data: Cu10 CUTLASS headers from corex-samples
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cat_files/default_gemm.h
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383
cat_files/default_gemm.h
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/***************************************************************************************************
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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
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Default kernel-level GEMM definitions combine threadblock-scoped matrix multiply-add with
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the appropriate threadblock-scoped epilogue.
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Note, CUTLASS epilogues universally target row-major outputs. Column-major outputs are
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accommodated by exchanging A and B operands and assuming transposed layouts. Partial
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specializations here choose 'device::GemmTransposed' to implement this functionality.
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*/
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#pragma once
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#include "cutlass/cutlass.h"
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#include "cutlass/layout/matrix.h"
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#include "cutlass/numeric_types.h"
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#include "cutlass/arch/mma.h"
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#include "cutlass/epilogue/threadblock/epilogue.h"
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#include "cutlass/epilogue/thread/linear_combination.h"
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#include "cutlass/gemm/gemm.h"
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#include "cutlass/gemm/kernel/gemm.h"
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#include "cutlass/gemm/kernel/gemm_pipelined.h"
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#include "cutlass/gemm/threadblock/default_mma.h"
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#include "cutlass/gemm/threadblock/default_mma_core_simt.h"
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#include "cutlass/gemm/threadblock/threadblock_swizzle.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_simt.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_tensor_op.h"
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#include "cutlass/transform/threadblock/predicated_tile_iterator.h"
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////////////////////////////////////////////////////////////////////////////////
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namespace cutlass {
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namespace gemm {
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namespace kernel {
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////////////////////////////////////////////////////////////////////////////////
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template <
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/// Element type for A matrix operand
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typename ElementA_,
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/// Layout type for A matrix operand
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typename LayoutA_,
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/// Access granularity of A matrix in units of elements
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int kAlignmentA,
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/// Element type for B matrix operand
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typename ElementB_,
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/// Layout type for B matrix operand
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typename LayoutB_,
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/// Access granularity of B matrix in units of elements
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int kAlignmentB,
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/// Element type for C and D matrix operands
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typename ElementC_,
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/// Layout type for C and D matrix operands
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typename LayoutC_,
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/// Element type for internal accumulation
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typename ElementAccumulator,
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/// Operator class tag
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typename OperatorClass,
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/// Tag indicating architecture to tune for
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typename ArchTag,
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/// Threadblock-level tile size (concept: GemmShape)
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typename ThreadblockShape,
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/// Warp-level tile size (concept: GemmShape)
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typename WarpShape,
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/// Warp-level tile size (concept: GemmShape)
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typename InstructionShape,
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/// Epilogue output operator
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typename EpilogueOutputOp,
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/// Threadblock-level swizzling operator
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typename ThreadblockSwizzle,
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/// Number of stages used in the pipelined mainloop
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int Stages,
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/// If true, kernel is configured to support serial reduction in the
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/// epilogue
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bool SplitKSerial,
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/// Operation performed by GEMM
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typename Operator>
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struct DefaultGemm;
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////////////////////////////////////////////////////////////////////////////////
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/// Partial specialization for SIMT
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template <
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/// Element type for A matrix operand
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typename ElementA,
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/// Layout type for A matrix operand
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typename LayoutA,
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/// Access granularity of A matrix in units of elements
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int kAlignmentA,
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/// Element type for B matrix operand
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typename ElementB,
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/// Layout type for B matrix operand
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typename LayoutB,
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/// Access granularity of A matrix in units of elements
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int kAlignmentB,
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/// Element type for C and D matrix operands
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typename ElementC,
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/// Element type for internal accumulation
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typename ElementAccumulator,
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/// Tag indicating architecture to tune for
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typename ArchTag,
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/// Threadblock-level tile size (concept: GemmShape)
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typename ThreadblockShape,
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/// Warp-level tile size (concept: GemmShape)
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typename WarpShape,
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/// Epilogue output operator
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typename EpilogueOutputOp,
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/// Threadblock-level swizzling operator
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typename ThreadblockSwizzle,
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/// If true, kernel is configured to support serial reduction in the epilogue
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bool SplitKSerial,
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/// Operation performed by GEMM
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typename Operator
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>
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struct DefaultGemm<
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ElementA,
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LayoutA,
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kAlignmentA,
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ElementB,
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LayoutB,
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kAlignmentB,
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ElementC,
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layout::RowMajor,
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ElementAccumulator,
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arch::OpClassSimt,
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ArchTag,
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ThreadblockShape,
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WarpShape,
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GemmShape<1, 1, 1>,
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EpilogueOutputOp,
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ThreadblockSwizzle,
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2,
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SplitKSerial,
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Operator> {
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/// Define the threadblock-scoped matrix multiply-accumulate
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using Mma = typename cutlass::gemm::threadblock::DefaultMma<
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ElementA,
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LayoutA,
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kAlignmentA,
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ElementB,
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LayoutB,
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kAlignmentB,
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ElementAccumulator,
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layout::RowMajor,
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arch::OpClassSimt,
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arch::Sm50,
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ThreadblockShape,
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WarpShape,
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GemmShape<1, 1, 1>,
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2,
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Operator>::ThreadblockMma;
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static int const kEpilogueElementsPerAccess = EpilogueOutputOp::kCount;
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static_assert(kEpilogueElementsPerAccess == 1, "simt epilogue must operate on scalars");
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/// Define the epilogue
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using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueSimt<
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ThreadblockShape,
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typename Mma::Operator,
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EpilogueOutputOp,
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kEpilogueElementsPerAccess
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>::Epilogue;
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/// Define the kernel-level GEMM operator.
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using GemmKernel = kernel::Gemm<Mma, Epilogue, ThreadblockSwizzle, SplitKSerial>;
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};
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////////////////////////////////////////////////////////////////////////////////
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/// Partial specialization for SIMT DP4A
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template <
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/// Layout type for A matrix operand
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typename LayoutA,
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/// Access granularity of A matrix in units of elements
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int kAlignmentA,
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/// Layout type for B matrix operand
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typename LayoutB,
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/// Access granularity of A matrix in units of elements
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int kAlignmentB,
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/// Layout type for C matrix operand
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typename LayoutC,
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/// Element type for C and D matrix operands
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typename ElementC,
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/// Tag indicating architecture to tune for
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typename ArchTag,
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/// Element type for internal accumulation
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typename ElementAccumulator,
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/// Threadblock-level tile size (concept: GemmShape)
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typename ThreadblockShape,
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/// Warp-level tile size (concept: GemmShape)
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typename WarpShape,
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/// Epilogue output operator
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typename EpilogueOutputOp,
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/// Threadblock-level swizzling operator
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typename ThreadblockSwizzle,
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/// If true, kernel is configured to support serial reduction in the
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/// epilogue
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bool SplitKSerial,
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/// Operation performed by GEMM
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typename Operator>
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struct DefaultGemm<int8_t, LayoutA, kAlignmentA, int8_t, LayoutB, kAlignmentB,
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ElementC, LayoutC, ElementAccumulator, arch::OpClassSimt,
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ArchTag, ThreadblockShape, WarpShape, GemmShape<1, 1, 4>,
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EpilogueOutputOp, ThreadblockSwizzle, 2, SplitKSerial,
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Operator> {
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using InstructionShape = GemmShape<1, 1, 4>;
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using ElementA = int8_t;
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using ElementB = int8_t;
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using OperatorClass = arch::OpClassSimt;
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/// Define the threadblock-scoped matrix multiply-accumulate
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using Mma = typename cutlass::gemm::threadblock::DefaultMma<ElementA,
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LayoutA,
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kAlignmentA,
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ElementB,
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LayoutB,
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kAlignmentB,
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ElementAccumulator,
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LayoutC,
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arch::OpClassSimt,
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arch::Sm50,
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ThreadblockShape,
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WarpShape,
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InstructionShape,
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2,
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Operator,
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false
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>::ThreadblockMma;
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static int const kEpilogueElementsPerAccess = EpilogueOutputOp::kCount;
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static_assert(kEpilogueElementsPerAccess == 1, "simt epilogue must operate on scalars");
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/// Define the epilogue
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using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueSimt<
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ThreadblockShape,
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typename Mma::Operator,
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EpilogueOutputOp,
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kEpilogueElementsPerAccess
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>::Epilogue;
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/// Define the kernel-level GEMM operator.
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using GemmKernel = kernel::Gemm<Mma, Epilogue, ThreadblockSwizzle, SplitKSerial>;
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};
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////////////////////////////////////////////////////////////////////////////////
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/// Partial specialization for BigIsland 1.0 tensor op architecture
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template <
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/// Element type for A matrix operand
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typename ElementA,
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/// Layout type for A matrix operand
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typename LayoutA,
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/// Access granularity of A matrix in units of elements
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int kAlignmentA,
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/// Element type for B matrix operand
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typename ElementB,
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/// Layout type for B matrix operand
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typename LayoutB,
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/// Access granularity of B matrix in units of elements
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int kAlignmentB,
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/// Element type for C and D matrix operands
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typename ElementC,
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/// Element type for internal accumulation
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typename ElementAccumulator,
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/// Tag indicating architecture to tune for
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typename ArchTag,
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/// Threadblock-level tile size (concept: GemmShape)
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typename ThreadblockShape,
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/// Warp-level tile size (concept: GemmShape)
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typename WarpShape,
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/// Instrcution shape
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typename InstructionShape,
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/// Epilogue output operator
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typename EpilogueOutputOp,
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/// Threadblock-level swizzling operator
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typename ThreadblockSwizzle,
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/// Number of stages used in the pipelined mainloop
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int Stages,
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/// If true, kernel is configured to support serial reduction in the epilogue
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bool SplitKSerial,
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/// Operation performed by GEMM
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typename Operator
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>
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struct DefaultGemm<
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ElementA, LayoutA, kAlignmentA,
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ElementB, LayoutB, kAlignmentB,
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ElementC, layout::RowMajor,
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ElementAccumulator,
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arch::OpClassTensorOp,
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ArchTag,
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ThreadblockShape,
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WarpShape,
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InstructionShape,
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EpilogueOutputOp,
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ThreadblockSwizzle,
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Stages,
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SplitKSerial,
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Operator
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> {
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/// Define the threadblock-scoped matrix multiply-accumulate
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using Mma = typename cutlass::gemm::threadblock::DefaultMma<
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ElementA,
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LayoutA,
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kAlignmentA,
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ElementB,
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LayoutB,
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kAlignmentB,
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ElementAccumulator,
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layout::RowMajor,
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arch::OpClassTensorOp,
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ArchTag,
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ThreadblockShape,
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WarpShape,
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InstructionShape,
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Stages,
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Operator
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>::ThreadblockMma;
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static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK;
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/// FIXME(Peter Han): Probably DefaultEpiloguesTensorOp should be used here, let's see
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static const int kEpilougeElementsPerAccess = EpilogueOutputOp::kCount;
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/// Define the epilogue
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using Epilogue = typename cutlass::epilogue::threadblock::DefaultEpilogueTensorOp<
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ThreadblockShape,
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typename Mma::Operator,
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EpilogueOutputOp,
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kEpilougeElementsPerAccess
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>::Epilogue;
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/// Define the kernel-level GEMM operator.
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using GemmKernel = kernel::Gemm<Mma, Epilogue, ThreadblockSwizzle, SplitKSerial>;
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};
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////////////////////////////////////////////////////////////////////////////////
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} // namespace kernel
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} // namespace gemm
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} // namespace cutlass
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