277 lines
8.0 KiB
Plaintext
277 lines
8.0 KiB
Plaintext
/***************************************************************************************************
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* Copyright (c) 2017-2018, 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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////////////////////////////////////////////////////////////////////////////////////////////////////
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// Guard conditions around the entire file.
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#if !defined(__CUDA_ARCH__) || __CUDA_ARCH__ >= 700
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////////////////////////////////////////////////////////////////////////////////////////////////////
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#include "cutlass_unit_tests.h"
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#include "tools/util/half.h"
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#include "tools/test/unit/gemm/gemm_testbed.h"
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#include "cutlass/gemm/warp_multiply_add_nvcuda.h"
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////////////////////////////////////////////////////////////////////////////////////////////////////
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//
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// Tests for Warp-level Multiply Add operation using NvCuda API
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//
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namespace test {
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///
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template <typename WarpMultiplyAdd>
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__global__ void warp_multiply_add(
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typename WarpMultiplyAdd::ScalarA const *A,
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int lda,
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typename WarpMultiplyAdd::ScalarB const *B,
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int ldb,
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typename WarpMultiplyAdd::ScalarC *C, int ldc) {
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typename WarpMultiplyAdd::LoadIteratorA iteratorA(A, lda);
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typename WarpMultiplyAdd::LoadIteratorB iteratorB(B, ldb);
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typename WarpMultiplyAdd::StoreIteratorC iteratorC(C, ldc);
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typename WarpMultiplyAdd::FragmentA fragmentA;
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typename WarpMultiplyAdd::FragmentB fragmentB;
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typename WarpMultiplyAdd::FragmentC fragmentC;
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iteratorA.load(fragmentA);
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iteratorB.load(fragmentB);
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fragmentC.clear();
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WarpMultiplyAdd::multiply_add(fragmentC, fragmentA, fragmentB, fragmentC);
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iteratorC.store(fragmentC);
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}
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/// Test environment for Warp Multiply Add operation
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template <
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cutlass::MatrixLayout::Kind LayoutA,
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cutlass::MatrixLayout::Kind LayoutB,
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cutlass::MatrixLayout::Kind LayoutC,
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typename ScalarC,
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typename WarpTile,
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typename WmmaTile
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>
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struct TestWarpMultiplyAdd {
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typedef cutlass::gemm::WarpMultiplyAddNvcuda<
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LayoutA,
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LayoutB,
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LayoutC,
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half,
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half,
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ScalarC,
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WarpTile,
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cutlass::Shape<1, 1, 1, 1>,
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WmmaTile
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> WarpMultiplyAdd;
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/// Testbed type
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typedef test::GemmTestbed<
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cutlass::half_t,
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cutlass::half_t,
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ScalarC,
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ScalarC,
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ScalarC
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> GemmTestbed;
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//
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// Data members
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//
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GemmTestbed testbed;
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//
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// Methods
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//
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TestWarpMultiplyAdd(): testbed(
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WarpTile::kW, // M
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WarpTile::kH, // N
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WarpTile::kD, // K
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cutlass::convert(LayoutA),
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cutlass::convert(LayoutB),
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1,
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0,
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CUBLAS_GEMM_DEFAULT_TENSOR_OP,
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cutlass::convert(LayoutC))
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{
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}
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/// Run
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void run() {
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testbed.initialize();
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// launch
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warp_multiply_add<WarpMultiplyAdd><<<
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dim3(1,1,1), dim3(32, 1, 1)
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>>>(
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testbed.ptr_A(),
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testbed.lda(),
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testbed.ptr_B(),
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testbed.ldb(),
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testbed.ptr_computed(),
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testbed.ldc()
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);
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// verify
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ASSERT_TRUE(testbed.verify_with_host());
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}
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};
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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template <
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typename ScalarC,
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typename WarpTile,
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typename WmmaTile
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>
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struct TestWarpMultiplyAddForAllLayouts {
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void run() {
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test::TestWarpMultiplyAdd<
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cutlass::MatrixLayout::kColumnMajor,
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cutlass::MatrixLayout::kRowMajor,
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cutlass::MatrixLayout::kColumnMajor,
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ScalarC,
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WarpTile,
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WmmaTile
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>().run();
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test::TestWarpMultiplyAdd<
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cutlass::MatrixLayout::kRowMajor,
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cutlass::MatrixLayout::kRowMajor,
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cutlass::MatrixLayout::kColumnMajor,
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ScalarC,
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WarpTile,
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WmmaTile
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>().run();
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test::TestWarpMultiplyAdd<
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cutlass::MatrixLayout::kRowMajor,
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cutlass::MatrixLayout::kColumnMajor,
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cutlass::MatrixLayout::kColumnMajor,
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ScalarC,
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WarpTile,
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WmmaTile
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>().run();
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test::TestWarpMultiplyAdd<
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cutlass::MatrixLayout::kColumnMajor,
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cutlass::MatrixLayout::kColumnMajor,
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cutlass::MatrixLayout::kColumnMajor,
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ScalarC,
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WarpTile,
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WmmaTile
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>().run();
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test::TestWarpMultiplyAdd<
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cutlass::MatrixLayout::kColumnMajor,
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cutlass::MatrixLayout::kRowMajor,
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cutlass::MatrixLayout::kRowMajor,
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ScalarC,
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WarpTile,
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WmmaTile
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>().run();
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test::TestWarpMultiplyAdd<
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cutlass::MatrixLayout::kRowMajor,
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cutlass::MatrixLayout::kRowMajor,
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cutlass::MatrixLayout::kRowMajor,
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ScalarC,
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WarpTile,
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WmmaTile
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>().run();
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test::TestWarpMultiplyAdd<
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cutlass::MatrixLayout::kRowMajor,
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cutlass::MatrixLayout::kColumnMajor,
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cutlass::MatrixLayout::kRowMajor,
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ScalarC,
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WarpTile,
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WmmaTile
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>().run();
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test::TestWarpMultiplyAdd<
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cutlass::MatrixLayout::kColumnMajor,
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cutlass::MatrixLayout::kColumnMajor,
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cutlass::MatrixLayout::kRowMajor,
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ScalarC,
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WarpTile,
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WmmaTile
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>().run();
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}
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};
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////////////////////////////////////////////////////////////////////////////////////////////////////
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//
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// 16x16x16 WMMA Tile Shape with F32 accumulation
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//
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TEST(WmmaGemm, WarpMultiplyAdd_f32_16x16x16_16x16x16) {
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TestWarpMultiplyAddForAllLayouts<
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float,
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cutlass::Shape<16, 16, 16>,
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cutlass::Shape<16, 16, 16>
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>().run();
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}
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TEST(WmmaGemm, WarpMultiplyAdd_f32_16x16x32_16x16x16) {
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TestWarpMultiplyAddForAllLayouts<
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float,
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cutlass::Shape<16, 16, 32>,
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cutlass::Shape<16, 16, 16>
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>().run();
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}
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TEST(WmmaGemm, WarpMultiplyAdd_f32_16x32x32_16x16x16) {
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TestWarpMultiplyAddForAllLayouts<
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float,
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cutlass::Shape<16, 32, 32>,
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cutlass::Shape<16, 16, 16>
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>().run();
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}
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TEST(WmmaGemm, WarpMultiplyAdd_f32_16x32x64_16x16x16) {
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TestWarpMultiplyAddForAllLayouts<
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float,
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cutlass::Shape<16, 32, 64>,
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cutlass::Shape<16, 16, 16>
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>().run();
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////
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#endif
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