Add benchmark

Author: lshaw8317

bench/ndarray/multithreaded_matmul_bench.py

@@ -0,0 +1,48 @@
+import blosc2
+import numpy as np
+import time
+
+N = 10000
+ndim = 2
+ashape = (N,) * ndim
+bshape = ashape
+dtype = np.float64
+
+achunks = (1000, 1000)
+bchunks = (achunks[1], achunks[0])
+ablocks = (200, 200)
+bblocks = (ablocks[1], ablocks[0])
+outblocks = (ablocks[0], bblocks[1])
+outchunks = (achunks[0], bchunks[1])
+# a = blosc2.linspace(0, 1, dtype=dtype, shape=ashape, chunks=achunks, blocks=ablocks)
+# b = blosc2.linspace(0, 1, dtype=dtype, shape=bshape, chunks=bchunks, blocks=bblocks)
+a = blosc2.ones(dtype=dtype, shape=ashape, chunks=achunks, blocks=ablocks)
+b = blosc2.full(fill_value=2, dtype=dtype, shape=bshape, chunks=bchunks, blocks=bblocks)
+
+a_np = a[:]
+b_np = b[:]
+tic = time.time()
+np_res = np.matmul(a_np, b_np)
+print(f'numpy finished in {time.time()-tic} s')
+
+tic = time.time()
+b2_res = blosc2.matmul(a, b, blocks=outblocks, chunks=outchunks)
+print(f'blosc2 multithreaded finished in {time.time()-tic} s')
+
+tic = time.time()
+b2_res = blosc2.matmul(a, b)
+print(f'blosc2 normal finished in {time.time()-tic} s')
+
+achunks = None #(1000, 1000)
+bchunks = None #(achunks[1], achunks[0])
+ablocks = None #(200, 200)
+bblocks = None #(ablocks[1], ablocks[0])
+outblocks = None #(ablocks[0], bblocks[1])
+outchunks = None #(achunks[0], bchunks[1])
+# a = blosc2.linspace(0, 1, dtype=dtype, shape=ashape, chunks=achunks, blocks=ablocks)
+# b = blosc2.linspace(0, 1, dtype=dtype, shape=bshape, chunks=bchunks, blocks=bblocks)
+a = blosc2.ones(dtype=dtype, shape=ashape, chunks=achunks, blocks=ablocks)
+b = blosc2.full(fill_value=2, dtype=dtype, shape=bshape, chunks=bchunks, blocks=bblocks)
+tic = time.time()
+b2_res = blosc2.matmul(a, b, blocks=outblocks, chunks=outchunks)
+print(f'blosc2 normal with default chunks etc. finished in {time.time()-tic} s')