 1) { free_ram *= 1024; break; } @@ -419,7 +423,6 @@ bool llama_expert_hotstore::copy_top_s(const llama_expert_heatmap & heatmap) { for (entry * e : entries_by_layer[il]) { const size_t slot = ggml_nbytes(e->src) / (size_t) e->src->ne[2]; - const int pidx = llama_expert_preload::index_of(e->src); if (preloaded) { // the startup slices were streamed into the store at load // (write_entry), so the GPU store is already sound. @@ -672,7 +675,6 @@ bool llama_expert_hotstore::resync_top_s(const llama_expert_heatmap & heatmap) { if (pidx < 0) { continue; // mmap: data stays in the file } - const size_t slot = ggml_nbytes(ent->src) / (size_t) ent->src->ne[2]; llama_expert_preload::set_cpu_slice(pidx, it->expert, &stg[stg_off + staging_slot_off(entries_by_layer[il], ent)]); } rout[it->expert] = 0; // the CPU output counts now diff --git a/src/llama-expert-pin.cpp b/src/llama-expert-pin.cpp index 40b24712dd4..c6b630ab660 100644 --- a/src/llama-expert-pin.cpp +++ b/src/llama-expert-pin.cpp @@ -8,6 +8,7 @@ #include "ggml-backend.h" #include +#include #include #include #include @@ -17,6 +18,9 @@ #include #include #else +#ifndef NOMINMAX +#define NOMINMAX +#endif #include #endif @@ -109,9 +113,9 @@ static void hint_experts(const llama_model * model, if (f) { char line[256]; while (fgets(line, sizeof(line), f)) { - if (sscanf(line, "MemTotal: %lld kB", &mem_total) == 1) { + if (sscanf(line, "MemTotal: %" PRId64 " kB", &mem_total) == 1) { mem_total *= 1024; - } else if (sscanf(line, "MemAvailable: %lld kB", &mem_avail) == 1) { + } else if (sscanf(line, "MemAvailable: %" PRId64 " kB", &mem_avail) == 1) { mem_avail *= 1024; } } diff --git a/src/llama-expert-preload.cpp b/src/llama-expert-preload.cpp index 14850418a77..25f6402cc15 100644 --- a/src/llama-expert-preload.cpp +++ b/src/llama-expert-preload.cpp @@ -11,6 +11,9 @@ #include #ifdef _WIN32 +#ifndef NOMINMAX +#define NOMINMAX +#endif #include #include #include @@ -230,7 +233,7 @@ bool read_expert(size_t idx, int expert, void * out, size_t n) { bool write_cold(size_t idx, const uint8_t * data, size_t nbytes) { if (idx >= g_entries.size() || !g_cpu_buf || !data) { fprintf(stderr, "write_cold: FAIL idx=%zu cpu_buf=%p data=%p nbytes=%zu\n", - idx, (void *) g_cpu_buf, (void *) data, nbytes); + idx, (void *) g_cpu_buf, (const void *) data, nbytes); return false; } const entry & e = g_entries[idx]; diff --git a/tools/cli/README.md b/tools/cli/README.md index 8944328e9c2..4e76525b2b1 100644 --- a/tools/cli/README.md +++ b/tools/cli/README.md @@ -105,6 +105,22 @@ | `--spec-draft-type-k, -ctkd, --cache-type-k-draft TYPE` | KV cache data type for K for the draft model
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_SPEC_DRAFT_CACHE_TYPE_K) | | `--spec-draft-type-v, -ctvd, --cache-type-v-draft TYPE` | KV cache data type for V for the draft model
allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
(default: f16)
(env: LLAMA_ARG_SPEC_DRAFT_CACHE_TYPE_V) | +### Expert tier params + +| Argument | Explanation | +| -------- | ----------- | +| `-ehs, --expert-hot-s N` | expert hot store slots: -1 = autofit from free VRAM, 0 = disabled, N = manual top-N slots
(env: LLAMA_ARG_EXPERT_HOT_S) | +| `--expert-pin N` | fraction (percent) of cold experts to keep pinned in RAM via madvise, 0 = off, -1 = auto
(env: LLAMA_ARG_EXPERT_PIN) | +| `--expert-copy` | copy experts to the GPU store (keep the RAM copy). default: move (GPU store replaces the RAM copy; frees RAM)
(env: LLAMA_ARG_EXPERT_COPY) | +| `--expert-sidecar` | load the expert heatmap sidecar (`.tier`) at start, save it at exit
(env: LLAMA_ARG_EXPERT_SIDECAR) | +| `--expert-gpu N` | put the expert store on this GPU index (default: -1 = all GPUs)
(env: LLAMA_ARG_EXPERT_GPU) | +| `--expert-sync-period N` | expert hot store re-sync cadence in tokens (default: 1)
(env: LLAMA_ARG_EXPERT_SYNC_PERIOD) | +| `--expert-hyst F` | expert hot store hysteresis ratio (default: 1.3, 0 = off)
(env: LLAMA_ARG_EXPERT_HYST) | +| `--expert-dwell N` | expert hot store minimum dwell updates before swap (default: 0 = off)
(env: LLAMA_ARG_EXPERT_DWELL) | +| `--expert-heat-decay F` | expert heatmap decay rate per update (default: 0.999)
(env: LLAMA_ARG_EXPERT_HEAT_DECAY) | +| `--expert-heat-log-period N` | print the expert heatmap at generation end (default: 0, 0 = off)
(env: LLAMA_ARG_EXPERT_HEAT_LOG_PERIOD) | +| `--expert-no-evict` | never evict experts from the hot store (fill-only, no move-back) | + ### Sampling params From 48f107d35fd43b53d58cb9aee662c9f7f74b3c22 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 10 Aug 2026 02:30:57 +0300 Subject: [PATCH 57/61] expert tier: fix windows and macos portability --- src/llama-expert-hotstore.cpp | 12 +++++++++++- src/llama-expert-pin.cpp | 2 ++ src/llama-model-loader.cpp | 2 -- 3 files changed, 13 insertions(+), 3 deletions(-) diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index dbc867bc1e5..f181534d2c8 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -131,11 +131,14 @@ llama_expert_hotstore::llama_expert_hotstore( // _SC_AVPHYS_PAGES only counts truly-free pages and underreports int64_t free_ram = 0; #if defined(_WIN32) - MEMORYSTATUSEX ms = { sizeof(ms) }; + MEMORYSTATUSEX ms; + memset(&ms, 0, sizeof(ms)); + ms.dwLength = sizeof(ms); if (GlobalMemoryStatusEx(&ms)) { free_ram = (int64_t) ms.ullAvailPhys; } #else +#if defined(__linux__) FILE * f = fopen("/proc/meminfo", "r"); if (f) { char line[256]; @@ -147,9 +150,16 @@ llama_expert_hotstore::llama_expert_hotstore( } fclose(f); } +#endif if (free_ram <= 0) { + // fallback: total pages (Linux AVPHYS is the available count; + // other POSIX lack it, so use PHYS as a coarse bound) const long page = sysconf(_SC_PAGESIZE); +#if defined(_SC_AVPHYS_PAGES) free_ram = (int64_t) sysconf(_SC_AVPHYS_PAGES) * page; +#else + free_ram = (int64_t) sysconf(_SC_PHYS_PAGES) * page; +#endif } #endif if (exps_bytes > 0 && free_ram > exps_bytes * 2) { diff --git a/src/llama-expert-pin.cpp b/src/llama-expert-pin.cpp index c6b630ab660..84528fde542 100644 --- a/src/llama-expert-pin.cpp +++ b/src/llama-expert-pin.cpp @@ -109,6 +109,7 @@ static void hint_experts(const llama_model * model, // tight (MemAvailable under 10% of total). bool ram_tight = false; int64_t mem_total = 0, mem_avail = 0; +#if defined(__linux__) FILE * f = fopen("/proc/meminfo", "r"); if (f) { char line[256]; @@ -121,6 +122,7 @@ static void hint_experts(const llama_model * model, } fclose(f); } +#endif ram_tight = mem_total > 0 && mem_avail * 10 < mem_total; // group the exps tensors by layer diff --git a/src/llama-model-loader.cpp b/src/llama-model-loader.cpp index 0c799a5a8de..1ed0fcdfc16 100644 --- a/src/llama-model-loader.cpp +++ b/src/llama-model-loader.cpp @@ -14,8 +14,6 @@ #include #include #include -#include -#include static const size_t kiB = 1024; static const size_t MiB = 1024*kiB; From ea63c7f6e66a137ef7e7fc469916efa5dea75b0a Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 10 Aug 2026 02:33:17 +0300 Subject: [PATCH 58/61] fix unused param and export cold slice fn --- common/arg.cpp | 2 +- ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index f07a21e0512..4c4177cc118 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2752,7 +2752,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex {"--expert-no-evict"}, {}, "never evict experts from the hot store (fill-only, no move-back)", - [](common_params & params, bool value) { + [](common_params &, bool value) { llama_expert_preload::set_no_evict(value); } )); diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c index d01f7a94d54..dcedb525843 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c @@ -21,11 +21,11 @@ static ggml_mmid_cold_slice_fn g_slice_fn = NULL; -void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn) { +GGML_BACKEND_API void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn) { g_slice_fn = fn; } -const uint8_t * ggml_mmid_cold_get_slice(const struct ggml_tensor * src0, int expert) { +GGML_BACKEND_API const uint8_t * ggml_mmid_cold_get_slice(const struct ggml_tensor * src0, int expert) { return g_slice_fn ? g_slice_fn(src0, expert) : NULL; } #include From b0baf88eba22c726b2edc6bf8d3a06ec89af57a3 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 10 Aug 2026 02:59:28 +0300 Subject: [PATCH 59/61] fix cross platform compiler errors --- ggml/include/ggml-cpu.h | 7 ------- ggml/include/ggml.h | 6 ++++++ ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c | 18 ++---------------- ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h | 4 ---- ggml/src/ggml.c | 10 ++++++++++ 5 files changed, 18 insertions(+), 27 deletions(-) diff --git a/ggml/include/ggml-cpu.h b/ggml/include/ggml-cpu.h index c9f04834b2d..dc6453c6eaa 100644 --- a/ggml/include/ggml-cpu.h +++ b/ggml/include/ggml-cpu.h @@ -147,13 +147,6 @@ extern "C" { GGML_BACKEND_API void ggml_cpu_fp32_to_bf16(const float *, ggml_bf16_t *, int64_t); GGML_BACKEND_API void ggml_cpu_bf16_to_fp32(const ggml_bf16_t *, float *, int64_t); - // optional per-expert slice source for the MoE cold op. when set, the op - // reads expert slices from the hook instead of src0->data (used by the - // llama expert preload, whose exps tensors only carry a placeholder). - // return nullptr to fall back to the tensor's own data. - typedef const uint8_t * (*ggml_mmid_cold_slice_fn)(const struct ggml_tensor * src0, int expert); - GGML_BACKEND_API void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn); - #ifdef __cplusplus } #endif diff --git a/ggml/include/ggml.h b/ggml/include/ggml.h index 7a5376275b8..59f636b87f8 100644 --- a/ggml/include/ggml.h +++ b/ggml/include/ggml.h @@ -1481,6 +1481,12 @@ extern "C" { struct ggml_tensor * counts, int32_t act); + // optional per-expert slice source for the MoE cold op; base lib so the + // dlopen'd ggml-cpu module and the llama lib both resolve it + typedef const uint8_t * (*ggml_mmid_cold_slice_fn)(const struct ggml_tensor * src0, int expert); + GGML_API void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn); + GGML_API const uint8_t * ggml_mmid_cold_get_slice(const struct ggml_tensor * src0, int expert); + // A: m columns, n rows, // B: p columns, n rows, // result is m columns, p rows diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c index dcedb525843..fee27d9d6e8 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.c @@ -18,16 +18,6 @@ #include #include #include - -static ggml_mmid_cold_slice_fn g_slice_fn = NULL; - -GGML_BACKEND_API void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn) { - g_slice_fn = fn; -} - -GGML_BACKEND_API const uint8_t * ggml_mmid_cold_get_slice(const struct ggml_tensor * src0, int expert) { - return g_slice_fn ? g_slice_fn(src0, expert) : NULL; -} #include #include @@ -183,12 +173,8 @@ void ggml_compute_forward_mul_mat_id_cold( // prefer the registered per-expert slice source (expert preload), else // read from the tensor's own data const char * src0_cur; - if (g_slice_fn) { - const uint8_t * s = g_slice_fn(src0, (int) cur_a); - src0_cur = s ? (const char *) s : (const char *) src0->data + cur_a * nb02; - } else { - src0_cur = (const char *) src0->data + cur_a * nb02; - } + const uint8_t * s = ggml_mmid_cold_get_slice(src0, (int) cur_a); + src0_cur = s ? (const char *) s : (const char *) src0->data + cur_a * nb02; const void * wdata = (src1->type == vec_dot_type) ? src1->data : params->wdata; const size_t row_size = ggml_row_size(vec_dot_type, ne10); diff --git a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h index e22bf4f4e54..3a5aa03d503 100644 --- a/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h +++ b/ggml/src/ggml-cpu/ggml-cpu-mul-mat-id-cold.h @@ -41,10 +41,6 @@ void ggml_compute_forward_mul_mat_id_cold( const struct ggml_compute_params * params, struct ggml_tensor * dst); -// resolve an expert slice through the registered hook (nullptr = fall back to -// the tensor's own data); shared by the MUL_MAT_ID_COLD and MOE_COLD kernels -const uint8_t * ggml_mmid_cold_get_slice(const struct ggml_tensor * src0, int expert); - #ifdef __cplusplus } #endif diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c index 22046d4e10c..fca71c73c76 100644 --- a/ggml/src/ggml.c +++ b/ggml/src/ggml.c @@ -3447,6 +3447,16 @@ struct ggml_tensor * ggml_moe_cold( return result; } +static ggml_mmid_cold_slice_fn g_mmid_cold_slice_fn = NULL; + +GGML_API void ggml_mmid_cold_set_slice_fn(ggml_mmid_cold_slice_fn fn) { + g_mmid_cold_slice_fn = fn; +} + +GGML_API const uint8_t * ggml_mmid_cold_get_slice(const struct ggml_tensor * src0, int expert) { + return g_mmid_cold_slice_fn ? g_mmid_cold_slice_fn(src0, expert) : NULL; +} + // ggml_out_prod static inline bool ggml_can_out_prod(const struct ggml_tensor * t0, const struct ggml_tensor * t1) { From 86beff0e67cefbef84d32447ea43356a2c1fadd3 Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 10 Aug 2026 03:31:54 +0300 Subject: [PATCH 60/61] export preload setters for common lib --- src/llama-expert-preload.cpp | 6 +++--- src/llama-expert-preload.h | 8 +++++--- 2 files changed, 8 insertions(+), 6 deletions(-) diff --git a/src/llama-expert-preload.cpp b/src/llama-expert-preload.cpp index 25f6402cc15..5074b019977 100644 --- a/src/llama-expert-preload.cpp +++ b/src/llama-expert-preload.cpp @@ -79,7 +79,7 @@ namespace { } } -void set_model_path(const char * path) { +LLAMA_API void set_model_path(const char * path) { g_path = path ? path : ""; if (g_fd >= 0) { close(g_fd); @@ -87,7 +87,7 @@ void set_model_path(const char * path) { } g_fd = open(g_path.c_str(), O_RDONLY); } -void set_slots(int s) { +LLAMA_API void set_slots(int s) { g_slots = s; } @@ -97,7 +97,7 @@ int get_slots() { bool g_no_evict = false; -void set_no_evict(bool no_evict) { +LLAMA_API void set_no_evict(bool no_evict) { g_no_evict = no_evict; } diff --git a/src/llama-expert-preload.h b/src/llama-expert-preload.h index 4c43008dea9..c16c07e27be 100644 --- a/src/llama-expert-preload.h +++ b/src/llama-expert-preload.h @@ -1,5 +1,7 @@ #pragma once +#include "llama.h" + #include #include @@ -19,10 +21,10 @@ struct ggml_backend_buffer_type; // host buffer through a slice hook. namespace llama_expert_preload { - void set_slots(int s); + LLAMA_API void set_slots(int s); int get_slots(); - void set_model_path(const char * path); // for the debug disk hash - void set_no_evict(bool no_evict); // --expert-no-evict + LLAMA_API void set_model_path(const char * path); // for the debug disk hash + LLAMA_API void set_no_evict(bool no_evict); // --expert-no-evict bool get_no_evict(); // true when the tier will actually build a hot store: slots requested AND From 118554af401b622a34634cd225db182e5eba712a Mon Sep 17 00:00:00 2001 From: Miltos22 Date: Mon, 10 Aug 2026 04:02:25 +0300 Subject: [PATCH 61/61] expert tier: rename mode flag to expert-move-mode --- common/arg.cpp | 13 ++++++------- common/common.cpp | 2 +- common/common.h | 2 +- include/llama.h | 2 +- src/llama-context.cpp | 4 ++-- src/llama-expert-hotstore.cpp | 18 +++++++++++------- src/llama-expert-hotstore.h | 5 +++-- tools/cli/README.md | 2 +- tools/server/README.md | 2 +- 9 files changed, 27 insertions(+), 23 deletions(-) diff --git a/common/arg.cpp b/common/arg.cpp index 4c4177cc118..d07e7c59297 100644 --- a/common/arg.cpp +++ b/common/arg.cpp @@ -2757,14 +2757,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex } )); add_opt(common_arg( - {"--expert-copy"}, - {}, - "copy experts to the GPU store (keep the RAM copy). default: move " - "(GPU store replaces the RAM copy; frees RAM)", - [](common_params & params, bool value) { - params.expert_copy = value; + {"--expert-move-mode"}, "N", + "expert store mode: 0 = auto, 1 = copy (keep RAM copy), 2 = move " + "(free RAM after verified transfer)", + [](common_params & params, int value) { + params.expert_move_mode = value; } - ).set_env("LLAMA_ARG_EXPERT_COPY")); + ).set_env("LLAMA_ARG_EXPERT_MOVE_MODE")); add_opt(common_arg( {"--expert-sidecar"}, {}, diff --git a/common/common.cpp b/common/common.cpp index abeb84b62ba..41f12dd0809 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -1710,7 +1710,7 @@ struct llama_context_params common_context_params_to_llama(const common_params & cparams.expert_hyst = params.expert_hyst; cparams.expert_dwell = params.expert_dwell; cparams.expert_pin_pct = params.expert_pin_pct; - cparams.expert_copy = params.expert_copy; + cparams.expert_move_mode = params.expert_move_mode; cparams.expert_sidecar = params.expert_sidecar; cparams.expert_gpu = params.expert_gpu; cparams.model_path = params.model.path.c_str(); diff --git a/common/common.h b/common/common.h index 80b94350f70..6d4cc47cb61 100644 --- a/common/common.h +++ b/common/common.h @@ -531,7 +531,7 @@ struct common_params { float expert_hyst = 1.3f; // hysteresis ratio: only swap when cold >= hyst x hot int expert_dwell = 0; // minimum updates a resident slot must keep before a swap int expert_pin_pct = -1; // percent of cold experts to keep pinned (madvise); -1 = auto - bool expert_copy = false; // copy experts to GPU (keep RAM copy); default move + int expert_move_mode = 0; // expert store mode: 0 = auto, 1 = copy, 2 = move bool expert_sidecar = false; // load/save the expert heatmap sidecar (.tier) int expert_gpu = -1; // expert store GPU index (-1 = all GPUs) bool offline = false; diff --git a/include/llama.h b/include/llama.h index 9c69aa8b65c..67f6cf6a1b4 100644 --- a/include/llama.h +++ b/include/llama.h @@ -413,8 +413,8 @@ extern "C" { float expert_hyst; // hysteresis ratio for slot swaps int expert_dwell; // min updates a resident slot keeps before swap int expert_pin_pct; // percent of cold experts to keep pinned (madvise); -1 = auto - bool expert_copy; // copy experts to GPU (keep RAM copy); default move bool expert_sidecar; // load/save the expert heatmap sidecar (.tier) + int expert_move_mode; // expert store mode: 0 = auto, 1 = copy, 2 = move int expert_gpu; // put the expert store on this GPU index (-1 = all GPUs) // a source/target/parent context diff --git a/src/llama-context.cpp b/src/llama-context.cpp index 3faefb659d9..5b70e116544 100644 --- a/src/llama-context.cpp +++ b/src/llama-context.cpp @@ -491,7 +491,7 @@ llama_context::llama_context( expert_hotstore = std::make_unique( &model, hparams.n_layer(), hparams.n_expert, params.expert_hot_s, sync_period, - params.expert_hyst, params.expert_dwell, params.expert_copy); + params.expert_hyst, params.expert_dwell, params.expert_move_mode); // enable the GPU hot store on any GPU backend (CUDA, Vulkan, ROCm, // SYCL, Metal, ...). bool cache_enabled = false; @@ -3648,7 +3648,7 @@ llama_context_params llama_context_default_params() { /*.expert_hyst =*/ 1.3f, /*.expert_dwell =*/ 0, /*.expert_pin_pct =*/ -1, - /*.expert_copy =*/ false, + /*.expert_move_mode =*/ 0, /*.expert_sidecar =*/ false, /*.expert_gpu =*/ -1, /*.ctx_other =*/ nullptr, diff --git a/src/llama-expert-hotstore.cpp b/src/llama-expert-hotstore.cpp index f181534d2c8..7ab47c465ed 100644 --- a/src/llama-expert-hotstore.cpp +++ b/src/llama-expert-hotstore.cpp @@ -76,7 +76,7 @@ static const std::regex g_re_exps_weight("blk\\.(\\d+)\\.ffn_(up|down|gate|gate_ llama_expert_hotstore::llama_expert_hotstore( const llama_model * model, int n_layers, int n_experts, int hot_s, int sync_period, - float hyst, int dwell, bool copy_mode) : + float hyst, int dwell, int mode) : n_layers(n_layers), n_experts(n_experts), hot_s(hot_s), @@ -84,7 +84,7 @@ llama_expert_hotstore::llama_expert_hotstore( sync_period(sync_period), hyst(hyst), dwell(dwell), - copy_mode(copy_mode) { + mode(mode) { if (n_layers <= 0) { return; } @@ -112,11 +112,15 @@ llama_expert_hotstore::llama_expert_hotstore( entries_by_layer[e.layer_idx].push_back(&e); } - // auto copy/move: copy keeps the RAM copy of promoted experts (needs the - // full exps set resident); move frees it (RAM-tight). mmap exps are - // file-backed page cache (kernel-reclaimable), so copy is always right - // there; the RAM check only matters on no-mmap (committed anonymous pool). - if (!copy_mode) { + // resolve mode: 1 = copy, 2 = move, 0 = auto. copy keeps the RAM copy of + // promoted experts (needs the full exps set resident); move frees it + // (RAM-tight). mmap exps are file-backed page cache (kernel-reclaimable), + // so copy is always right there; the RAM check only matters on no-mmap. + if (mode == 1) { + copy_mode = true; + } else if (mode == 2) { + copy_mode = false; + } else if (!copy_mode) { const bool mmap_mode = !entries.empty() && llama_expert_preload::index_of(entries[0].src) < 0; if (mmap_mode) { copy_mode = true; diff --git a/src/llama-expert-hotstore.h b/src/llama-expert-hotstore.h index 01659fff1c2..83d140371a8 100644 --- a/src/llama-expert-hotstore.h +++ b/src/llama-expert-hotstore.h @@ -97,7 +97,8 @@ struct llama_expert_hotstore { // expert scores >= hyst * the incumbent AND the slot has dwelled long enough float hyst = 0.0f; // 0 = gate off (swap freely) int dwell = 0; // minimum syncs a resident must keep; 0 = off - bool copy_mode = false; // keep the RAM copy of promoted experts (copy), else move + bool copy_mode = false; // resolved: keep the RAM copy of promoted experts + int mode = 0; // user mode: 0 = auto, 1 = copy, 2 = move // max concurrent transfers in flight per layer, per direction (eviction // queue + promotion queue). higher = faster store adaptation, at the cost // of more slots temporarily in transition (not counted). @@ -138,7 +139,7 @@ struct llama_expert_hotstore { llama_expert_hotstore(const llama_model * model, int n_layers, int n_experts, int hot_s, int sync_period = 0, - float hyst = 0.0f, int dwell = 0, bool copy_mode = false); + float hyst = 0.0f, int dwell = 0, int mode = 0); ~llama_expert_hotstore(); diff --git a/tools/cli/README.md b/tools/cli/README.md index 4e76525b2b1..57a65d8d1d4 100644 --- a/tools/cli/README.md +++ b/tools/cli/README.md @@ -111,7 +111,7 @@ | -------- | ----------- | | `-ehs, --expert-hot-s N` | expert hot store slots: -1 = autofit from free VRAM, 0 = disabled, N = manual top-N slots
(env: LLAMA_ARG_EXPERT_HOT_S) | | `--expert-pin N` | fraction (percent) of cold experts to keep pinned in RAM via madvise, 0 = off, -1 = auto
(env: LLAMA_ARG_EXPERT_PIN) | -| `--expert-copy` | copy experts to the GPU store (keep the RAM copy). default: move (GPU store replaces the RAM copy; frees RAM)
(env: LLAMA_ARG_EXPERT_COPY) | +| `--expert-move-mode N` | expert store mode: 0 = auto, 1 = copy (keep RAM copy), 2 = move (free RAM after verified transfer)
(env: LLAMA_ARG_EXPERT_MOVE_MODE) | | `--expert-sidecar` | load the expert heatmap sidecar (`.tier`) at start, save it at exit
(env: LLAMA_ARG_EXPERT_SIDECAR) | | `--expert-gpu N` | put the expert store on this GPU index (default: -1 = all GPUs)
(env: LLAMA_ARG_EXPERT_GPU) | | `--expert-sync-period N` | expert hot store re-sync cadence in tokens (default: 1)
(env: LLAMA_ARG_EXPERT_SYNC_PERIOD) | diff --git a/tools/server/README.md b/tools/server/README.md index 4339c72b7ac..908fc3003d5 100644 --- a/tools/server/README.md +++ b/tools/server/README.md @@ -121,7 +121,7 @@ For the full list of features, please refer to [server's changelog](https://gith | -------- | ----------- | | `-ehs, --expert-hot-s N` | expert hot store slots: -1 = autofit from free VRAM, 0 = disabled, N = manual top-N slots
(env: LLAMA_ARG_EXPERT_HOT_S) | | `--expert-pin N` | fraction (percent) of cold experts to keep pinned in RAM via madvise, 0 = off, -1 = auto
(env: LLAMA_ARG_EXPERT_PIN) | -| `--expert-copy` | copy experts to the GPU store (keep the RAM copy). default: move (GPU store replaces the RAM copy; frees RAM)
(env: LLAMA_ARG_EXPERT_COPY) | +| `--expert-move-mode N` | expert store mode: 0 = auto, 1 = copy (keep RAM copy), 2 = move (free RAM after verified transfer)
(env: LLAMA_ARG_EXPERT_MOVE_MODE) | | `--expert-sidecar` | load the expert heatmap sidecar (`.tier`) at start, save it at exit
(env: LLAMA_ARG_EXPERT_SIDECAR) | | `--expert-gpu N` | put the expert store on this GPU index (default: -1 = all GPUs)
(env: LLAMA_ARG_EXPERT_GPU) | | `--expert-sync-period N` | expert hot store re-sync cadence in tokens (default: 1)
(env: LLAMA_ARG_EXPERT_SYNC_PERIOD) |