124 lines
5.1 KiB
C++
124 lines
5.1 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2017 - 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* SPDX-License-Identifier: BSD-3-Clause
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice, this
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* list of conditions and the following disclaimer.
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*
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* 3. Neither the name of the copyright holder nor the names of its
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* contributors may be used to endorse or promote products derived from
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* this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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* 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 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. Row major is used
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/// when output layout is interleaved.
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bool AccumulatorsInRowMajor = false>
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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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/// 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_,
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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. Row major is used
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/// when output layout is interleaved.
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bool AccumulatorsInRowMajor>
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struct DefaultMmaTensorOp {
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using Policy = cutlass::gemm::warp::MmaTensorOpPolicy<
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cutlass::arch::Mma<InstructionShape_, 32, ElementA,
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cutlass::layout::RowMajor, ElementB,
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cutlass::layout::ColumnMajor, ElementC,
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cutlass::layout::RowMajor, Operator_>,
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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_, ElementA, LayoutA, ElementB, LayoutB, ElementC, LayoutC,
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Policy, PartitionsK, 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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#include "cutlass/gemm/warp/default_mma_tensor_op_sm80.h"
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/////////////////////////////////////////////////////////////////////////////////////////////////
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