482 lines
14 KiB
C++
482 lines
14 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2017 - 2023 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 Problem visitor for grouped GEMMs
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*/
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#pragma once
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#include "cutlass/cutlass.h"
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#include "cutlass/fast_math.h"
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#include "cutlass/gemm/gemm.h"
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#include "cutlass/matrix_coord.h"
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#include "cutlass/complex.h"
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#include "cutlass/semaphore.h"
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#include "cutlass/layout/matrix.h"
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#include "cutlass/trace.h"
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#include "cutlass/gemm/kernel/gemm_transpose_operands.h"
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#include "cutlass/gemm/kernel/gemm_grouped_problem_visitor.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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typename Mma_, ///! Threadblock-scoped matrix multiply-accumulate
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typename Epilogue_, ///! Epilogue
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typename ThreadblockSwizzle_, ///! Threadblock swizzling function
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GroupScheduleMode GroupScheduleMode_, ///! Type of scheduling to perform
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bool Transposed = false
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>
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struct GemmGrouped {
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public:
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using Mma = Mma_;
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using Epilogue = Epilogue_;
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using EpilogueOutputOp = typename Epilogue::OutputOp;
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using ThreadblockSwizzle = ThreadblockSwizzle_;
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static GroupScheduleMode const kGroupScheduleMode = GroupScheduleMode_;
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static bool const kTransposed = Transposed;
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// Optional transpose
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using MapArguments = kernel::detail::MapArguments<
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typename Mma::IteratorA::Element,
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typename Mma::IteratorA::Layout,
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Mma::kTransformA,
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Mma::IteratorA::AccessType::kElements,
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typename Mma::IteratorB::Element,
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typename Mma::IteratorB::Layout,
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Mma::kTransformB,
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Mma::IteratorB::AccessType::kElements,
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typename Mma::LayoutC,
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kTransposed
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>;
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// Public-facing type definitions related to operand element type, layout, and complex conjugate
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// operation. Must interact with the 'kTransposed' notion.
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using ElementA = typename MapArguments::ElementA;
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using LayoutA = typename MapArguments::LayoutA;
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using ElementB = typename MapArguments::ElementB;
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using LayoutB = typename MapArguments::LayoutB;
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using ElementC = typename Epilogue::OutputTileIterator::Element;
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using LayoutC = typename MapArguments::LayoutC;
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static ComplexTransform const kTransformA = MapArguments::kTransformA;
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static ComplexTransform const kTransformB = MapArguments::kTransformB;
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// Type definitions about the mainloop.
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using Operator = typename Mma::Operator;
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using OperatorClass = typename Mma::Operator::OperatorClass;
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using ThreadblockShape = typename Mma::Shape;
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using WarpShape = typename Mma::Operator::Shape;
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using InstructionShape = typename Mma::Policy::Operator::InstructionShape;
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using ArchTag = typename Mma::ArchTag;
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static int const kStages = Mma::kStages;
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static int const kAlignmentA = MapArguments::kAlignmentA;
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static int const kAlignmentB = MapArguments::kAlignmentB;
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static int const kAlignmentC = Epilogue::OutputTileIterator::kElementsPerAccess;
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/// Warp count (concept: GemmShape)
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using WarpCount = typename Mma::WarpCount;
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static int const kThreadCount = 32 * WarpCount::kCount;
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using ProblemVisitor = GemmGroupedProblemVisitor<
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ThreadblockShape,
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kGroupScheduleMode,
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kThreadCount,
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kThreadCount,
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kTransposed>;
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//
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// Structures
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//
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/// Argument structure
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struct Arguments {
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//
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// Data members
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//
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GemmCoord *problem_sizes;
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int problem_count;
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int threadblock_count;
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typename EpilogueOutputOp::Params output_op;
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ElementA ** ptr_A;
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ElementB ** ptr_B;
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ElementC ** ptr_C;
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ElementC ** ptr_D;
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typename LayoutA::Stride::LongIndex *lda;
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typename LayoutB::Stride::LongIndex *ldb;
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typename LayoutC::Stride::LongIndex *ldc;
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typename LayoutC::Stride::LongIndex *ldd;
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// Only used by device-level operator
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GemmCoord *host_problem_sizes;
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//
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// Methods
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//
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/// Default ctor
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CUTLASS_HOST_DEVICE
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Arguments():
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problem_count(0),
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threadblock_count(0),
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ptr_A(nullptr),
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ptr_B(nullptr),
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ptr_C(nullptr),
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ptr_D(nullptr),
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lda(nullptr),
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ldb(nullptr),
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ldc(nullptr),
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ldd(nullptr),
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host_problem_sizes(nullptr)
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{
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}
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/// Ctor
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CUTLASS_HOST_DEVICE
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Arguments(
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GemmCoord *problem_sizes,
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int problem_count,
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int threadblock_count,
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typename EpilogueOutputOp::Params output_op,
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ElementA ** ptr_A,
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ElementB ** ptr_B,
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ElementC ** ptr_C,
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ElementC ** ptr_D,
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typename LayoutA::Stride::LongIndex *lda,
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typename LayoutB::Stride::LongIndex *ldb,
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typename LayoutC::Stride::LongIndex *ldc,
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typename LayoutC::Stride::LongIndex *ldd,
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GemmCoord *host_problem_sizes=nullptr
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):
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problem_sizes(problem_sizes),
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problem_count(problem_count),
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threadblock_count(threadblock_count),
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output_op(output_op),
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ptr_A(ptr_A),
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ptr_B(ptr_B),
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ptr_C(ptr_C),
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ptr_D(ptr_D),
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lda(lda),
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ldb(ldb),
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ldc(ldc),
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ldd(ldd),
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host_problem_sizes(host_problem_sizes)
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{
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}
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};
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//
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// Structure for precomputing values in host memory and passing to kernels
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//
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/// Parameters structure
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struct Params {
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typename ProblemVisitor::Params problem_visitor;
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int threadblock_count;
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typename EpilogueOutputOp::Params output_op;
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ElementA ** ptr_A;
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ElementB ** ptr_B;
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ElementC ** ptr_C;
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ElementC ** ptr_D;
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typename LayoutA::Stride::LongIndex *lda;
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typename LayoutB::Stride::LongIndex *ldb;
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typename LayoutC::Stride::LongIndex *ldc;
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typename LayoutC::Stride::LongIndex *ldd;
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//
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// Methods
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//
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CUTLASS_HOST_DEVICE
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Params():
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ptr_A(nullptr),
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ptr_B(nullptr),
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ptr_C(nullptr),
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ptr_D(nullptr),
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lda(nullptr),
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ldb(nullptr),
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ldc(nullptr),
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ldd(nullptr)
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{ }
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CUTLASS_HOST_DEVICE
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Params(Arguments const &args,
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void *workspace = nullptr,
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int tile_count = 0):
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problem_visitor(args.problem_sizes, args.problem_count, workspace, tile_count),
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threadblock_count(args.threadblock_count),
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output_op(args.output_op),
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ptr_A(args.ptr_A),
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ptr_B(args.ptr_B),
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ptr_C(args.ptr_C),
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ptr_D(args.ptr_D),
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lda(args.lda),
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ldb(args.ldb),
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ldc(args.ldc),
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ldd(args.ldd)
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{
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}
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CUTLASS_HOST_DEVICE
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void update(
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Arguments const &args,
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void *workspace = nullptr,
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int tile_count = 0) {
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problem_visitor = typename ProblemVisitor::Params(args.problem_sizes, args.problem_count,
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workspace, tile_count);
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threadblock_count = args.threadblock_count;
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output_op = args.output_op;
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ptr_A = args.ptr_A;
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ptr_B = args.ptr_B;
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ptr_C = args.ptr_C;
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ptr_D = args.ptr_D;
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lda = args.lda;
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ldb = args.ldb;
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ldc = args.ldc;
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ldd = args.ldd;
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}
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};
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/// Shared memory storage structure
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struct SharedStorage {
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union {
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typename Mma::SharedStorage main_loop;
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typename Epilogue::SharedStorage epilogue;
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} kernel;
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// ProblemVisitor shared storage can't be overlapped with others
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typename ProblemVisitor::SharedStorage problem_visitor;
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};
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public:
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//
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// Methods
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//
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CUTLASS_DEVICE
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GemmGrouped() { }
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/// Determines whether kernel satisfies alignment
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static Status can_implement(cutlass::gemm::GemmCoord const & problem_size) {
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return Status::kSuccess;
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}
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static Status can_implement(Arguments const &args) {
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return Status::kSuccess;
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}
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/// Executes one GEMM
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CUTLASS_DEVICE
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void operator()(Params const ¶ms, SharedStorage &shared_storage) {
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//
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// These types shadow the type-level definitions and support the ability to implement
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// a 'transposed' GEMM that computes the transposed problems.
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//
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using ElementA = typename Mma::IteratorA::Element;
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using LayoutA = typename Mma::IteratorA::Layout;
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using ElementB = typename Mma::IteratorB::Element;
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using LayoutB = typename Mma::IteratorB::Layout;
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using ElementC = typename Epilogue::OutputTileIterator::Element;
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using LayoutC = typename Epilogue::OutputTileIterator::Layout;
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//
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// Problem visitor.
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//
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ProblemVisitor problem_visitor(
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params.problem_visitor,
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shared_storage.problem_visitor,
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blockIdx.x);
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// Outer 'persistent' loop to iterate over tiles
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while (problem_visitor.next_tile()) {
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GemmCoord problem_size = problem_visitor.problem_size();
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int32_t problem_idx = problem_visitor.problem_index();
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int32_t threadblock_idx = int32_t(problem_visitor.threadblock_idx());
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GemmCoord grid_shape = problem_visitor.grid_shape(problem_size);
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cutlass::gemm::GemmCoord threadblock_offset(
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int(threadblock_idx / grid_shape.n()) * Mma::Shape::kM,
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int(threadblock_idx % grid_shape.n()) * Mma::Shape::kN,
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0);
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// Load element pointers. Exchange pointers and strides if working on the transpose
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ElementA *ptr_A = reinterpret_cast<ElementA *>((kTransposed ? params.ptr_B[problem_idx] : params.ptr_A[problem_idx]));
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typename LayoutA::LongIndex ldm_A = (kTransposed ? params.ldb[problem_idx] : params.lda[problem_idx]);
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ElementB *ptr_B = reinterpret_cast<ElementB *>((kTransposed ? params.ptr_A[problem_idx] : params.ptr_B[problem_idx]));
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typename LayoutB::LongIndex ldm_B = (kTransposed ? params.lda[problem_idx] : params.ldb[problem_idx]);
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// Compute initial location in logical coordinates
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cutlass::MatrixCoord tb_offset_A{
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threadblock_offset.m(),
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0,
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};
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cutlass::MatrixCoord tb_offset_B{
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0,
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threadblock_offset.n()
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};
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// Compute position within threadblock
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int thread_idx = threadIdx.x;
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// Construct iterators to A and B operands
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typename Mma::IteratorA iterator_A(
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LayoutA(ldm_A),
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ptr_A,
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{problem_size.m(), problem_size.k()},
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thread_idx,
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tb_offset_A);
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typename Mma::IteratorB iterator_B(
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LayoutB(ldm_B),
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ptr_B,
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{problem_size.k(), problem_size.n()},
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thread_idx,
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tb_offset_B);
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typename Mma::FragmentC accumulators;
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accumulators.clear();
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// Broadcast the warp_id computed by lane 0 to ensure dependent code
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// is compiled as warp-uniform.
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int warp_idx = canonical_warp_idx();
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int lane_idx = threadIdx.x % 32;
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//
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// Matrix multiply phase
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//
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// Construct thread-scoped matrix multiply
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Mma mma(shared_storage.kernel.main_loop, thread_idx, warp_idx, lane_idx);
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// Compute threadblock-scoped matrix multiply-add
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int gemm_k_iterations = (problem_size.k() + Mma::Shape::kK - 1) / Mma::Shape::kK;
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// Wait for all threads to finish their epilogue phases from the previous tile.
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__syncthreads();
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// Compute threadblock-scoped matrix multiply-add
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mma(
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gemm_k_iterations,
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accumulators,
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iterator_A,
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iterator_B,
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accumulators);
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//
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// Epilogue
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//
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EpilogueOutputOp output_op(params.output_op);
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ElementC *ptr_C = params.ptr_C[problem_idx];
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ElementC *ptr_D = params.ptr_D[problem_idx];
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LayoutC layout_C(params.ldc[problem_idx]);
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LayoutC layout_D(params.ldd[problem_idx]);
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typename Epilogue::OutputTileIterator::Params params_C(layout_C);
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typename Epilogue::OutputTileIterator::Params params_D(layout_D);
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// Tile iterator loading from source tensor.
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typename Epilogue::OutputTileIterator iterator_C(
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params_C,
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ptr_C,
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problem_size.mn(),
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thread_idx,
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threadblock_offset.mn()
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);
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// Tile iterator writing to destination tensor.
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typename Epilogue::OutputTileIterator iterator_D(
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params_D,
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ptr_D,
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problem_size.mn(),
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thread_idx,
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threadblock_offset.mn()
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);
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Epilogue epilogue(
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shared_storage.kernel.epilogue,
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thread_idx,
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warp_idx,
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lane_idx);
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// Execute the epilogue operator to update the destination tensor.
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epilogue(
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output_op,
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iterator_D,
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accumulators,
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iterator_C);
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// Next tile
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problem_visitor.advance(gridDim.x);
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}
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}
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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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/////////////////////////////////////////////////////////////////////////////////////////////////
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