/*************************************************************************************************** * Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved. * * Redistribution and use in source and binary forms, with or without modification, are permitted * provided that the following conditions are met: * * Redistributions of source code must retain the above copyright notice, this list of * conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright notice, this list of * conditions and the following disclaimer in the documentation and/or other materials * provided with the distribution. * * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used * to endorse or promote products derived from this software without specific prior written * permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, * STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * **************************************************************************************************/ #if (!defined(__CUDA_ARCH__) || (__CUDA_ARCH__ >= 610)) #include "cutlass_unit_test.h" #include "cutlass/gemm/gemm.h" #include "cutlass/gemm/igemm_traits.h" #include "cutlass/reduction/batched_reduction_traits.h" #include "tools/test/unit/gemm/gemm_testbed.h" #include "tools/test/unit/gemm/run_gemm.h" //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(SplitK_igemm_128x128x32_splits16, igemm_128x256x512_nn) { const int splits_count = 16; const int m = 128; const int n = 256; const int k = 512; /*batched igemm traits*/ typedef cutlass::gemm::IgemmTraits, int, cutlass::gemm::LinearScaling > IgemmTraits; /*batched reduction traits*/ typedef cutlass::reduction::BatchedReductionTraits, cutlass::Shape<1, 1, 64>, cutlass::Shape<1, 1, 2> > BatchedReductionTraits; run_splitK_gemm(m, n, k, 2, 1, true /*use host reference*/); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(SplitK_igemm_128x128x32_splits16, igemm_128x256x512_nt) { const int splits_count = 16; const int m = 128; const int n = 256; const int k = 512; /*batched igemm traits*/ typedef cutlass::gemm::IgemmTraits, int, cutlass::gemm::LinearScaling > IgemmTraits; /*batched reduction traits*/ typedef cutlass::reduction::BatchedReductionTraits, cutlass::Shape<1, 1, 64>, cutlass::Shape<1, 1, 2> > BatchedReductionTraits; run_splitK_gemm(m, n, k, 1/*partitionK_multiple*/, 2, 1, true /*use host reference*/); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(SplitK_igemm_128x128x32_splits16, igemm_128x256x512_tn) { const int splits_count = 16; const int m = 128; const int n = 256; const int k = 512; /*batched igemm traits*/ typedef cutlass::gemm::IgemmTraits, int, cutlass::gemm::LinearScaling > IgemmTraits; /*batched reduction traits*/ typedef cutlass::reduction::BatchedReductionTraits, cutlass::Shape<1, 1, 64>, cutlass::Shape<1, 1, 2> > BatchedReductionTraits; run_splitK_gemm(m, n, k, 1/*partitionK_multiple*/, 2, 1, true /*use host reference*/); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(SplitK_igemm_128x128x32_splits16, igemm_128x256x512_tt) { const int splits_count = 16; const int m = 128; const int n = 256; const int k = 512; /*batched igemm traits*/ typedef cutlass::gemm::IgemmTraits, int, cutlass::gemm::LinearScaling > IgemmTraits; /*batched reduction traits*/ typedef cutlass::reduction::BatchedReductionTraits, cutlass::Shape<1, 1, 64>, cutlass::Shape<1, 1, 2> > BatchedReductionTraits; run_splitK_gemm(m, n, k, 1/*partitionK_multiple*/, 2, 1, true /*use host reference*/); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(SplitK_igemm_128x128x32_splits16, igemm_1024x64x4096_nn) { const int splits_count = 16; const int m = 1024; const int n = 64; const int k = 4096; /*batched igemm traits*/ typedef cutlass::gemm::IgemmTraits, int, cutlass::gemm::LinearScaling > IgemmTraits; /*batched reduction traits*/ typedef cutlass::reduction::BatchedReductionTraits, cutlass::Shape<1, 1, 64>, cutlass::Shape<1, 1, 2> > BatchedReductionTraits; run_splitK_gemm(m, n, k, 1/*partitionK_multiple*/, 1, 0, false /*not use host reference*/); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(SplitK_igemm_128x128x32_splits16, igemm_1024x64x4096_nt) { const int splits_count = 16; const int m = 1024; const int n = 64; const int k = 4096; /*batched igemm traits*/ typedef cutlass::gemm::IgemmTraits, int, cutlass::gemm::LinearScaling > IgemmTraits; /*batched reduction traits*/ typedef cutlass::reduction::BatchedReductionTraits, cutlass::Shape<1, 1, 64>, cutlass::Shape<1, 1, 2> > BatchedReductionTraits; run_splitK_gemm(m, n, k, 1/*partitionK_multiple*/, 1, 0, false /*not use host reference*/); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(SplitK_igemm_128x128x32_splits16, igemm_1024x64x4096_tn) { const int splits_count = 16; const int m = 1024; const int n = 64; const int k = 4096; /*batched igemm traits*/ typedef cutlass::gemm::IgemmTraits, int, cutlass::gemm::LinearScaling > IgemmTraits; /*batched reduction traits*/ typedef cutlass::reduction::BatchedReductionTraits, cutlass::Shape<1, 1, 64>, cutlass::Shape<1, 1, 2> > BatchedReductionTraits; run_splitK_gemm(m, n, k, 1/*partitionK_multiple*/, 1, 0, false /*not use host reference*/); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(SplitK_igemm_128x128x32_splits16, igemm_1024x64x4096_tt) { const int splits_count = 16; const int m = 1024; const int n = 64; const int k = 4096; /*batched igemm traits*/ typedef cutlass::gemm::IgemmTraits, int, cutlass::gemm::LinearScaling > IgemmTraits; /*batched reduction traits*/ typedef cutlass::reduction::BatchedReductionTraits, cutlass::Shape<1, 1, 64>, cutlass::Shape<1, 1, 2> > BatchedReductionTraits; run_splitK_gemm(m, n, k, 1/*partitionK_multiple*/, 1, 0, false /*not use host reference*/); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(SplitK_igemm_128x32x32_splits16, igemm_1024x64x4096_nn) { const int splits_count = 16; const int m = 1024; const int n = 64; const int k = 4096; /*batched igemm traits*/ typedef cutlass::gemm::IgemmTraits, int, cutlass::gemm::LinearScaling > IgemmTraits; /*batched reduction traits*/ typedef cutlass::reduction::BatchedReductionTraits, cutlass::Shape<1, 1, 64>, cutlass::Shape<1, 1, 2> > BatchedReductionTraits; run_splitK_gemm(m, n, k, 1/*partitionK_multiple*/, 1, 0, false /*not use host reference*/); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(SplitK_igemm_128x32x32_splits16, igemm_1024x64x4096_nt) { const int splits_count = 16; const int m = 1024; const int n = 64; const int k = 4096; /*batched igemm traits*/ typedef cutlass::gemm::IgemmTraits, int, cutlass::gemm::LinearScaling > IgemmTraits; /*batched reduction traits*/ typedef cutlass::reduction::BatchedReductionTraits, cutlass::Shape<1, 1, 64>, cutlass::Shape<1, 1, 2> > BatchedReductionTraits; run_splitK_gemm(m, n, k, 1/*partitionK_multiple*/, 1, 0, false /*not use host reference*/); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(SplitK_igemm_128x32x32_splits16, igemm_1024x64x4096_tn) { const int splits_count = 16; const int m = 1024; const int n = 64; const int k = 4096; /*batched igemm traits*/ typedef cutlass::gemm::IgemmTraits, int, cutlass::gemm::LinearScaling > IgemmTraits; /*batched reduction traits*/ typedef cutlass::reduction::BatchedReductionTraits, cutlass::Shape<1, 1, 64>, cutlass::Shape<1, 1, 2> > BatchedReductionTraits; run_splitK_gemm(m, n, k, 1/*partitionK_multiple*/, 1, 0, false /*not use host reference*/); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(SplitK_igemm_128x32x32_splits16, igemm_1024x64x4096_tt) { const int splits_count = 16; const int m = 1024; const int n = 64; const int k = 4096; /*batched igemm traits*/ typedef cutlass::gemm::IgemmTraits, int, cutlass::gemm::LinearScaling > IgemmTraits; /*batched reduction traits*/ typedef cutlass::reduction::BatchedReductionTraits, cutlass::Shape<1, 1, 64>, cutlass::Shape<1, 1, 2> > BatchedReductionTraits; run_splitK_gemm(m, n, k, 1/*partitionK_multiple*/, 1, 0, false /*not use host reference*/); } #endif // if (!defined(__CUDA_ARCH__) || (__CUDA_ARCH__ >= 610))