877bdcace6
CUTLASS 1.3 Release - Efficient GEMM kernel targeting Volta Tensor Cores via mma.sync instruction added in CUDA 10.1.
146 lines
6.1 KiB
C++
146 lines
6.1 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2017-2019, 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 Defines properties of GEMM computation that impose some constraints on caller.
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*/
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#pragma once
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#include "cutlass/shape.h"
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namespace cutlass {
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namespace gemm {
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////////////////////////////////////////////////////////////////////////////////////////////////////
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template <
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/// The scalar type for A.
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typename ScalarA_,
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/// The scalar type for B.
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typename ScalarB_,
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/// The scalar type for C.
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typename ScalarC_,
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/// The scalar type for D.
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typename ScalarD_,
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/// The threadblock tile size for the GEMM KxNxM.
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typename OutputTile_,
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/// The functor to do the math.
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typename MultiplyAdd_,
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/// The number of scalars per LDG for A.
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int kScalarsPerLdgA_,
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/// The number of scalars per STS for A.
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int kScalarsPerStsA_,
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/// The number of scalars per LDG for A.
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int kScalarsPerLdsA_,
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/// The number of scalars per LDG for B.
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int kScalarsPerLdgB_,
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/// The number of scalars per STS for B.
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int kScalarsPerStsB_,
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/// The number of scalars per LDS for B.
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int kScalarsPerLdsB_,
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/// The number of scalars per LDG for C and STG for D.
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int kScalarsPerLdgCAndStgD_,
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/// The number of scalars per STS for D.
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int kScalarsPerStsD_,
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/// The number of scalars per LDS for D.
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int kScalarsPerLdsD_,
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/// The number of stages in shared memory to do single/double/triple-buffering.
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int kStages_,
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/// If true, residue is computed in mainloop. If false, separate loops are instantiated.
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bool kResidueSeparate_ = false,
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/// Is residue performed in prologue?
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bool kResidueInProlog_ = false,
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/// If true, kernel is launched with CUDA launch bounds specified
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bool kLaunchBounds_ = true>
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struct GemmConfig {
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//
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/// The scalar for A.
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typedef ScalarA_ ScalarA;
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/// The scalar for B.
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typedef ScalarB_ ScalarB;
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/// The scalar for C.
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typedef ScalarC_ ScalarC;
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/// The scalar for D.
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typedef ScalarD_ ScalarD;
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/// The tile.
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typedef OutputTile_ OutputTile;
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/// The functor to do D = A*B + C.
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typedef MultiplyAdd_ MultiplyAdd;
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/// The shape of the instruction.
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typedef typename MultiplyAdd::InstructionShape InstructionShape;
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/// The shape of warp-level GEMM
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typedef typename MultiplyAdd::AccumulatorsPerWarp AccumulatorsPerWarp;
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/// The accumulators.
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typedef typename MultiplyAdd::Accumulators Accumulators;
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/// The number of warps.
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typedef typename ShapeDiv<OutputTile, AccumulatorsPerWarp>::Shape Warps;
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/// The default warp size (32 threads per warp).
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static int const kWarpSize = cutlass::kWarpSize;
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/// The numnber of threads.
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static int const kThreads = ShapeCount<Warps>::kCount * kWarpSize;
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/// The number of scalars per LDG/STS/LDS for A.
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static int const kScalarsPerLdgA = kScalarsPerLdgA_;
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static int const kScalarsPerStsA = kScalarsPerStsA_;
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static int const kScalarsPerLdsA = kScalarsPerLdsA_;
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/// The number of scalars per LDG/STS/LDS for B.
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static int const kScalarsPerLdgB = kScalarsPerLdgB_;
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static int const kScalarsPerStsB = kScalarsPerStsB_;
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static int const kScalarsPerLdsB = kScalarsPerLdsB_;
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/// The number of scalars per LDG for C.
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static int const kScalarsPerLdgC = kScalarsPerLdgCAndStgD_;
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/// The number of scalars per STS/LDS/STG for D.
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static int const kScalarsPerStgD = kScalarsPerLdgCAndStgD_;
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static int const kScalarsPerStsD = kScalarsPerStsD_;
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static int const kScalarsPerLdsD = kScalarsPerLdsD_;
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/// The number of accumulators that are going to be fed from one LDS A/B.
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static int const kAccumulatorsPerLdsA = kScalarsPerLdsA / InstructionShape::kD;
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static int const kAccumulatorsPerLdsB = kScalarsPerLdsB / InstructionShape::kD;
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/// The number of stages in shared memory to implement double, triple, more-buffering.
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static int const kStages = kStages_;
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/// If true, mainloop is instantiated twice. The first instantiation contains no predicate
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// updates and is more efficient for some kernels. If false, only a single mainloop is
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// instantaited.
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static bool const kResidueSeparate = kResidueSeparate_;
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/// If true, residue is computed in the prologue.
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static bool const kResidueInProlog = kResidueInProlog_;
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/// If true, kernel is launched with launch bounds specified
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static bool const kLaunchBounds = kLaunchBounds_;
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};
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////////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace gemm
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} // namespace cutlass
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