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Fuse dispatch for the legacy interleaved CQ4 GEMV #712

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Fuse dispatch for the legacy interleaved CQ4 GEMV #712

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95 changes: 65 additions & 30 deletions cactus-kernels/src/matmul.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -1694,6 +1694,15 @@ static void cactus_quant_panel_rescale_sb(const int32_t* psb, size_t sb, const f
for (uint32_t c = 0; c < valid; ++c) C[n_start + c] = static_cast<__fp16>(tmp[c]);
}

static size_t cactus_quant_gemv_sb_per_thread() {
static const size_t v = [] {
const char* e = getenv("CACTUS_GEMV_SB_PER_THREAD");
const int i = e ? atoi(e) : 8;
return static_cast<size_t>(i > 0 ? i : 8);
}();
return v;
}

// SME workers live INSIDE the thread budget, replacing NEON workers (measured frontier: flat k=2
// dominates k=0 on speed AND power). Env/setter overrides; backend 2 clamps >= 1 for leaf coverage.
static inline size_t cactus_quant_panel_k_sme(size_t nt, uint32_t gs) {
Expand All @@ -1712,11 +1721,7 @@ static void cactus_quant_panel_gemv(const CactusQuantMatrix* W, const __fp16* A,
const uint32_t N = W->N;
const size_t SB64 = (static_cast<size_t>(N) + 63) / 64;
auto& pool = CactusThreading::get_thread_pool();
static const size_t sb_per_thread = [] {
const char* e = getenv("CACTUS_GEMV_SB_PER_THREAD");
const int v = e ? atoi(e) : 8;
return static_cast<size_t>(v > 0 ? v : 8);
}();
const size_t sb_per_thread = cactus_quant_gemv_sb_per_thread();
const size_t nt_budget = std::max<size_t>(1, (SB64 + sb_per_thread - 1) / sb_per_thread);
const size_t nt = std::min(pool.num_workers(), std::min(nt_budget, SB64));

Expand Down Expand Up @@ -1814,11 +1819,7 @@ void cactus_quant_orth_panel_gemv(const CactusQuantMatrix* W2, const __fp16* rot
const uint32_t num_groups = W2->num_groups;
const size_t SB64 = (static_cast<size_t>(N) + 63) / 64;
auto& pool = CactusThreading::get_thread_pool();
static const size_t sb_per_thread = [] {
const char* e = getenv("CACTUS_GEMV_SB_PER_THREAD");
const int v = e ? atoi(e) : 8;
return static_cast<size_t>(v > 0 ? v : 8);
}();
const size_t sb_per_thread = cactus_quant_gemv_sb_per_thread();
const size_t nt_budget = std::max<size_t>(1, (SB64 + sb_per_thread - 1) / sb_per_thread);
const size_t nt = std::max<size_t>(1, std::min(pool.num_workers(), std::min(nt_budget, SB64)));

Expand Down Expand Up @@ -3051,6 +3052,8 @@ static void cactus_quant_interleaved4_gemv_blocks(
}
}

// Fused IL GEMV: the panel driver's dispatch (group-stolen phase A, spin barrier, dynamic
// 16-block-chunk stealing, main as worker 0, spin-join) over the unchanged IL micro-kernel.
void cactus_quant_4bit_gemv_interleaved(
const CactusQuantMatrix* W,
const uint8_t* packed_interleaved,
Expand All @@ -3064,37 +3067,69 @@ void cactus_quant_4bit_gemv_interleaved(
if (W->group_size > 256) return;

const uint32_t gs = W->group_size;
const uint32_t pgb = cactus_quant_packed_group_bytes(4, gs);
const uint32_t num_groups = W->num_groups;
const size_t N_blocks = W->N / 4;
const size_t n_chunks = (N_blocks + 15) / 16;
auto& pool = CactusThreading::get_thread_pool();
const size_t sb_per_thread = cactus_quant_gemv_sb_per_thread();
const size_t nt_budget = std::max<size_t>(1, (n_chunks + sb_per_thread - 1) / sb_per_thread);
const size_t nt = std::min(pool.num_workers(), std::min(nt_budget, n_chunks));

thread_local std::vector<__fp16> code_basis_buf;
if (code_basis_buf.size() < W->K) code_basis_buf.resize(W->K);
cactus_quant_transform_hadamard_activations(*W, x, 1, code_basis_buf.data());
const __fp16* code_basis = code_basis_buf.data();

thread_local std::vector<int8_t> act_i8_buf;
thread_local std::vector<float> act_scales_buf;
if (act_i8_buf.size() < W->K) act_i8_buf.resize(W->K);
if (act_scales_buf.size() < num_groups) act_scales_buf.resize(num_groups);
for (uint32_t g = 0; g < num_groups; ++g) {
act_scales_buf[g] = tq_quantize_group_i8(
code_basis + static_cast<size_t>(g) * gs,
act_i8_buf.data() + static_cast<size_t>(g) * gs, gs);
}
const int8_t* act_i8 = act_i8_buf.data();
const float* act_scales = act_scales_buf.data();
static thread_local std::vector<int8_t> tl_il_act_i8;
static thread_local std::vector<float> tl_il_act_scales;
if (tl_il_act_i8.size() < W->K) tl_il_act_i8.resize(W->K);
if (tl_il_act_scales.size() < num_groups) tl_il_act_scales.resize(num_groups);
int8_t* act_i8 = tl_il_act_i8.data();
float* act_scales = tl_il_act_scales.data();

int8_t cb_i8[16] = {};
const float cb_scale = tq_quantize_codebook_i8(W->codebook, cb_i8, 16);
const int8x16_t cb_lut = vld1q_s8(cb_i8);

const size_t N_blocks = W->N / 4;
auto phase_a_group = [&](uint32_t g) {
__fp16 basis[256];
cactus_quant_transform_hadamard_group(*W, x + static_cast<size_t>(g) * gs, g, basis);
act_scales[g] = tq_quantize_group_i8(basis, act_i8 + static_cast<size_t>(g) * gs, gs);
};

cactus_quant_parallel_ranges(N_blocks, 64, [&](size_t block_start, size_t block_end) {
if (nt <= 1) {
for (uint32_t g = 0; g < num_groups; ++g) phase_a_group(g);
cactus_quant_interleaved4_gemv_blocks(W, packed_interleaved, norms_interleaved,
act_i8, act_scales, cb_lut, cb_scale,
block_start, block_end, y);
0, N_blocks, y);
return;
}

std::atomic<uint32_t> ga{0};
std::atomic<uint32_t> a_done{0};
std::atomic<uint32_t> next{0};
std::atomic<uint32_t> done{0};
auto worker = [&](size_t) {
for (uint32_t g; (g = ga.fetch_add(1, std::memory_order_relaxed)) < num_groups; ) {
phase_a_group(g);
a_done.fetch_add(1, std::memory_order_release);
}
while (a_done.load(std::memory_order_acquire) < num_groups) { /* spin */ }
for (;;) {
const uint32_t seen = next.load(std::memory_order_relaxed);
if (seen >= n_chunks) break;
const uint32_t want = (n_chunks - seen > 4u * nt) ? 4u : 1u;
const uint32_t ck = next.fetch_add(want, std::memory_order_relaxed);
if (ck >= n_chunks) break;
const uint32_t cnt = std::min<uint32_t>(want, static_cast<uint32_t>(n_chunks) - ck);
const size_t b0 = static_cast<size_t>(ck) * 16;
const size_t b1 = std::min(N_blocks, b0 + static_cast<size_t>(cnt) * 16);
cactus_quant_interleaved4_gemv_blocks(W, packed_interleaved, norms_interleaved,
act_i8, act_scales, cb_lut, cb_scale,
b0, b1, y);
}
};
pool.enqueue_n_threads(nt - 1, nt - 1, [&](size_t wid, size_t) {
worker(wid + 1);
done.fetch_add(1, std::memory_order_release);
});
worker(0);
while (done.load(std::memory_order_acquire) < nt - 1) { /* spin */ }
}

void cactus_quant_3bit_gemv_interleaved(
Expand Down
8 changes: 6 additions & 2 deletions cactus-kernels/tests/test_matmul.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -563,8 +563,8 @@ static bool test_orth_panel(int backend, double& mse_inc, double& mse_panel) {
// legacy interleaved NEON kernel (old bundles); use_panels=true builds the panel layout from the
// SAME interleaved fixture through the reference encoder and exercises the panel GEMV
// (multi-super-block stealing included: N=192 = 3 super-blocks).
static bool test_cq4_interleaved(bool use_panels, int backend, double& mse_out) {
const uint32_t K = 1024, N = 192, gs = 128; // 192 = 3 super-blocks: exercises multi-SB stealing
static bool test_cq4_interleaved(bool use_panels, int backend, double& mse_out,
uint32_t K = 1024, uint32_t N = 192, uint32_t gs = 128) {
SyntheticCQ cq(4, K, N, gs, 777);
if (use_panels) cq.preexpand_il();
CactusQuantMatrix mat = cq.matrix_interleaved();
Expand Down Expand Up @@ -1049,6 +1049,10 @@ int main() {
{
double m1 = 0;
runner.run_test("matmul_cq4_il[file]", test_cq4_interleaved(false, 1, m1));
// N=4164: 1041 IL blocks -> 66 chunks (16-block + 1-block tail) -> multi-thread fused
// driver (phase-A stealing, spin barrier, 4-chunk grabs); N=192 stays on the serial path.
double m_mt = 0;
runner.run_test("matmul_cq4_il_mt[file]", test_cq4_interleaved(false, 1, m_mt, 1024, 4164, 128));
runner.run_test("panel_layout_invariance", test_panel_layout_invariance());
runner.run_test("orth_embed_rows_batched", test_orth_embed_rows());
}
Expand Down
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