interleaving fails with B
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@@ -39,7 +39,7 @@ void matmul(restrict read_only fp16 *A, restrict read_only fp16 *B,
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fp32 c[TM, TN] = 0;
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fp16* pa[TM, TK] = A + rka[newaxis, :]*lda + rxa[:, newaxis];
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fp16* pb[TN, TK] = B + rkb[newaxis, :]*ldb + ryb[:, newaxis];
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for(int32 k = K; k > TK; k = k - TK){
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for(int32 k = K; k > 0; k = k - TK){
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fp16 a[TM, TK] = *pa;
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fp16 b[TN, TK] = *pb;
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c = dot(a, trans(b), c);
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@@ -117,7 +117,7 @@ class BlockSparseGemmOp : public OpKernel {
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return 2.*M*N*K / ts * 1e-3;
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};
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// just-in-time compile source-code
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jit.autotune("matmul", src, benchmark);
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// jit.autotune("matmul", src, benchmark);
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// jit.add_module("matmul", src, {4, 2, 8, 4, 2, 32, 1, 4, 1, 1, 8, 8, 8, 1});
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// jit.add_module("matmul", src, {32, 2, 128, 32, 2, 128, 2, 2, 2, 2, 4, 8, 4, 1});
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jit.add_module("matmul", src, {16, 4, 128, 16, 4, 128, 2, 2, 2, 2, 8, 32, 8, 1});
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@@ -6,7 +6,7 @@ data_files_path = tf.resource_loader.get_data_files_path()
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library_dir = os.path.dirname(os.path.realpath(__file__))
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module = tf.load_op_library(os.path.join(library_dir, 'libtf_blocksparse.so'))
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M, N, K = 8192,8192,8192
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M, N, K = 128, 128, 128
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a = tf.placeholder(tf.float16, shape=[M, K])
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b = tf.placeholder(tf.float16, shape=[N, K])
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locks = tf.placeholder(tf.int32, shape=[4096])
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@@ -30,10 +30,10 @@ result = sess.run([c], feed_dict = {locks: np.zeros(4096),
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# min_iters=100)
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#print(end - start)
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#print(2*M*N*K / (end - start) * 1e-12)
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#hresult = np.dot(ha.T, hb).T
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#dif = np.abs(result - hresult)
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#print("dif: %f" % np.max(dif))
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hresult = np.dot(ha.T, hb).T
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dif = np.abs(result - hresult)
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print("dif: %f" % np.max(dif))
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#np.savetxt("dif.txt", dif, fmt="%5.2f")
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#np.savetxt("gpu.txt", result, fmt="%5.2f")
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#np.savetxt("cpu.txt", hresult, fmt="%5.2f")
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np.savetxt("dif.txt", dif, fmt="%5.2f")
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np.savetxt("gpu.txt", result, fmt="%5.2f")
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np.savetxt("cpu.txt", hresult, fmt="%5.2f")
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