877bdcace6
CUTLASS 1.3 Release - Efficient GEMM kernel targeting Volta Tensor Cores via mma.sync instruction added in CUDA 10.1.
248 lines
8.6 KiB
Plaintext
248 lines
8.6 KiB
Plaintext
/***************************************************************************************************
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* Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without modification, are permitted
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* provided that the following conditions are met:
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* * Redistributions of source code must retain the above copyright notice, this list of
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* conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright notice, this list of
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* conditions and the following disclaimer in the documentation and/or other materials
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* provided with the distribution.
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* * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
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* to endorse or promote products derived from this software without specific prior written
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* permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
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* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
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* FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
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* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
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* STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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**************************************************************************************************/
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#include "cutlass_unit_test.h"
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#include "cutlass/gemm/gemm.h"
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#include "cutlass/gemm/dgemm_traits.h"
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#include "cutlass/reduction/batched_reduction_traits.h"
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#include "tools/test/unit/gemm/gemm_testbed.h"
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#include "tools/test/unit/gemm/run_gemm.h"
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////////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SplitK_dgemm_128x128x8_splits16, dgemm_128x256x512_nn) {
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const int splits_count = 16;
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const int m = 128;
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const int n = 256;
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const int k = 512;
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/*batched sgemm traits*/
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typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kColumnMajor,
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cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
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DgemmTraits;
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/*batched reduction traits*/
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typedef cutlass::reduction::BatchedReductionTraits<double,
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double,
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double,
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double,
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double, /*accumulation type*/
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splits_count,
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cutlass::Shape<1, 1, 128>,
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cutlass::Shape<1, 1, 64>,
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cutlass::Shape<1, 1, 2> >
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BatchedReductionTraits;
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run_splitK_gemm<DgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SplitK_dgemm_128x128x8_splits16, dgemm_128x256x512_nt) {
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const int splits_count = 16;
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const int m = 128;
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const int n = 256;
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const int k = 512;
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/*batched sgemm traits*/
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typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kColumnMajor,
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cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
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DgemmTraits;
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/*batched reduction traits*/
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typedef cutlass::reduction::BatchedReductionTraits<double,
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double,
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double,
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double,
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double, /*accumulation type*/
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splits_count,
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cutlass::Shape<1, 1, 128>,
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cutlass::Shape<1, 1, 64>,
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cutlass::Shape<1, 1, 2> >
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BatchedReductionTraits;
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run_splitK_gemm<DgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SplitK_dgemm_128x128x8_splits16, dgemm_128x256x512_tn) {
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const int splits_count = 16;
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const int m = 128;
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const int n = 256;
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const int k = 512;
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/*batched sgemm traits*/
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typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kRowMajor,
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cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
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DgemmTraits;
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/*batched reduction traits*/
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typedef cutlass::reduction::BatchedReductionTraits<double,
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double,
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double,
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double,
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double, /*accumulation type*/
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splits_count,
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cutlass::Shape<1, 1, 128>,
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cutlass::Shape<1, 1, 64>,
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cutlass::Shape<1, 1, 2> >
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BatchedReductionTraits;
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run_splitK_gemm<DgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SplitK_dgemm_128x128x8_splits16, dgemm_128x256x512_tt) {
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const int splits_count = 16;
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const int m = 128;
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const int n = 256;
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const int k = 512;
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/*batched sgemm traits*/
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typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kRowMajor,
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cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
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DgemmTraits;
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/*batched reduction traits*/
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typedef cutlass::reduction::BatchedReductionTraits<double,
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double,
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double,
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double,
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double, /*accumulation type*/
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splits_count,
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cutlass::Shape<1, 1, 128>,
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cutlass::Shape<1, 1, 64>,
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cutlass::Shape<1, 1, 2> >
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BatchedReductionTraits;
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run_splitK_gemm<DgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SplitK_dgemm_128x128x8_splits16, dgemm_128x256x500_nn) {
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const int splits_count = 16;
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const int m = 128;
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const int n = 256;
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const int k = 500;
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/*batched sgemm traits*/
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typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kColumnMajor,
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cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
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DgemmTraits;
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/*batched reduction traits*/
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typedef cutlass::reduction::BatchedReductionTraits<double,
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double,
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double,
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double,
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double, /*accumulation type*/
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splits_count,
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cutlass::Shape<1, 1, 128>,
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cutlass::Shape<1, 1, 64>,
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cutlass::Shape<1, 1, 2> >
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BatchedReductionTraits;
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run_splitK_gemm<DgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SplitK_dgemm_128x128x8_splits16, dgemm_128x256x500_nt) {
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const int splits_count = 16;
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const int m = 128;
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const int n = 256;
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const int k = 500;
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/*batched sgemm traits*/
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typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kColumnMajor,
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cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
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DgemmTraits;
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/*batched reduction traits*/
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typedef cutlass::reduction::BatchedReductionTraits<double,
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double,
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double,
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double,
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double, /*accumulation type*/
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splits_count,
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cutlass::Shape<1, 1, 128>,
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cutlass::Shape<1, 1, 64>,
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cutlass::Shape<1, 1, 2> >
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BatchedReductionTraits;
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run_splitK_gemm<DgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SplitK_dgemm_128x128x8_splits16, dgemm_128x256x500_tn) {
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const int splits_count = 16;
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const int m = 128;
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const int n = 256;
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const int k = 500;
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/*batched sgemm traits*/
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typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kRowMajor,
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cutlass::MatrixLayout::kColumnMajor, cutlass::Shape<8, 128, 128> >
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DgemmTraits;
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/*batched reduction traits*/
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typedef cutlass::reduction::BatchedReductionTraits<double,
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double,
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double,
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double,
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double, /*accumulation type*/
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splits_count,
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cutlass::Shape<1, 1, 128>,
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cutlass::Shape<1, 1, 64>,
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cutlass::Shape<1, 1, 2> >
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BatchedReductionTraits;
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run_splitK_gemm<DgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SplitK_dgemm_128x128x8_splits16, dgemm_128x256x500_tt) {
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const int splits_count = 16;
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const int m = 128;
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const int n = 256;
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const int k = 500;
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/*batched sgemm traits*/
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typedef cutlass::gemm::DgemmTraits<cutlass::MatrixLayout::kRowMajor,
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cutlass::MatrixLayout::kRowMajor, cutlass::Shape<8, 128, 128> >
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DgemmTraits;
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/*batched reduction traits*/
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typedef cutlass::reduction::BatchedReductionTraits<double,
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double,
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double,
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double,
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double, /*accumulation type*/
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splits_count,
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cutlass::Shape<1, 1, 128>,
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cutlass::Shape<1, 1, 64>,
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cutlass::Shape<1, 1, 2> >
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BatchedReductionTraits;
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run_splitK_gemm<DgemmTraits, BatchedReductionTraits>(m, n, k, 1/*partitionK_multiple*/, 2.0f, 1.0f);
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}
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