2890 lines
69 KiB
Plaintext
2890 lines
69 KiB
Plaintext
/***************************************************************************************************
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* Copyright (c) 2017-2021, 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 TORT (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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/*! \file
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\brief Unit tests for thread-level GEMM
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*/
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#include <fstream>
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#include "../../common/cutlass_unit_test.h"
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#include "cutlass/aligned_buffer.h"
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#include "cutlass/half.h"
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#include "cutlass/epilogue/thread/linear_combination.h"
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#include "cutlass/gemm/warp/mma_tensor_op_sm70.h"
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#include "cutlass/epilogue/warp/fragment_iterator_volta_tensor_op.h"
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#include "cutlass/epilogue/threadblock/default_thread_map_volta_tensor_op.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_volta_tensor_op.h"
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#include "cutlass/util/host_tensor.h"
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#include "cutlass/util/tensor_view_io.h"
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#include "cutlass/util/reference/host/tensor_fill.h"
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#include "testbed.h"
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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_Epilogue_threadblock_epilogue, f16_volta_tensor_op_64x64_32x32x4) {
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//
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// Define the warp-level matrix multiply
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//
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using Shape = cutlass::gemm::GemmShape<64, 64, 4>;
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using WarpShape = cutlass::gemm::GemmShape<32, 32, 4>;
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using ElementA = cutlass::half_t;
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using ElementB = cutlass::half_t;
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using ElementC = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
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using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
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using ElementOutput = cutlass::half_t;
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using ElementAccumulator = cutlass::half_t;
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using ElementCompute = cutlass::half_t;
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using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
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cutlass::arch::Mma<
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cutlass::gemm::GemmShape<16, 16, 4>,
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32,
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ElementA,
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cutlass::layout::ColumnMajor,
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ElementB,
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cutlass::layout::RowMajor,
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ElementC,
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cutlass::layout::RowMajor,
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cutlass::arch::OpMultiplyAdd
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>,
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cutlass::MatrixShape<1, 1>
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>;
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using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
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WarpShape,
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ElementA,
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LayoutA,
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ElementB,
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LayoutB,
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ElementC,
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cutlass::layout::RowMajor,
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Policy
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>;
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int const kPartitionsK = 1;
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int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementC>::value;
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using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
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Shape,
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WarpShape,
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kPartitionsK,
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ElementC,
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kElementsPerAccess,
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ElementAccumulator>::Type;
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//
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// Output operator
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//
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using OutputOp = cutlass::epilogue::thread::LinearCombination<
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ElementOutput,
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kElementsPerAccess,
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ElementAccumulator,
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ElementCompute
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>;
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//
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// Define the epilogue
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//
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using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
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Shape,
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WarpMmaTensorOp,
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kPartitionsK,
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OutputOp,
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kElementsPerAccess
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>::Epilogue;
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//
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// Instantiate epilogue
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//
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EpilogueTestbed<Epilogue> testbed;
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bool passed = testbed.run_all();
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EXPECT_TRUE(passed);
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}
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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_Epilogue_threadblock_epilogue, f16_volta_tensor_op_128x64_64x32x4) {
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//
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// Define the warp-level matrix multiply
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//
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using Shape = cutlass::gemm::GemmShape<128, 64, 4>;
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using WarpShape = cutlass::gemm::GemmShape<64, 32, 4>;
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using ElementA = cutlass::half_t;
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using ElementB = cutlass::half_t;
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using ElementC = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
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using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
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using ElementOutput = cutlass::half_t;
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using ElementAccumulator = cutlass::half_t;
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using ElementCompute = cutlass::half_t;
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using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
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cutlass::arch::Mma<
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cutlass::gemm::GemmShape<16, 16, 4>,
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32,
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ElementA,
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cutlass::layout::ColumnMajor,
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ElementB,
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cutlass::layout::RowMajor,
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ElementC,
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cutlass::layout::RowMajor,
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cutlass::arch::OpMultiplyAdd
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>,
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cutlass::MatrixShape<1, 1>
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>;
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using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
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WarpShape,
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ElementA,
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LayoutA,
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ElementB,
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LayoutB,
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ElementC,
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cutlass::layout::RowMajor,
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Policy
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>;
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int const kPartitionsK = 1;
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int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementC>::value;
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using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
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Shape,
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WarpShape,
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kPartitionsK,
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ElementC,
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kElementsPerAccess,
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ElementAccumulator>::Type;
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//
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// Output operator
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//
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using OutputOp = cutlass::epilogue::thread::LinearCombination<
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ElementOutput,
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kElementsPerAccess,
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ElementAccumulator,
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ElementCompute
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>;
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//
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// Define the epilogue
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//
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using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
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Shape,
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WarpMmaTensorOp,
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kPartitionsK,
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OutputOp,
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kElementsPerAccess
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>::Epilogue;
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//
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// Instantiate epilogue
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//
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EpilogueTestbed<Epilogue> testbed;
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bool passed = testbed.run_all();
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EXPECT_TRUE(passed);
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}
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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_Epilogue_threadblock_epilogue, f16_volta_tensor_op_64x128_32x64x4) {
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//
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// Define the warp-level matrix multiply
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//
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using Shape = cutlass::gemm::GemmShape<64, 128, 4>;
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using WarpShape = cutlass::gemm::GemmShape<32, 64, 4>;
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using ElementA = cutlass::half_t;
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using ElementB = cutlass::half_t;
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using ElementC = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
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using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
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using ElementOutput = cutlass::half_t;
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using ElementAccumulator = cutlass::half_t;
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using ElementCompute = cutlass::half_t;
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using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
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cutlass::arch::Mma<
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cutlass::gemm::GemmShape<16, 16, 4>,
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32,
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ElementA,
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cutlass::layout::ColumnMajor,
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ElementB,
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cutlass::layout::RowMajor,
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ElementC,
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cutlass::layout::RowMajor,
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cutlass::arch::OpMultiplyAdd
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>,
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cutlass::MatrixShape<1, 1>
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>;
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using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
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WarpShape,
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ElementA,
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LayoutA,
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ElementB,
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LayoutB,
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ElementC,
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cutlass::layout::RowMajor,
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Policy
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>;
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int const kPartitionsK = 1;
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int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementC>::value;
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using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
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Shape,
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WarpShape,
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kPartitionsK,
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ElementC,
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kElementsPerAccess,
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ElementAccumulator>::Type;
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//
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// Output operator
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//
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using OutputOp = cutlass::epilogue::thread::LinearCombination<
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ElementOutput,
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kElementsPerAccess,
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ElementAccumulator,
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ElementCompute
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>;
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//
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// Define the epilogue
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//
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using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
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Shape,
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WarpMmaTensorOp,
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kPartitionsK,
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OutputOp,
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kElementsPerAccess
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>::Epilogue;
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//
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// Instantiate epilogue
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//
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EpilogueTestbed<Epilogue> testbed;
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bool passed = testbed.run_all();
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EXPECT_TRUE(passed);
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}
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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_Epilogue_threadblock_epilogue, f16_volta_tensor_op_64x64_64x64x4) {
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//
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// Define the warp-level matrix multiply
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//
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using Shape = cutlass::gemm::GemmShape<64, 64, 4>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
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using ElementA = cutlass::half_t;
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using ElementB = cutlass::half_t;
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using ElementC = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
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using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
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using ElementOutput = cutlass::half_t;
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using ElementAccumulator = cutlass::half_t;
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using ElementCompute = cutlass::half_t;
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using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
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cutlass::arch::Mma<
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cutlass::gemm::GemmShape<16, 16, 4>,
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32,
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ElementA,
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cutlass::layout::ColumnMajor,
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ElementB,
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cutlass::layout::RowMajor,
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ElementC,
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cutlass::layout::RowMajor,
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cutlass::arch::OpMultiplyAdd
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>,
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cutlass::MatrixShape<1, 1>
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>;
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using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
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WarpShape,
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ElementA,
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LayoutA,
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ElementB,
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LayoutB,
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ElementC,
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cutlass::layout::RowMajor,
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Policy
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>;
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int const kPartitionsK = 1;
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int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementC>::value;
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using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
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Shape,
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WarpShape,
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kPartitionsK,
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ElementC,
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kElementsPerAccess,
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ElementAccumulator>::Type;
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//
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// Output operator
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//
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using OutputOp = cutlass::epilogue::thread::LinearCombination<
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ElementOutput,
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kElementsPerAccess,
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ElementAccumulator,
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ElementCompute
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>;
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//
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// Define the epilogue
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//
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using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
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Shape,
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WarpMmaTensorOp,
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kPartitionsK,
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OutputOp,
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kElementsPerAccess
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>::Epilogue;
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//
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// Instantiate epilogue
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//
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EpilogueTestbed<Epilogue> testbed;
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bool passed = testbed.run_all();
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EXPECT_TRUE(passed);
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}
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/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_Epilogue_threadblock_epilogue, f16_volta_tensor_op_64x128_64x64x4) {
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//
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// Define the warp-level matrix multiply
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//
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using Shape = cutlass::gemm::GemmShape<64, 128, 4>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
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using ElementA = cutlass::half_t;
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using ElementB = cutlass::half_t;
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using ElementC = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
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using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
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using ElementOutput = cutlass::half_t;
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using ElementAccumulator = cutlass::half_t;
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using ElementCompute = cutlass::half_t;
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using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
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cutlass::arch::Mma<
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cutlass::gemm::GemmShape<16, 16, 4>,
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32,
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ElementA,
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cutlass::layout::ColumnMajor,
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ElementB,
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cutlass::layout::RowMajor,
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ElementC,
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cutlass::layout::RowMajor,
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cutlass::arch::OpMultiplyAdd
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>,
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cutlass::MatrixShape<1, 1>
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>;
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using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
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WarpShape,
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ElementA,
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LayoutA,
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ElementB,
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LayoutB,
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ElementC,
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cutlass::layout::RowMajor,
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Policy
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>;
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int const kPartitionsK = 1;
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int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementC>::value;
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using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
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Shape,
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WarpShape,
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kPartitionsK,
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ElementC,
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kElementsPerAccess,
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ElementAccumulator>::Type;
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//
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// Output operator
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//
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using OutputOp = cutlass::epilogue::thread::LinearCombination<
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ElementOutput,
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kElementsPerAccess,
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ElementAccumulator,
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ElementCompute
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>;
|
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|
//
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// Define the epilogue
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|
//
|
|
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|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
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Shape,
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|
WarpMmaTensorOp,
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|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
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|
>::Epilogue;
|
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|
|
//
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// Instantiate epilogue
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//
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EpilogueTestbed<Epilogue> testbed;
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bool passed = testbed.run_all();
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EXPECT_TRUE(passed);
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}
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|
/////////////////////////////////////////////////////////////////////////////////////////////////
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TEST(SM70_Epilogue_threadblock_epilogue, f16_volta_tensor_op_128x64_64x64x4) {
|
|
|
|
//
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|
// Define the warp-level matrix multiply
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|
//
|
|
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|
using Shape = cutlass::gemm::GemmShape<128, 64, 4>;
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using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
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using ElementA = cutlass::half_t;
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using ElementB = cutlass::half_t;
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using ElementC = cutlass::half_t;
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using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
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using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
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|
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using ElementOutput = cutlass::half_t;
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using ElementAccumulator = cutlass::half_t;
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using ElementCompute = cutlass::half_t;
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|
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using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
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cutlass::arch::Mma<
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cutlass::gemm::GemmShape<16, 16, 4>,
|
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32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
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>,
|
|
cutlass::MatrixShape<1, 1>
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>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
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WarpShape,
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|
ElementA,
|
|
LayoutA,
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ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
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|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementC>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f16_volta_tensor_op_128x128_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<128, 128, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = cutlass::half_t;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = cutlass::half_t;
|
|
using ElementCompute = cutlass::half_t;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementC>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f16_volta_tensor_op_128x256_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<128, 256, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = cutlass::half_t;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = cutlass::half_t;
|
|
using ElementCompute = cutlass::half_t;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementC>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f16_volta_tensor_op_256x128_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<256, 128, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = cutlass::half_t;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = cutlass::half_t;
|
|
using ElementCompute = cutlass::half_t;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementC>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
//
|
|
// Mixed: F32 accumulation
|
|
//
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f16_f32_volta_tensor_op_64x64_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f16_f32_volta_tensor_op_128x256_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<128, 256, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f16_f32_volta_tensor_op_256x128_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<256, 128, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f16_f32_volta_tensor_op_128x128_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<128, 128, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f16_f32_volta_tensor_op_64x64_32x32x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<32, 32, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f16_f32_volta_tensor_op_64x128_32x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<64, 128, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<32, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f16_f32_volta_tensor_op_128x64_64x32x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<128, 64, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 32, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
//
|
|
// F32 accumulation, F32 output
|
|
//
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f32_volta_tensor_op_64x64_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = float;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f32_volta_tensor_op_64x128_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<64, 128, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = float;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f32_volta_tensor_op_128x64_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<128, 64, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = float;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f32_volta_tensor_op_128x128_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<128, 128, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = float;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f32_volta_tensor_op_128x256_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<128, 256, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = float;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f32_volta_tensor_op_256x128_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<256, 128, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = float;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f32_volta_tensor_op_64x64_32x32x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<32, 32, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = float;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f32_volta_tensor_op_128x64_64x32x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<128, 64, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 32, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = float;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, f32_volta_tensor_op_64x128_32x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<64, 128, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<32, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = float;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 128 / cutlass::sizeof_bits<ElementOutput>::value;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// This works
|
|
TEST(SM70_Epilogue_threadblock_epilogue, vec8_f16_f32_volta_tensor_op_64x64_32x32x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<32, 32, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 8;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
// This works
|
|
TEST(SM70_Epilogue_threadblock_epilogue, vec2_f16_f32_volta_tensor_op_64x64_32x32x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<32, 32, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 2;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
// This fails
|
|
TEST(SM70_Epilogue_threadblock_epilogue, vec1_f16_f32_volta_tensor_op_64x64_32x32x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<32, 32, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 1;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, vec1_f32_volta_tensor_op_128x128_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<128, 128, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = float;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 1;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, vec1_f16_f32_volta_tensor_op_128x128_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<128, 128, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 1;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
TEST(SM70_Epilogue_threadblock_epilogue, vec1_f16_f32_volta_tensor_op_128x256_64x64x4) {
|
|
|
|
//
|
|
// Define the warp-level matrix multiply
|
|
//
|
|
|
|
using Shape = cutlass::gemm::GemmShape<128, 256, 4>;
|
|
using WarpShape = cutlass::gemm::GemmShape<64, 64, 4>;
|
|
using ElementA = cutlass::half_t;
|
|
using ElementB = cutlass::half_t;
|
|
using ElementC = float;
|
|
using LayoutA = cutlass::layout::ColumnMajorVoltaTensorOpMultiplicandCongruous<cutlass::sizeof_bits<ElementA>::value>;
|
|
using LayoutB = cutlass::layout::RowMajorVoltaTensorOpMultiplicandBCongruous<cutlass::sizeof_bits<ElementB>::value>;
|
|
|
|
using ElementOutput = cutlass::half_t;
|
|
using ElementAccumulator = ElementC;
|
|
using ElementCompute = ElementC;
|
|
|
|
using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
|
|
cutlass::arch::Mma<
|
|
cutlass::gemm::GemmShape<16, 16, 4>,
|
|
32,
|
|
ElementA,
|
|
cutlass::layout::ColumnMajor,
|
|
ElementB,
|
|
cutlass::layout::RowMajor,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
cutlass::arch::OpMultiplyAdd
|
|
>,
|
|
cutlass::MatrixShape<1, 1>
|
|
>;
|
|
|
|
using WarpMmaTensorOp = cutlass::gemm::warp::MmaVoltaTensorOp<
|
|
WarpShape,
|
|
ElementA,
|
|
LayoutA,
|
|
ElementB,
|
|
LayoutB,
|
|
ElementC,
|
|
cutlass::layout::RowMajor,
|
|
Policy
|
|
>;
|
|
|
|
|
|
int const kPartitionsK = 1;
|
|
int const kElementsPerAccess = 1;
|
|
|
|
using ThreadMap = typename cutlass::epilogue::threadblock::DefaultThreadMapVoltaTensorOp<
|
|
Shape,
|
|
WarpShape,
|
|
kPartitionsK,
|
|
ElementC,
|
|
kElementsPerAccess,
|
|
ElementAccumulator>::Type;
|
|
|
|
//
|
|
// Output operator
|
|
//
|
|
|
|
using OutputOp = cutlass::epilogue::thread::LinearCombination<
|
|
ElementOutput,
|
|
kElementsPerAccess,
|
|
ElementAccumulator,
|
|
ElementCompute
|
|
>;
|
|
|
|
//
|
|
// Define the epilogue
|
|
//
|
|
|
|
using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueVoltaTensorOp<
|
|
Shape,
|
|
WarpMmaTensorOp,
|
|
kPartitionsK,
|
|
OutputOp,
|
|
kElementsPerAccess
|
|
>::Epilogue;
|
|
|
|
|
|
|
|
//
|
|
// Instantiate epilogue
|
|
//
|
|
|
|
EpilogueTestbed<Epilogue> testbed;
|
|
|
|
bool passed = testbed.run_all();
|
|
|
|
EXPECT_TRUE(passed);
|
|
}
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|