560 lines
17 KiB
C++
560 lines
17 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2017-2020, 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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/*! \file
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\brief
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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/trace.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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>
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struct GemmUniversal {
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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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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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static ComplexTransform const kTransformA = Mma::kTransformA;
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static ComplexTransform const kTransformB = Mma::kTransformB;
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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 = Mma::IteratorA::AccessType::kElements;
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static int const kAlignmentB = Mma::IteratorB::AccessType::kElements;
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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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/// Split-K preserves splits that are 128b aligned
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static int const kSplitKAlignment = const_max(128 / sizeof_bits<ElementA>::value, 128 / sizeof_bits<ElementB>::value);
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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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GemmUniversalMode mode;
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GemmCoord problem_size;
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int batch_count;
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typename EpilogueOutputOp::Params epilogue;
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void const * ptr_A;
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void const * ptr_B;
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void const * ptr_C;
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void * ptr_D;
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int64_t batch_stride_A;
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int64_t batch_stride_B;
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int64_t batch_stride_C;
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int64_t batch_stride_D;
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int lda;
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int ldb;
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int ldc;
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int ldd;
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//
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// Methods
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//
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Arguments():
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mode(GemmUniversalMode::kGemm),
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batch_count(1),
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ptr_A(nullptr), ptr_B(nullptr), ptr_C(nullptr), ptr_D(nullptr) { }
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/// constructs an arguments structure
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Arguments(
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GemmUniversalMode mode,
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GemmCoord problem_size,
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int batch_count,
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typename EpilogueOutputOp::Params epilogue,
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void const * ptr_A,
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void const * ptr_B,
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void const * ptr_C,
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void * ptr_D,
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int64_t batch_stride_A,
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int64_t batch_stride_B,
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int64_t batch_stride_C,
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int64_t batch_stride_D,
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int lda,
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int ldb,
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int ldc,
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int ldd
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):
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mode(mode),
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problem_size(problem_size),
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batch_count(batch_count),
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epilogue(epilogue),
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ptr_A(ptr_A), ptr_B(ptr_B), ptr_C(ptr_C), ptr_D(ptr_D),
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batch_stride_A(batch_stride_A), batch_stride_B(batch_stride_B), batch_stride_C(batch_stride_C), batch_stride_D(batch_stride_D),
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lda(lda), ldb(ldb), ldc(ldc), ldd(ldd) {
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CUTLASS_TRACE_HOST("GemmUniversal::Arguments::Arguments() - problem_size: " << problem_size);
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}
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/// Returns arguments for the transposed problem
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Arguments transposed_problem() const {
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Arguments args(*this);
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std::swap(args.problem_size.m(), args.problem_size.n());
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std::swap(args.ptr_A, args.ptr_B);
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std::swap(args.lda, args.ldb);
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std::swap(args.batch_stride_A, args.batch_stride_B);
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return args;
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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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cutlass::gemm::GemmCoord problem_size;
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cutlass::gemm::GemmCoord grid_tiled_shape;
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typename Mma::IteratorA::Params params_A;
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typename Mma::IteratorB::Params params_B;
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typename Epilogue::OutputTileIterator::Params params_C;
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typename Epilogue::OutputTileIterator::Params params_D;
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typename EpilogueOutputOp::Params output_op;
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GemmUniversalMode mode;
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int batch_count;
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int gemm_k_size;
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void * ptr_A;
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void * ptr_B;
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void * ptr_C;
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void * ptr_D;
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int64_t batch_stride_A;
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int64_t batch_stride_B;
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int64_t batch_stride_C;
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int64_t batch_stride_D;
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int *semaphore;
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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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params_A(0),
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params_B(0),
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params_C(0),
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params_D(0),
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batch_count(0),
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gemm_k_size(0),
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mode(cutlass::gemm::GemmUniversalMode::kGemm),
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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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batch_stride_A(0),
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batch_stride_B(0),
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batch_stride_C(0),
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batch_stride_D(0),
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semaphore(nullptr) { }
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CUTLASS_HOST_DEVICE
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Params(
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Arguments const &args,
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cutlass::gemm::GemmCoord const & grid_tiled_shape,
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int gemm_k_size,
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void *workspace = nullptr
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):
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problem_size(args.problem_size),
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grid_tiled_shape(grid_tiled_shape),
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params_A(args.lda),
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params_B(args.ldb),
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params_C(args.ldc),
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params_D(args.ldd),
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output_op(args.epilogue),
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mode(args.mode),
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batch_count(args.batch_count),
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gemm_k_size(gemm_k_size),
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ptr_A(const_cast<void *>(args.ptr_A)),
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ptr_B(const_cast<void *>(args.ptr_B)),
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ptr_C(const_cast<void *>(args.ptr_C)),
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ptr_D(args.ptr_D),
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batch_stride_A(args.batch_stride_A),
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batch_stride_B(args.batch_stride_B),
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batch_stride_C(args.batch_stride_C),
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batch_stride_D(args.batch_stride_D),
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semaphore(static_cast<int *>(workspace)) {
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CUTLASS_TRACE_HOST("GemmUniversal::Params::Params() - problem_size: " << problem_size);
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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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ptr_A = const_cast<void *>(args.ptr_A);
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ptr_B = const_cast<void *>(args.ptr_B);
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ptr_C = const_cast<void *>(args.ptr_C);
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ptr_D = args.ptr_D;
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batch_stride_A = args.batch_stride_A;
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batch_stride_B = args.batch_stride_B;
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batch_stride_C = args.batch_stride_C;
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batch_stride_D = args.batch_stride_D;
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output_op = args.epilogue;
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semaphore = static_cast<int *>(workspace);
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CUTLASS_TRACE_HOST("GemmUniversal::Params::update()");
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}
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};
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/// Shared memory storage structure
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union SharedStorage {
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typename Mma::SharedStorage main_loop;
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typename Epilogue::SharedStorage epilogue;
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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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GemmUniversal() { }
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/// Determines whether kernel satisfies alignment
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static Status can_implement(
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cutlass::gemm::GemmCoord const & problem_size) {
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CUTLASS_TRACE_HOST("GemmUniversal::can_implement()");
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static int const kAlignmentA = Mma::IteratorA::AccessType::kElements;
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static int const kAlignmentB = Mma::IteratorB::AccessType::kElements;
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static int const kAlignmentC = Epilogue::OutputTileIterator::kElementsPerAccess;
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if ((problem_size.m() % kAlignmentA) || (problem_size.k() % kAlignmentA) ||
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(problem_size.n() % kAlignmentB) || (problem_size.k() % kAlignmentB) ||
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(problem_size.m() % kAlignmentC) || (problem_size.n() % kAlignmentC)) {
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CUTLASS_TRACE_HOST(" returning kErrorMisalignedOperand");
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return Status::kErrorMisalignedOperand;
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}
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CUTLASS_TRACE_HOST(" returning kSuccess");
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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 can_implement(args.problem_size);
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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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// Compute threadblock location
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ThreadblockSwizzle threadblock_swizzle;
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cutlass::gemm::GemmCoord threadblock_tile_offset =
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threadblock_swizzle.get_tile_offset(params.grid_tiled_shape);
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// Early exit if CTA is out of range
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if (params.grid_tiled_shape.m() <= threadblock_tile_offset.m() ||
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params.grid_tiled_shape.n() <= threadblock_tile_offset.n()) {
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return;
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}
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int offset_k = 0;
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int problem_size_k = params.problem_size.k();
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ElementA *ptr_A = static_cast<ElementA *>(params.ptr_A);
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ElementB *ptr_B = static_cast<ElementB *>(params.ptr_B);
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//
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// Fetch pointers based on mode.
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//
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if (params.mode == GemmUniversalMode::kGemm ||
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params.mode == GemmUniversalMode::kGemmSplitKParallel) {
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if (threadblock_tile_offset.k() + 1 < params.grid_tiled_shape.k()) {
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problem_size_k = (threadblock_tile_offset.k() + 1) * params.gemm_k_size;
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}
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offset_k = threadblock_tile_offset.k() * params.gemm_k_size;
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}
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else if (params.mode == GemmUniversalMode::kBatched) {
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ptr_A += threadblock_tile_offset.k() * params.batch_stride_A;
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ptr_B += threadblock_tile_offset.k() * params.batch_stride_B;
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}
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else if (params.mode == GemmUniversalMode::kArray) {
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ptr_A = static_cast<ElementA * const *>(params.ptr_A)[threadblock_tile_offset.k()];
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ptr_B = static_cast<ElementB * const *>(params.ptr_B)[threadblock_tile_offset.k()];
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}
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__syncthreads();
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// Compute initial location in logical coordinates
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cutlass::MatrixCoord tb_offset_A{
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threadblock_tile_offset.m() * Mma::Shape::kM,
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offset_k,
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};
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cutlass::MatrixCoord tb_offset_B{
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offset_k,
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threadblock_tile_offset.n() * Mma::Shape::kN
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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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params.params_A,
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ptr_A,
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{params.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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params.params_B,
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ptr_B,
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{problem_size_k, params.problem_size.n()},
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thread_idx,
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tb_offset_B);
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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 = __shfl_sync(0xffffffff, threadIdx.x / 32, 0);
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int lane_idx = threadIdx.x % 32;
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//
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// Main loop
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//
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// Construct thread-scoped matrix multiply
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Mma mma(shared_storage.main_loop, thread_idx, warp_idx, lane_idx);
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typename Mma::FragmentC accumulators;
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accumulators.clear();
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// Compute threadblock-scoped matrix multiply-add
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int gemm_k_iterations = (problem_size_k - offset_k + Mma::Shape::kK - 1) / Mma::Shape::kK;
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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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//
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// Masked tile iterators constructed from members
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//
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threadblock_tile_offset =
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threadblock_swizzle.get_tile_offset(params.grid_tiled_shape);
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//assume identity swizzle
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MatrixCoord threadblock_offset(
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threadblock_tile_offset.m() * Mma::Shape::kM,
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threadblock_tile_offset.n() * Mma::Shape::kN
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);
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int block_idx = threadblock_tile_offset.m() + threadblock_tile_offset.n() * params.grid_tiled_shape.m();
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ElementC *ptr_C = static_cast<ElementC *>(params.ptr_C);
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ElementC *ptr_D = static_cast<ElementC *>(params.ptr_D);
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//
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// Fetch pointers based on mode.
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//
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// Construct the semaphore.
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Semaphore semaphore(params.semaphore + block_idx, thread_idx);
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if (params.mode == GemmUniversalMode::kGemm) {
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// If performing a reduction via split-K, fetch the initial synchronization
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if (params.grid_tiled_shape.k() > 1) {
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// Fetch the synchronization lock initially but do not block.
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semaphore.fetch();
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// Indicate which position in a serial reduction the output operator is currently updating
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output_op.set_k_partition(threadblock_tile_offset.k());
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}
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}
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else if (params.mode == GemmUniversalMode::kGemmSplitKParallel) {
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ptr_D += threadblock_tile_offset.k() * params.batch_stride_D;
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}
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else if (params.mode == GemmUniversalMode::kBatched) {
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ptr_C += threadblock_tile_offset.k() * params.batch_stride_C;
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ptr_D += threadblock_tile_offset.k() * params.batch_stride_D;
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}
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else if (params.mode == GemmUniversalMode::kArray) {
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ptr_C = static_cast<ElementC * const *>(params.ptr_C)[threadblock_tile_offset.k()];
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ptr_D = static_cast<ElementC * const *>(params.ptr_D)[threadblock_tile_offset.k()];
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}
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// Tile iterator loading from source tensor.
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typename Epilogue::OutputTileIterator iterator_C(
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params.params_C,
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ptr_C,
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params.problem_size.mn(),
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thread_idx,
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threadblock_offset
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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.params_D,
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ptr_D,
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params.problem_size.mn(),
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thread_idx,
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threadblock_offset
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);
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Epilogue epilogue(
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shared_storage.epilogue,
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thread_idx,
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warp_idx,
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lane_idx);
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// Wait on the semaphore - this latency may have been covered by iterator construction
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if (params.mode == GemmUniversalMode::kGemm && params.grid_tiled_shape.k() > 1) {
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// For subsequent threadblocks, the source matrix is held in the 'D' tensor.
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if (threadblock_tile_offset.k()) {
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iterator_C = iterator_D;
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}
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semaphore.wait(threadblock_tile_offset.k());
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__threadfence();
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}
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|
|
|
|
// Execute the epilogue operator to update the destination tensor.
|
|
epilogue(
|
|
output_op,
|
|
iterator_D,
|
|
accumulators,
|
|
iterator_C);
|
|
|
|
//
|
|
// Release the semaphore
|
|
//
|
|
|
|
if (params.mode == GemmUniversalMode::kGemm && params.grid_tiled_shape.k() > 1) {
|
|
|
|
int lock = 0;
|
|
if (params.grid_tiled_shape.k() == threadblock_tile_offset.k() + 1) {
|
|
|
|
// The final threadblock resets the semaphore for subsequent grids.
|
|
lock = 0;
|
|
}
|
|
else {
|
|
// Otherwise, the semaphore is incremented
|
|
lock = threadblock_tile_offset.k() + 1;
|
|
}
|
|
|
|
semaphore.release(lock);
|
|
}
|
|
}
|
|
};
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
} // namespace kernel
|
|
} // namespace gemm
|
|
} // namespace cutlass
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|