149 lines
5.8 KiB
C++
149 lines
5.8 KiB
C++
/***************************************************************************************************
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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 TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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**************************************************************************************************/
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/***************************************************************************************************
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* Copyright (c) 2021 Iluvatar CoreX. All rights reserved.
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* Copyright Declaration: This software, including all of its code and documentation,
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* except for the third-party software it contains, is a copyrighted work of Shanghai Iluvatar CoreX
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* Semiconductor Co., Ltd. and its affiliates ("Iluvatar CoreX") in accordance with the PRC Copyright
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* Law and relevant international treaties, and all rights contained therein are enjoyed by Iluvatar
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* CoreX. No user of this software shall have any right, ownership or interest in this software and
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* any use of this software shall be in compliance with the terms and conditions of the End User
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* License Agreement.
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**************************************************************************************************/
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/*! \file
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\brief Default warp-level GEMM operators selected by data type, size, and layouts of operands.
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*/
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#pragma once
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#include "cutlass/cutlass.h"
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#include "cutlass/gemm/warp/mma_tensor_op.h"
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namespace cutlass {
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namespace gemm {
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namespace warp {
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/////////////////////////////////////////////////////////////////////////////////////////////////
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template <
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/// Size of the Gemm problem - concept: gemm::GemmShape<>
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typename WarpShape_,
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/// Shape of one matrix production operation (concept: GemmShape)
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typename InstructionShape_,
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/// Data type of A elements
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typename ElementA_,
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/// Layout of A matrix (concept: MatrixLayout)
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typename LayoutA_,
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/// Data type of B elements
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typename ElementB_,
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/// Layout of B matrix (concept: MatrixLayout)
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typename LayoutB_,
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/// Element type of C matrix
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typename ElementC_,
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/// Layout of C matrix (concept: MatrixLayout)
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typename LayoutC_,
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/// Operator describing the tensor operation
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typename Operator_ = arch::OpMultiplyAdd,
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/// Number of partitions along K dimension
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int PartitionsK = 1,
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/// Store the accumulators in row major or column major.
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bool AccumulatorsInRowMajor = true>
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struct DefaultMmaTensorOp;
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// Partial specialization for m-by-n-by-kgroup
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template <
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/// Shape of one matrix production operation (concept: GemmShape)
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typename WarpShape_,
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/// Data type of A elements
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typename ElementA,
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/// Layout of A matrix (concept: MatrixLayout)
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typename LayoutA,
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/// Data type of B elements
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typename ElementB,
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/// Layout of B matrix (concept: MatrixLayout)
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typename LayoutB,
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/// Element type of C matrix
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typename ElementC,
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/// Layout of C matrix (concept: MatrixLayout)
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typename LayoutC,
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/// Number of partitions along K dimension
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int PartitionsK,
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/// Store the accumulators in row major or column major.
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bool AccumulatorsInRowMajor>
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struct DefaultMmaTensorOp<
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WarpShape_,
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GemmShape<16, 16, 16>,
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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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LayoutC,
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arch::OpMultiplyAdd,
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PartitionsK,
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AccumulatorsInRowMajor> {
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/// Warp shape
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using Shape = WarpShape_;
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using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
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cutlass::arch::Mma<GemmShape<16, 16, 16>,
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64,
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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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LayoutC,
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arch::OpMultiplyAdd>,
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cutlass::MatrixShape<1, 1> >;
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// Define the warp-level tensor op
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using Type = cutlass::gemm::warp::MmaTensorOp<
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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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LayoutC,
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Policy,
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PartitionsK,
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AccumulatorsInRowMajor>;
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};
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/////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace warp
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} // namespace gemm
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} // namespace cutlass
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/////////////////////////////////////////////////////////////////////////////////////////////////
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