/*************************************************************************************************** * 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. * **************************************************************************************************/ #include #include #include "cutlass_unit_test.h" #include "tools/util/half.h" #include "tools/util/host_tensor.h" #include "tools/util/tensor_view_io.h" #include "cutlass/gemm/volta884_gemm_traits.h" #include "cutlass/gemm/gemm.h" #include "tools/test/unit/gemm/gemm_testbed.h" #include "tools/test/unit/gemm/run_gemm.h" #if CUTLASS_ENABLE_TENSOR_CORE_MMA //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(Volta884_h884gemm_partitionedK_64x64x32, volta884_h884gemm_128x256x88x10_nn) { /* for example partitionedK gemm, m = 128, n = 256, overall_K = 88, partitionK_count = 10 for the first 9 partition k = overall_k / partitionK_count = 8 for the last partition last_k = overall_k - (partitionK_count - 1) * k = 16 for volta884 it is safe to make sure leading dim are multiple of 8 */ int m = 128; int n = 256; int overall_k = 88; int partitionK_count = 10; typedef cutlass::gemm::Volta884GemmTraits< cutlass::MatrixLayout::kColumnMajor, cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<32, 64, 64>, cutlass::Shape<32, 64, 64>, half, half, half, 2 > GemmTraits; run_partitioned_k_gemm(m, n, overall_k, partitionK_count); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(Volta884_h884gemm_partitionedK_64x64x32, volta884_h884gemm_128x256x88x10_nt) { /* for example partitionedK gemm, m = 128, n = 256, overall_K = 88, partitionK_count = 10 for the first 9 partition k = overall_k / partitionK_count = 8 for the last partition last_k = overall_k - (partitionK_count - 1) * k = 16 for volta884 it is safe to make sure leading dim are multiple of 8 */ int m = 128; int n = 256; int overall_k = 88; int partitionK_count = 10; typedef cutlass::gemm::Volta884GemmTraits< cutlass::MatrixLayout::kColumnMajor, cutlass::MatrixLayout::kRowMajor, cutlass::Shape<32, 64, 64>, cutlass::Shape<32, 64, 64>, half, half, half, 2 > GemmTraits; run_partitioned_k_gemm(m, n, overall_k, partitionK_count); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(Volta884_h884gemm_partitionedK_64x64x32, volta884_h884gemm_128x256x88x10_tn) { /* for example partitionedK gemm, m = 128, n = 256, overall_K = 88, partitionK_count = 10 for the first 9 partition k = overall_k / partitionK_count = 8 for the last partition last_k = overall_k - (partitionK_count - 1) * k = 16 for volta884 it is safe to make sure leading dim are multiple of 8 */ int m = 128; int n = 256; int overall_k = 88; int partitionK_count = 10; typedef cutlass::gemm::Volta884GemmTraits< cutlass::MatrixLayout::kRowMajor, cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<32, 64, 64>, cutlass::Shape<32, 64, 64>, half, half, half, 2 > GemmTraits; run_partitioned_k_gemm(m, n, overall_k, partitionK_count); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(Volta884_h884gemm_partitionedK_64x64x32, volta884_h884gemm_128x256x88x10_tt) { /* for example partitionedK gemm, m = 128, n = 256, overall_K = 88, partitionK_count = 10 for the first 9 partition k = overall_k / partitionK_count = 8 for the last partition last_k = overall_k - (partitionK_count - 1) * k = 16 for volta884 it is safe to make sure leading dim are multiple of 8 */ int m = 128; int n = 256; int overall_k = 88; int partitionK_count = 10; typedef cutlass::gemm::Volta884GemmTraits< cutlass::MatrixLayout::kRowMajor, cutlass::MatrixLayout::kRowMajor, cutlass::Shape<32, 64, 64>, cutlass::Shape<32, 64, 64>, half, half, half, 2 > GemmTraits; run_partitioned_k_gemm(m, n, overall_k, partitionK_count); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(Volta884_h884gemm_partitionedK_64x64x32, volta884_h884gemm_128x256x128x10_nn) { /* for example partitionedK gemm, m = 128, n = 256, overall_K = 128, partitionK_count = 10 for the first 9 partition k = overall_k / partitionK_count = 12. But if we require the partition mulitple to be 8, the first 9 partition k = k - (k % partition_mulitiple) = 8 for the last partition last_k = overall_k - (partitionK_count - 1) * k = 56 for volta884 it is safe to make sure leading dim are multiple of 8 */ int m = 128; int n = 256; int overall_k = 128; int partitionK_count = 10; int partitionK_multiple = 8; typedef cutlass::gemm::Volta884GemmTraits< cutlass::MatrixLayout::kColumnMajor, cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<32, 64, 64>, cutlass::Shape<32, 64, 64>, half, half, half, 2 > GemmTraits; run_partitioned_k_gemm(m, n, overall_k, partitionK_count, partitionK_multiple); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(Volta884_h884gemm_partitionedK_64x64x32, volta884_h884gemm_128x256x128x10_nt) { /* for example partitionedK gemm, m = 128, n = 256, overall_K = 128, partitionK_count = 10 for the first 9 partition k = overall_k / partitionK_count = 12. But if we require the partition mulitple to be 8, the first 9 partition k = k - (k % partition_mulitiple) = 8 for the last partition last_k = overall_k - (partitionK_count - 1) * k = 56 for volta884 it is safe to make sure leading dim are multiple of 8 */ int m = 128; int n = 256; int overall_k = 128; int partitionK_count = 10; int partitionK_multiple = 8; typedef cutlass::gemm::Volta884GemmTraits< cutlass::MatrixLayout::kColumnMajor, cutlass::MatrixLayout::kRowMajor, cutlass::Shape<32, 64, 64>, cutlass::Shape<32, 64, 64>, half, half, half, 2 > GemmTraits; run_partitioned_k_gemm(m, n, overall_k, partitionK_count, partitionK_multiple); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(Volta884_h884gemm_partitionedK_64x64x32, volta884_h884gemm_128x256x128x10_tn) { /* for example partitionedK gemm, m = 128, n = 256, overall_K = 128, partitionK_count = 10 for the first 9 partition k = overall_k / partitionK_count = 12. But if we require the partition mulitple to be 8, the first 9 partition k = k - (k % partition_mulitiple) = 8 for the last partition last_k = overall_k - (partitionK_count - 1) * k = 56 for volta884 it is safe to make sure leading dim are multiple of 8 */ int m = 128; int n = 256; int overall_k = 128; int partitionK_count = 10; int partitionK_multiple = 8; typedef cutlass::gemm::Volta884GemmTraits< cutlass::MatrixLayout::kRowMajor, cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<32, 64, 64>, cutlass::Shape<32, 64, 64>, half, half, half, 2 > GemmTraits; run_partitioned_k_gemm(m, n, overall_k, partitionK_count, partitionK_multiple); } //////////////////////////////////////////////////////////////////////////////////////////////////// TEST(Volta884_h884gemm_partitionedK_64x64x32, volta884_h884gemm_128x256x128x10_tt) { /* for example partitionedK gemm, m = 128, n = 256, overall_K = 128, partitionK_count = 10 for the first 9 partition k = overall_k / partitionK_count = 12. But if we require the partition mulitple to be 8, the first 9 partition k = k - (k % partition_mulitiple) = 8 for the last partition last_k = overall_k - (partitionK_count - 1) * k = 56 for volta884 it is safe to make sure leading dim are multiple of 8 */ int m = 128; int n = 256; int overall_k = 128; int partitionK_count = 10; int partitionK_multiple = 8; typedef cutlass::gemm::Volta884GemmTraits< cutlass::MatrixLayout::kRowMajor, cutlass::MatrixLayout::kRowMajor, cutlass::Shape<32, 64, 64>, cutlass::Shape<32, 64, 64>, half, half, half, 2 > GemmTraits; run_partitioned_k_gemm(m, n, overall_k, partitionK_count, partitionK_multiple); } #endif // if defined(CUTLASS_ENABLE_TENSOR_CORE_MMA)