416 lines
14 KiB
C++
416 lines
14 KiB
C++
/***************************************************************************************************
|
|
* Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
|
|
* SPDX-License-Identifier: BSD-3-Clause
|
|
*
|
|
* Redistribution and use in source and binary forms, with or without
|
|
* modification, are permitted provided that the following conditions are met:
|
|
*
|
|
* 1. Redistributions of source code must retain the above copyright notice, this
|
|
* list of conditions and the following disclaimer.
|
|
*
|
|
* 2. Redistributions in binary form must reproduce the above copyright notice,
|
|
* this list of conditions and the following disclaimer in the documentation
|
|
* and/or other materials provided with the distribution.
|
|
*
|
|
* 3. Neither the name of the copyright holder nor the names of its
|
|
* contributors may be used to endorse or promote products derived from
|
|
* this software without specific prior written permission.
|
|
*
|
|
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
|
|
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
|
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
|
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
|
|
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
|
|
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
|
|
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
|
|
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
|
|
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
|
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
*
|
|
**************************************************************************************************/
|
|
/*! \file
|
|
\brief Template for a GEMM kernel that can reduce one of the input matrix
|
|
into a vector along the K dimension.
|
|
*/
|
|
|
|
#pragma once
|
|
|
|
#include "cutlass/cutlass.h"
|
|
#include "cutlass/numeric_types.h"
|
|
#include "cutlass/arch/arch.h"
|
|
#include "cutlass/device_kernel.h"
|
|
|
|
#include "cutlass/gemm/gemm.h"
|
|
#include "cutlass/gemm/threadblock/threadblock_swizzle.h"
|
|
#include "cutlass/gemm/kernel/gemm_with_k_reduction.h"
|
|
|
|
#include "cutlass/gemm/kernel/default_gemm_with_k_reduction.h"
|
|
#include "cutlass/gemm/device/default_gemm_configuration.h"
|
|
#include "cutlass/gemm/device/gemm_universal_base.h"
|
|
|
|
#include "cutlass/layout/permute.h"
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
namespace cutlass {
|
|
namespace gemm {
|
|
namespace device {
|
|
|
|
/////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
/*!
|
|
The universal GEMM accommodates serial reductions, parallel reductions, batched strided, and
|
|
batched array variants.
|
|
*/
|
|
template <
|
|
/// Element type for A matrix operand
|
|
typename ElementA_,
|
|
/// Layout type for A matrix operand
|
|
typename LayoutA_,
|
|
/// Element type for B matrix operand
|
|
typename ElementB_,
|
|
/// Layout type for B matrix operand
|
|
typename LayoutB_,
|
|
/// Element type for C and D matrix operands
|
|
typename ElementC_,
|
|
/// Layout type for C and D matrix operands
|
|
typename LayoutC_,
|
|
/// Element type for internal accumulation
|
|
typename ElementAccumulator_ = ElementC_,
|
|
/// Operator class tag
|
|
typename OperatorClass_ = arch::OpClassSimt,
|
|
/// Reduce A or B operand along the K dimension
|
|
bool ReduceKForA_ = true,
|
|
/// Tag indicating architecture to tune for. This is the minimum SM that
|
|
/// supports the intended feature. The device kernel can be built
|
|
/// targeting any SM larger than this number.
|
|
typename ArchTag_ = arch::Sm70,
|
|
/// Threadblock-level tile size (concept: GemmShape)
|
|
typename ThreadblockShape_ = typename DefaultGemmConfiguration<
|
|
OperatorClass_, ArchTag_, ElementA_, ElementB_, ElementC_,
|
|
ElementAccumulator_>::ThreadblockShape,
|
|
/// Warp-level tile size (concept: GemmShape)
|
|
typename WarpShape_ = typename DefaultGemmConfiguration<
|
|
OperatorClass_, ArchTag_, ElementA_, ElementB_, ElementC_,
|
|
ElementAccumulator_>::WarpShape,
|
|
/// Instruction-level tile size (concept: GemmShape)
|
|
typename InstructionShape_ = typename DefaultGemmConfiguration<
|
|
OperatorClass_, ArchTag_, ElementA_, ElementB_, ElementC_,
|
|
ElementAccumulator_>::InstructionShape,
|
|
/// Epilogue output operator
|
|
typename EpilogueOutputOp_ = typename DefaultGemmConfiguration<
|
|
OperatorClass_, ArchTag_, ElementA_, ElementB_, ElementC_,
|
|
ElementAccumulator_>::EpilogueOutputOp,
|
|
/// Threadblock-level swizzling operator
|
|
typename ThreadblockSwizzle_ = threadblock::GemmIdentityThreadblockSwizzle<>,
|
|
/// Number of stages used in the pipelined mainloop
|
|
int Stages =
|
|
DefaultGemmConfiguration<OperatorClass_, ArchTag_, ElementA_, ElementB_,
|
|
ElementC_, ElementAccumulator_>::kStages,
|
|
/// Access granularity of A matrix in units of elements
|
|
int AlignmentA =
|
|
DefaultGemmConfiguration<OperatorClass_, ArchTag_, ElementA_, ElementB_,
|
|
ElementC_, ElementAccumulator_>::kAlignmentA,
|
|
/// Access granularity of B matrix in units of elements
|
|
int AlignmentB =
|
|
DefaultGemmConfiguration<OperatorClass_, ArchTag_, ElementA_, ElementB_,
|
|
ElementC_, ElementAccumulator_>::kAlignmentB,
|
|
/// Operation performed by GEMM
|
|
typename Operator_ = typename DefaultGemmConfiguration<
|
|
OperatorClass_, ArchTag_, ElementA_, ElementB_, ElementC_,
|
|
ElementAccumulator_>::Operator,
|
|
/// Complex elementwise transformation on A operand
|
|
ComplexTransform TransformA = ComplexTransform::kNone,
|
|
/// Complex elementwise transformation on B operand
|
|
ComplexTransform TransformB = ComplexTransform::kNone,
|
|
/// Gather operand A by using an index array
|
|
bool GatherA = false,
|
|
/// Gather operand B by using an index array
|
|
bool GatherB = false,
|
|
/// Scatter result D by using an index array
|
|
bool ScatterD = false,
|
|
/// Permute result D
|
|
typename PermuteDLayout = layout::NoPermute
|
|
>
|
|
class GemmWithKReduction :
|
|
public GemmUniversalBase<
|
|
typename kernel::DefaultGemmWithKReduction<
|
|
ElementA_,
|
|
LayoutA_,
|
|
TransformA,
|
|
AlignmentA,
|
|
ElementB_,
|
|
LayoutB_,
|
|
TransformB,
|
|
AlignmentB,
|
|
ElementC_,
|
|
LayoutC_,
|
|
ElementAccumulator_,
|
|
OperatorClass_,
|
|
ReduceKForA_,
|
|
ArchTag_,
|
|
ThreadblockShape_,
|
|
WarpShape_,
|
|
InstructionShape_,
|
|
EpilogueOutputOp_,
|
|
ThreadblockSwizzle_,
|
|
Stages,
|
|
Operator_,
|
|
SharedMemoryClearOption::kNone
|
|
>::GemmKernel
|
|
> {
|
|
|
|
public:
|
|
|
|
using ElementAccumulator = ElementAccumulator_;
|
|
using OperatorClass = OperatorClass_;
|
|
using ArchTag = ArchTag_;
|
|
using ThreadblockShape = ThreadblockShape_;
|
|
using WarpShape = WarpShape_;
|
|
using InstructionShape = InstructionShape_;
|
|
using EpilogueOutputOp = EpilogueOutputOp_;
|
|
using ThreadblockSwizzle = ThreadblockSwizzle_;
|
|
using Operator = Operator_;
|
|
static constexpr int kStages = Stages;
|
|
static constexpr int kAlignmentA = AlignmentA;
|
|
static constexpr int kAlignmentB = AlignmentB;
|
|
static constexpr int kAlignmentC = EpilogueOutputOp::kCount;
|
|
static constexpr ComplexTransform kTransformA = TransformA;
|
|
static constexpr ComplexTransform kTransformB = TransformB;
|
|
|
|
using Base = GemmUniversalBase<
|
|
typename kernel::DefaultGemmWithKReduction<
|
|
ElementA_,
|
|
LayoutA_,
|
|
TransformA,
|
|
AlignmentA,
|
|
ElementB_,
|
|
LayoutB_,
|
|
TransformB,
|
|
AlignmentB,
|
|
ElementC_,
|
|
LayoutC_,
|
|
ElementAccumulator_,
|
|
OperatorClass_,
|
|
ReduceKForA_,
|
|
ArchTag_,
|
|
ThreadblockShape_,
|
|
WarpShape_,
|
|
InstructionShape_,
|
|
EpilogueOutputOp_,
|
|
ThreadblockSwizzle_,
|
|
Stages,
|
|
Operator_,
|
|
SharedMemoryClearOption::kNone
|
|
>::GemmKernel
|
|
>;
|
|
|
|
using Arguments = typename Base::Arguments;
|
|
using GemmKernel = typename Base::GemmKernel;
|
|
};
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
/// Partial specialization for column-major output exchanges problem size and operand.
|
|
template <
|
|
/// Element type for A matrix operand
|
|
typename ElementA_,
|
|
/// Layout type for A matrix operand
|
|
typename LayoutA_,
|
|
/// Element type for B matrix operand
|
|
typename ElementB_,
|
|
/// Layout type for B matrix operand
|
|
typename LayoutB_,
|
|
/// Element type for C and D matrix operands
|
|
typename ElementC_,
|
|
/// Element type for internal accumulation
|
|
typename ElementAccumulator_,
|
|
/// Operator class tag
|
|
typename OperatorClass_,
|
|
/// Reduce A or B operand along the K dimension
|
|
bool ReduceKForA_,
|
|
/// Tag indicating architecture to tune for. This is the minimum SM that
|
|
/// supports the intended feature. The device kernel can be built
|
|
/// targeting any SM larger than this number.
|
|
typename ArchTag_,
|
|
/// Threadblock-level tile size (concept: GemmShape)
|
|
typename ThreadblockShape_,
|
|
/// Warp-level tile size (concept: GemmShape)
|
|
typename WarpShape_,
|
|
/// Instruction-level tile size (concept: GemmShape)
|
|
typename InstructionShape_,
|
|
/// Epilogue output operator
|
|
typename EpilogueOutputOp_,
|
|
/// Threadblock-level swizzling operator
|
|
typename ThreadblockSwizzle_,
|
|
/// Number of stages used in the pipelined mainloop
|
|
int Stages,
|
|
/// Access granularity of A matrix in units of elements
|
|
int AlignmentA,
|
|
/// Access granularity of B matrix in units of elements
|
|
int AlignmentB,
|
|
/// Operation performed by GEMM
|
|
typename Operator_,
|
|
/// Complex elementwise transformation on A operand
|
|
ComplexTransform TransformA,
|
|
/// Complex elementwise transformation on B operand
|
|
ComplexTransform TransformB,
|
|
/// Gather operand A by using an index array
|
|
bool GatherA,
|
|
/// Gather operand B by using an index array
|
|
bool GatherB,
|
|
/// Scatter result D by using an index array
|
|
bool ScatterD,
|
|
/// Permute result D
|
|
typename PermuteDLayout
|
|
>
|
|
class GemmWithKReduction<ElementA_, LayoutA_, ElementB_, LayoutB_, ElementC_,
|
|
layout::ColumnMajor, // partially specialized on LayoutC
|
|
ElementAccumulator_, OperatorClass_, ReduceKForA_, ArchTag_, ThreadblockShape_,
|
|
WarpShape_, InstructionShape_, EpilogueOutputOp_,
|
|
ThreadblockSwizzle_, Stages, AlignmentA, AlignmentB,
|
|
Operator_, TransformA, TransformB, GatherA, GatherB, ScatterD, PermuteDLayout> {
|
|
public:
|
|
|
|
using ElementA = ElementA_;
|
|
using LayoutA = LayoutA_;
|
|
using TensorRefA = TensorRef<ElementA const, LayoutA>;
|
|
using ElementB = ElementB_;
|
|
using LayoutB = LayoutB_;
|
|
using TensorRefB = TensorRef<ElementB const, LayoutB>;
|
|
using ElementC = ElementC_;
|
|
using LayoutC = layout::ColumnMajor;
|
|
using TensorRefC = TensorRef<ElementC const, LayoutC>;
|
|
using TensorRefD = TensorRef<ElementC, LayoutC>;
|
|
using ElementAccumulator = ElementAccumulator_;
|
|
using OperatorClass = OperatorClass_;
|
|
using ArchTag = ArchTag_;
|
|
using ThreadblockShape = ThreadblockShape_;
|
|
using WarpShape = WarpShape_;
|
|
using InstructionShape = InstructionShape_;
|
|
using EpilogueOutputOp = EpilogueOutputOp_;
|
|
using ThreadblockSwizzle = ThreadblockSwizzle_;
|
|
using Operator = Operator_;
|
|
static int const kStages = Stages;
|
|
static int const kAlignmentA = AlignmentA;
|
|
static int const kAlignmentB = AlignmentB;
|
|
static ComplexTransform const kTransformA = TransformA;
|
|
static ComplexTransform const kTransformB = TransformB;
|
|
|
|
using UnderlyingOperator = typename GemmWithKReduction<
|
|
ElementB,
|
|
typename layout::LayoutTranspose<LayoutB>::type,
|
|
ElementA,
|
|
typename layout::LayoutTranspose<LayoutA>::type,
|
|
ElementC,
|
|
layout::RowMajor,
|
|
ElementAccumulator,
|
|
OperatorClass,
|
|
!ReduceKForA_,
|
|
ArchTag,
|
|
ThreadblockShape,
|
|
WarpShape,
|
|
InstructionShape,
|
|
EpilogueOutputOp,
|
|
ThreadblockSwizzle,
|
|
Stages,
|
|
kAlignmentB,
|
|
kAlignmentA,
|
|
Operator,
|
|
kTransformB,
|
|
kTransformA,
|
|
GatherB,
|
|
GatherA,
|
|
ScatterD,
|
|
PermuteDLayout
|
|
>::Base;
|
|
|
|
using GemmKernel = typename UnderlyingOperator::GemmKernel;
|
|
static int const kAlignmentC = EpilogueOutputOp::kCount;
|
|
|
|
/// Argument structure
|
|
using Arguments = typename UnderlyingOperator::Arguments;
|
|
|
|
private:
|
|
|
|
UnderlyingOperator underlying_operator_;
|
|
|
|
public:
|
|
|
|
/// Constructs the GEMM.
|
|
GemmWithKReduction() = default;
|
|
|
|
/// Helper to construct a transposed equivalent for the underying GEMM operator
|
|
static Arguments to_underlying_arguments(Arguments const &args) {
|
|
return args.transposed_problem();
|
|
}
|
|
|
|
/// Determines whether the GEMM can execute the given problem.
|
|
static Status can_implement(Arguments const &args) {
|
|
|
|
return UnderlyingOperator::can_implement(to_underlying_arguments(args));
|
|
}
|
|
|
|
/// Gets the workspace size
|
|
static size_t get_workspace_size(Arguments const &args) {
|
|
|
|
return UnderlyingOperator::get_workspace_size(to_underlying_arguments(args));
|
|
}
|
|
|
|
/// Computes the grid shape
|
|
static dim3 get_grid_shape(Arguments const &args) {
|
|
return UnderlyingOperator::get_grid_shape(to_underlying_arguments(args));
|
|
}
|
|
|
|
/// Computes the maximum number of active blocks per multiprocessor
|
|
static int maximum_active_blocks(int smem_capacity = -1) {
|
|
return UnderlyingOperator::maximum_active_blocks(smem_capacity);
|
|
}
|
|
|
|
/// Initializes GEMM state from arguments.
|
|
Status initialize(Arguments const &args, void *workspace = nullptr, cudaStream_t stream = nullptr) {
|
|
|
|
return underlying_operator_.initialize(to_underlying_arguments(args), workspace, stream);
|
|
}
|
|
|
|
/// Lightweight update given a subset of arguments
|
|
Status update(Arguments const &args, void *workspace = nullptr) {
|
|
|
|
return underlying_operator_.update(to_underlying_arguments(args), workspace);
|
|
}
|
|
|
|
/// Runs the kernel using initialized state.
|
|
Status run(cudaStream_t stream = nullptr) {
|
|
|
|
return underlying_operator_.run(stream);
|
|
}
|
|
|
|
/// Runs the kernel using initialized state.
|
|
Status operator()(cudaStream_t stream = nullptr) {
|
|
return run(stream);
|
|
}
|
|
|
|
/// Runs the kernel using initialized state.
|
|
Status operator()(
|
|
Arguments const &args,
|
|
void *workspace = nullptr,
|
|
cudaStream_t stream = nullptr) {
|
|
|
|
Status status = initialize(args, workspace, stream);
|
|
|
|
if (status == Status::kSuccess) {
|
|
status = run(stream);
|
|
}
|
|
|
|
return status;
|
|
}
|
|
};
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|
|
|
|
} // namespace device
|
|
} // namespace gemm
|
|
} // namespace cutlass
|
|
|
|
////////////////////////////////////////////////////////////////////////////////
|