Andrew Kerr
86931fef85
Adds support for NVIDIA Ampere Architecture features. CUDA 11 Toolkit recommended.
239 lines
7.6 KiB
C++
239 lines
7.6 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 Templates implementing warp-level matrix multiply-accumulate operations.
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*/
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#pragma once
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#include "cutlass/cutlass.h"
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#include "cutlass/array.h"
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#include "cutlass/numeric_types.h"
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#include "cutlass/matrix_shape.h"
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#include "cutlass/gemm/gemm.h"
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#include "cutlass/gemm/warp/mma.h"
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#include "cutlass/gemm/thread/mma.h"
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#include "cutlass/gemm/warp/mma_simt_tile_iterator.h"
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#include "cutlass/gemm/warp/mma_simt_policy.h"
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/////////////////////////////////////////////////////////////////////////////////////////////////
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namespace cutlass {
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namespace gemm {
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namespace warp {
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// Structure to compute the matrix product targeting CUDA cores and SIMT math instructions.
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template <
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/// Size of the Gemm problem - concept: gemm::GemmShape<>
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typename Shape_,
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/// Data type of A elements
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typename ElementA_,
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/// Layout of A matrix (concept: MatrixLayout)
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typename LayoutA_,
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/// Data type of B elements
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typename ElementB_,
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/// Layout of B matrix (concept: MatrixLayout)
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typename LayoutB_,
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/// Element type of C matrix
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typename ElementC_,
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/// Layout of C matrix (concept: MatrixLayout)
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typename LayoutC_,
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/// Shape of the warp in units of thread (concept: MmaSimtPolicy)
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typename Policy_,
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/// Number of partitions along K dimension
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int PartitionsK = 1,
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/// Used for partial specialization
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typename Enable = bool
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>
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class MmaSimt {
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public:
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/// Shape of warp-level matrix operation (concept: GemmShape)
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using Shape = Shape_;
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/// Data type of multiplicand A
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using ElementA = ElementA_;
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/// Layout of multiplicand A
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using LayoutA = LayoutA_;
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/// Data type of multiplicand B
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using ElementB = ElementB_;
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/// Layout of multiplicand B
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using LayoutB = LayoutB_;
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/// Data type of accumulator matrix C
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using ElementC = ElementC_;
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/// Layout of accumulator matrix C
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using LayoutC = LayoutC_;
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/// Shape of the warp in units of thread (concept: MmaLanePolicySimt)
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using Policy = Policy_;
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/// Indicates class of matrix operator
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using OperatorClass = arch::OpClassSimt;
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/// Hard-coded for now
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using ArchTag = arch::Sm50;
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/// Complex transform on A operand
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static ComplexTransform const kTransformA = ComplexTransform::kNone;
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/// Complex transform on B operand
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static ComplexTransform const kTransformB = ComplexTransform::kNone;
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/// Layout of threads
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using ThreadLayoutA = typename platform::conditional< platform::is_same< layout::ColumnMajorInterleaved<4>, LayoutA >::value,
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layout::ColumnMajor,
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typename platform::conditional < platform::is_same< layout::RowMajorInterleaved<4>, LayoutA >::value,
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layout::RowMajor,
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LayoutA>::type
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>::type;
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using ThreadLayoutB = typename platform::conditional< platform::is_same< layout::ColumnMajorInterleaved<4>, LayoutB >::value,
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layout::ColumnMajor,
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typename platform::conditional < platform::is_same< layout::RowMajorInterleaved<4>, LayoutB >::value,
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layout::RowMajor,
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LayoutB>::type
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>::type;
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static constexpr bool use_dp4a = (platform::is_same< layout::ColumnMajorInterleaved<4>, LayoutA>::value ||
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platform::is_same< layout::RowMajorInterleaved<4>, LayoutA >::value) &&
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platform::is_same< ElementA, int8_t >::value &&
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platform::is_same< ElementB, int8_t >::value;
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using dp4a_type = typename platform::conditional< use_dp4a , int8_t, bool >::type;
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/// Thread-level matrix multiply accumulate operator
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using ThreadMma = thread::Mma<
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GemmShape<
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Shape::kM / Policy::WarpShape::kRow,
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Shape::kN / Policy::WarpShape::kColumn,
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Policy::LaneMmaShape::kK>,
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ElementA,
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ThreadLayoutA,
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ElementB,
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ThreadLayoutB,
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ElementC,
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LayoutC,
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arch::OpMultiplyAdd,
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dp4a_type
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>;
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/// Shape of the underlying instruction
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using InstructionShape = GemmShape<1,1,use_dp4a ? 4 : 1>;
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public:
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/// Iterates over the A operand in memory
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using IteratorA = MmaSimtTileIterator<
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MatrixShape<Shape::kM, Policy::LaneMmaShape::kK>,
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Operand::kA,
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ElementA,
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LayoutA,
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Policy,
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PartitionsK,
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Shape::kK
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>;
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/// Storage for A tile
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using FragmentA = typename IteratorA::Fragment;
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/// Storage for transformed A tile
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using TransformedFragmentA = FragmentA;
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/// Iterates over the B operand in memory
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using IteratorB = MmaSimtTileIterator<
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MatrixShape<Policy::LaneMmaShape::kK, Shape::kN>,
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Operand::kB,
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ElementB,
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LayoutB,
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Policy,
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PartitionsK,
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Shape::kK
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>;
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/// Storage for B tile
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using FragmentB = typename IteratorB::Fragment;
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/// Storage for transformed A tile
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using TransformedFragmentB = FragmentB;
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/// Iterates over the C operand in memory
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using IteratorC = MmaSimtTileIterator<
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MatrixShape<Shape::kM, Shape::kN>,
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Operand::kC,
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ElementC,
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LayoutC,
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Policy
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>;
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/// Storage for C tile
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using FragmentC = typename ThreadMma::FragmentC;
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public:
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//
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// Methods
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//
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/// Ctor
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CUTLASS_DEVICE
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MmaSimt() {}
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/// Performs a warp-level matrix multiply-accumulate operation
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CUTLASS_DEVICE
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void operator()(
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FragmentC &d,
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FragmentA const &a,
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FragmentB const &b,
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FragmentC const &c, int group_idx = 0) const {
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ThreadMma mma;
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mma(d, a, b, c);
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}
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/// Transform the mma operands to the required types
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CUTLASS_DEVICE
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void transform(TransformedFragmentA &dst_A, TransformedFragmentB &dst_B,
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FragmentA const &A, FragmentB const &B) const {
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//TODO: Implement this
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dst_A = A;
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dst_B = B;
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}
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};
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/////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace warp
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} // namespace gemm
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} // namespace cutlass
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