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gemm_with_fused_epilogue.h
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/***************************************************************************************************
* Copyright (c) 2017 - 2025 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 Gemm kernel with fused reduction operation.
*/
#pragma once
#include "cutlass/cutlass.h"
#include "cutlass/fast_math.h"
#include "cutlass/layout/layout.h"
#include "cutlass/gemm/gemm.h"
#include "cutlass/matrix_coord.h"
#include "cutlass/complex.h"
#include "cutlass/semaphore.h"
#include "cutlass/gemm/kernel/params_universal_base.h"
#include "cutlass/subbyte_reference.h"
#include "cutlass/trace.h"
/////////////////////////////////////////////////////////////////////////////////////////////////
namespace cutlass {
namespace gemm {
namespace kernel {
/////////////////////////////////////////////////////////////////////////////////////////////////
template <
typename Mma_, ///! Threadblock-scoped matrix multiply-accumulate
typename Epilogue_, ///! Epilogue
typename ThreadblockSwizzle_, ///! Threadblock swizzling function
bool IsSingleSource = Epilogue_::kIsSingleSource
>
struct GemmWithFusedEpilogue;
// GemmWithFusedEpilogue with two sources
template <
typename Mma_, ///! Threadblock-scoped matrix multiply-accumulate
typename Epilogue_, ///! Epilogue
typename ThreadblockSwizzle_ ///! Threadblock swizzling function
>
struct GemmWithFusedEpilogue<Mma_, Epilogue_, ThreadblockSwizzle_, false> {
public:
using Mma = Mma_;
using Epilogue = Epilogue_;
using EpilogueOutputOp = typename Epilogue::OutputOp;
using ThreadblockSwizzle = ThreadblockSwizzle_;
using ElementA = typename Mma::IteratorA::Element;
using LayoutA = typename Mma::IteratorA::Layout;
using ElementB = typename Mma::IteratorB::Element;
using LayoutB = typename Mma::IteratorB::Layout;
using ElementC = typename Epilogue::OutputTileIterator::Element;
using LayoutC = typename Epilogue::OutputTileIterator::Layout;
static ComplexTransform const kTransformA = Mma::kTransformA;
static ComplexTransform const kTransformB = Mma::kTransformB;
using Operator = typename Mma::Operator;
using OperatorClass = typename Mma::Operator::OperatorClass;
using ThreadblockShape = typename Mma::Shape;
using WarpShape = typename Mma::Operator::Shape;
using InstructionShape = typename Mma::Policy::Operator::InstructionShape;
using ArchTag = typename Mma::ArchTag;
static int const kStages = Mma::kStages;
static int const kAlignmentA = Mma::IteratorA::AccessType::kElements;
static int const kAlignmentB = Mma::IteratorB::AccessType::kElements;
static int const kAlignmentC = Epilogue::OutputTileIterator::kElementsPerAccess;
/// Warp count (concept: GemmShape)
using WarpCount = typename Mma::WarpCount;
static int const kThreadCount = 32 * WarpCount::kCount;
/// Split-K preserves splits that are 128b aligned
static int const kSplitKAlignment = const_max(
128 / sizeof_bits<ElementA>::value,
128 / sizeof_bits<ElementB>::value
);
//
// Structures
//
/// Argument structure
struct Arguments : UniversalArgumentsBase{
//
// Data members
//
typename EpilogueOutputOp::Params epilogue;
void const * ptr_A;
void const * ptr_B;
void const * ptr_C1;
void const * ptr_C2;
void * ptr_D;
void * ptr_Vector;
void * ptr_Tensor;
int64_t batch_stride_A;
int64_t batch_stride_B;
int64_t batch_stride_C1;
int64_t batch_stride_C2;
int64_t batch_stride_Vector;
int64_t batch_stride_Tensor;
typename LayoutA::Stride::Index lda;
typename LayoutB::Stride::Index ldb;
typename LayoutC::Stride::Index ldc1;
typename LayoutC::Stride::Index ldc2;
typename LayoutC::Stride::Index ldd;
typename LayoutC::Stride::Index ldr;
typename LayoutC::Stride::Index ldt;
//
// Methods
//
Arguments():
ptr_A(nullptr),
ptr_B(nullptr),
ptr_C1(nullptr),
ptr_C2(nullptr),
ptr_D(nullptr)
{}
/// constructs an arguments structure
Arguments(
GemmUniversalMode mode,
GemmCoord problem_size,
int batch_count,
typename EpilogueOutputOp::Params epilogue,
void const * ptr_A,
void const * ptr_B,
void const * ptr_C1,
void const * ptr_C2,
void * ptr_D,
void * ptr_Vector,
void * ptr_Tensor,
int64_t batch_stride_A,
int64_t batch_stride_B,
int64_t batch_stride_C1,
int64_t batch_stride_C2,
int64_t batch_stride_D,
int64_t batch_stride_Vector,
int64_t batch_stride_Tensor,
typename LayoutA::Stride::Index lda,
typename LayoutB::Stride::Index ldb,
typename LayoutC::Stride::Index ldc1,
typename LayoutC::Stride::Index ldc2,
typename LayoutC::Stride::Index ldd,
typename LayoutC::Stride::Index ldr,
typename LayoutC::Stride::Index ldt)
:
UniversalArgumentsBase(mode, problem_size, batch_count, batch_stride_D),
epilogue(epilogue),
ptr_A(ptr_A), ptr_B(ptr_B), ptr_C1(ptr_C1), ptr_C2(ptr_C2), ptr_D(ptr_D),
ptr_Vector(ptr_Vector),
ptr_Tensor(ptr_Tensor),
batch_stride_A(batch_stride_A),
batch_stride_B(batch_stride_B),
batch_stride_C1(batch_stride_C1),
batch_stride_C2(batch_stride_C2),
batch_stride_Vector(batch_stride_Vector),
batch_stride_Tensor(batch_stride_Tensor),
lda(lda), ldb(ldb), ldc1(ldc1), ldc2(ldc2), ldd(ldd), ldr(ldr), ldt(ldt)
{
CUTLASS_TRACE_HOST("GemmWithFusedEpilogue::Arguments::Arguments() - problem_size: " << problem_size);
CUTLASS_TRACE_HOST(" ptr_Vector: " << (void *)this->ptr_Vector);
CUTLASS_TRACE_HOST(" ptr_Tensor: " << (void *)this->ptr_Tensor);
CUTLASS_TRACE_HOST(" ldr: " << this->ldr);
CUTLASS_TRACE_HOST(" ldt: " << this->ldt);
}
/// Returns arguments for the transposed problem
Arguments transposed_problem() const {
Arguments args(*this);
std::swap(args.problem_size.m(), args.problem_size.n());
std::swap(args.ptr_A, args.ptr_B);
std::swap(args.lda, args.ldb);
std::swap(args.batch_stride_A, args.batch_stride_B);
return args;
}
};
//
// Structure for precomputing values in host memory and passing to kernels
//
/// Parameters structure
struct Params : UniversalParamsBase<
ThreadblockSwizzle,
ThreadblockShape,
ElementA,
ElementB,
ElementC,
LayoutA,
LayoutB>
{
using ParamsBase = UniversalParamsBase<
ThreadblockSwizzle,
ThreadblockShape,
ElementA,
ElementB,
ElementC,
LayoutA,
LayoutB>;
//
// Data members
//
typename Mma::IteratorA::Params params_A;
typename Mma::IteratorB::Params params_B;
typename Epilogue::OutputTileIterator::Params params_C1;
typename Epilogue::OutputTileIterator::Params params_C2;
typename Epilogue::OutputTileIterator::Params params_D;
typename Epilogue::TensorTileIterator::Params params_Tensor;
typename EpilogueOutputOp::Params output_op;
void * ptr_A;
void * ptr_B;
void * ptr_C1;
void * ptr_C2;
void * ptr_D;
void * ptr_Vector;
typename LayoutC::Stride::Index ldr;
void * ptr_Tensor;
int64_t batch_stride_A;
int64_t batch_stride_B;
int64_t batch_stride_C1;
int64_t batch_stride_C2;
int64_t batch_stride_Vector;
int64_t batch_stride_Tensor;
//
// Host dispatch API
//
/// Default constructor
Params() = default;
/// Constructor
Params(
Arguments const &args, /// GEMM application arguments
int device_sms, /// Number of SMs on the device
int sm_occupancy) /// Kernel SM occupancy (in thread blocks)
:
ParamsBase(args, device_sms, sm_occupancy),
params_A(args.lda),
params_B(args.ldb),
params_C1(args.ldc1),
params_C2(args.ldc2),
params_D(args.ldd),
params_Tensor(args.ldt),
output_op(args.epilogue),
ptr_A(const_cast<void *>(args.ptr_A)),
ptr_B(const_cast<void *>(args.ptr_B)),
ptr_C1(const_cast<void *>(args.ptr_C1)),
ptr_C2(const_cast<void *>(args.ptr_C2)),
ptr_D(args.ptr_D),
ptr_Vector(args.ptr_Vector),
ldr(args.ldr),
ptr_Tensor(args.ptr_Tensor),
batch_stride_A(args.batch_stride_A),
batch_stride_B(args.batch_stride_B),
batch_stride_C1(args.batch_stride_C1),
batch_stride_C2(args.batch_stride_C2),
batch_stride_Vector(args.batch_stride_Vector),
batch_stride_Tensor(args.batch_stride_Tensor)
{
CUTLASS_TRACE_HOST("GemmWithFusedEpilogue::Params::Params()");
CUTLASS_TRACE_HOST(" ptr_Vector: " << (void *)this->ptr_Vector);
CUTLASS_TRACE_HOST(" ptr_Tensor: " << (void *)this->ptr_Tensor);
CUTLASS_TRACE_HOST(" ldr: " << this->ldr);
CUTLASS_TRACE_HOST(" ldt: " << args.ldt);
}
/// Lightweight update given a subset of arguments.
CUTLASS_HOST_DEVICE
void update(Arguments const &args)
{
ptr_A = const_cast<void *>(args.ptr_A);
ptr_B = const_cast<void *>(args.ptr_B);
ptr_C1 = const_cast<void *>(args.ptr_C1);
ptr_C2 = const_cast<void *>(args.ptr_C2);
ptr_D = args.ptr_D;
ptr_Vector = args.ptr_Vector;
ldr = args.ldr;
ptr_Tensor = args.ptr_Tensor;
batch_stride_A = args.batch_stride_A;
batch_stride_B = args.batch_stride_B;
batch_stride_C1 = args.batch_stride_C1;
batch_stride_C2 = args.batch_stride_C2;
batch_stride_Vector = args.batch_stride_Vector;
batch_stride_Tensor = args.batch_stride_Tensor;
this->batch_stride_D = args.batch_stride_D;
output_op = args.epilogue;
CUTLASS_TRACE_HOST("GemmWithFusedEpilogue::Params::update()");
CUTLASS_TRACE_HOST(" ptr_Vector: " << (void *)this->ptr_Vector);
CUTLASS_TRACE_HOST(" ptr_Tensor: " << (void *)this->ptr_Tensor);
CUTLASS_TRACE_HOST(" ldr: " << this->ldr);
}
};
/// Shared memory storage structure
union SharedStorage {
typename Mma::SharedStorage main_loop;
typename Epilogue::SharedStorage epilogue;
};
public:
//
// Host dispatch API
//
/// Determines whether kernel satisfies alignment
static Status can_implement(
cutlass::gemm::GemmCoord const & problem_size) {
CUTLASS_TRACE_HOST("GemmWithFusedEpilogue::can_implement()");
static int const kAlignmentA = Mma::IteratorA::AccessType::kElements;
static int const kAlignmentB = Mma::IteratorB::AccessType::kElements;
static int const kAlignmentC = Epilogue::OutputTileIterator::kElementsPerAccess;
bool isAMisaligned = false;
bool isBMisaligned = false;
bool isCMisaligned = false;
if (platform::is_same<LayoutA, layout::RowMajor>::value) {
isAMisaligned = problem_size.k() % kAlignmentA;
} else if (platform::is_same<LayoutA, layout::ColumnMajor>::value) {
isAMisaligned = problem_size.m() % kAlignmentA;
} else if (platform::is_same<LayoutA, layout::ColumnMajorInterleaved<32>>::value
|| platform::is_same<LayoutA, layout::ColumnMajorInterleaved<64>>::value) {
isAMisaligned = problem_size.k() % kAlignmentA;
}
if (platform::is_same<LayoutB, layout::RowMajor>::value) {
isBMisaligned = problem_size.n() % kAlignmentB;
} else if (platform::is_same<LayoutB, layout::ColumnMajor>::value) {
isBMisaligned = problem_size.k() % kAlignmentB;
} else if (platform::is_same<LayoutB, layout::RowMajorInterleaved<32>>::value
|| platform::is_same<LayoutB, layout::RowMajorInterleaved<64>>::value) {
isBMisaligned = problem_size.k() % kAlignmentB;
}
if (platform::is_same<LayoutC, layout::RowMajor>::value) {
isCMisaligned = problem_size.n() % kAlignmentC;
} else if (platform::is_same<LayoutC, layout::ColumnMajor>::value) {
isCMisaligned = problem_size.m() % kAlignmentC;
} else if (platform::is_same<LayoutC, layout::ColumnMajorInterleaved<32>>::value
|| platform::is_same<LayoutC, layout::ColumnMajorInterleaved<64>>::value) {
isCMisaligned = problem_size.n() % kAlignmentC;
}
if (isAMisaligned) {
CUTLASS_TRACE_HOST(" returning kErrorMisalignedOperand for A operand");
return Status::kErrorMisalignedOperand;
}
if (isBMisaligned) {
CUTLASS_TRACE_HOST(" returning kErrorMisalignedOperand for B operand");
return Status::kErrorMisalignedOperand;
}
if (isCMisaligned) {
CUTLASS_TRACE_HOST(" returning kErrorMisalignedOperand for C operand");
return Status::kErrorMisalignedOperand;
}
CUTLASS_TRACE_HOST(" returning kSuccess");
return Status::kSuccess;
}
static Status can_implement(Arguments const &args) {
return can_implement(args.problem_size);
}
public:
//
// Device-only API
//
// Factory invocation
CUTLASS_DEVICE
static void invoke(
Params const ¶ms,
SharedStorage &shared_storage)
{
GemmWithFusedEpilogue op;
op(params, shared_storage);
}
#define SPLIT_K_ENABLED 1
/// Executes one GEMM
CUTLASS_DEVICE
void operator()(Params const ¶ms, SharedStorage &shared_storage) {
// Compute threadblock location
ThreadblockSwizzle threadblock_swizzle;
cutlass::gemm::GemmCoord threadblock_tile_offset = threadblock_swizzle.get_tile_offset(params.swizzle_log_tile);
// Early exit if CTA is out of range
if (params.grid_tiled_shape.m() <= threadblock_tile_offset.m() ||
params.grid_tiled_shape.n() <= threadblock_tile_offset.n()) {
return;
}
int offset_k = 0;
int problem_size_k = params.problem_size.k();
ElementA *ptr_A = static_cast<ElementA *>(params.ptr_A);
ElementB *ptr_B = static_cast<ElementB *>(params.ptr_B);
#if SPLIT_K_ENABLED
//
// Fetch pointers based on mode.
//
if (params.mode == GemmUniversalMode::kGemm ||
params.mode == GemmUniversalMode::kGemmSplitKParallel) {
if (threadblock_tile_offset.k() + 1 < params.grid_tiled_shape.k()) {
problem_size_k = (threadblock_tile_offset.k() + 1) * params.gemm_k_size;
}
offset_k = threadblock_tile_offset.k() * params.gemm_k_size;
}
else if (params.mode == GemmUniversalMode::kBatched) {
ptr_A += threadblock_tile_offset.k() * params.batch_stride_A;
ptr_B += threadblock_tile_offset.k() * params.batch_stride_B;
}
else if (params.mode == GemmUniversalMode::kArray) {
ptr_A = static_cast<ElementA * const *>(params.ptr_A)[threadblock_tile_offset.k()];
ptr_B = static_cast<ElementB * const *>(params.ptr_B)[threadblock_tile_offset.k()];
}
#endif
// Compute initial location in logical coordinates
cutlass::MatrixCoord tb_offset_A{
threadblock_tile_offset.m() * Mma::Shape::kM,
offset_k,
};
cutlass::MatrixCoord tb_offset_B{
offset_k,
threadblock_tile_offset.n() * Mma::Shape::kN
};
// Compute position within threadblock
int thread_idx = threadIdx.x;
// Construct iterators to A and B operands
typename Mma::IteratorA iterator_A(
params.params_A,
ptr_A,
{params.problem_size.m(), problem_size_k},
thread_idx,
tb_offset_A);
typename Mma::IteratorB iterator_B(
params.params_B,
ptr_B,
{problem_size_k, params.problem_size.n()},
thread_idx,
tb_offset_B);
// Broadcast the warp_id computed by lane 0 to ensure dependent code
// is compiled as warp-uniform.
int warp_idx = __shfl_sync(0xffffffff, threadIdx.x / 32, 0);
int lane_idx = threadIdx.x % 32;
//
// Main loop
//
// Construct thread-scoped matrix multiply
Mma mma(shared_storage.main_loop, thread_idx, warp_idx, lane_idx);
typename Mma::FragmentC accumulators;
accumulators.clear();
// Compute threadblock-scoped matrix multiply-add
int gemm_k_iterations = (problem_size_k - offset_k + Mma::Shape::kK - 1) / Mma::Shape::kK;
// Compute threadblock-scoped matrix multiply-add
mma(
gemm_k_iterations,
accumulators,
iterator_A,
iterator_B,
accumulators);
//
// Epilogue
//
EpilogueOutputOp output_op(params.output_op);
//
// Masked tile iterators constructed from members
//
threadblock_tile_offset = threadblock_swizzle.get_tile_offset(params.swizzle_log_tile);
//assume identity swizzle
MatrixCoord threadblock_offset(
threadblock_tile_offset.m() * Mma::Shape::kM,
threadblock_tile_offset.n() * Mma::Shape::kN
);
int block_idx = threadblock_tile_offset.m() + threadblock_tile_offset.n() * params.grid_tiled_shape.m();
ElementC *ptr_C1 = static_cast<ElementC *>(params.ptr_C1);
ElementC *ptr_C2 = static_cast<ElementC *>(params.ptr_C2);
ElementC *ptr_D = static_cast<ElementC *>(params.ptr_D);
typename Epilogue::ElementTensor *ptr_Tensor = static_cast<typename Epilogue::ElementTensor *>(params.ptr_Tensor);
// Define the reduction output pointer and move to the appropriate place
typename Epilogue::ElementVector *ptr_Vector =
static_cast<typename Epilogue::ElementVector *>(params.ptr_Vector);
//
// Fetch pointers based on mode.
//
//
// Special path when split-K not enabled.
//
if (params.mode == GemmUniversalMode::kGemm && params.grid_tiled_shape.k() == 1) {
// Tile iterators loading from source tensors.
typename Epilogue::OutputTileIterator iterator_C1(
params.params_C1,
ptr_C1,
params.problem_size.mn(),
thread_idx,
threadblock_offset
);
typename Epilogue::OutputTileIterator iterator_C2(
params.params_C2,
ptr_C2,
params.problem_size.mn(),
thread_idx,
threadblock_offset
);
// Tile iterator writing to destination tensor.
typename Epilogue::OutputTileIterator iterator_D(
params.params_D,
ptr_D,
params.problem_size.mn(),
thread_idx,
threadblock_offset
);
// Additional tensor to load from
typename Epilogue::TensorTileIterator tensor_iterator(
params.params_Tensor,
// Only the final block outputs Tensor
ptr_Tensor,
params.problem_size.mn(),
thread_idx,
threadblock_offset);
// Construct the epilogue
Epilogue epilogue(
shared_storage.epilogue,
thread_idx,
warp_idx,
lane_idx);
// Move to appropriate location for this output tile
if (ptr_Vector) {
ptr_Vector += threadblock_offset.column() + threadblock_tile_offset.m() * params.ldr;
}
// Execute the epilogue operator to update the destination tensor.
epilogue(output_op,
ptr_Vector,
iterator_D,
accumulators,
iterator_C1,
iterator_C2,
tensor_iterator,
params.problem_size.mn(),
threadblock_offset);
return;
}
//
// Slower path when split-K or batching is needed
//
#if SPLIT_K_ENABLED
// Construct the semaphore.
Semaphore semaphore(params.semaphore + block_idx, thread_idx);
if (params.mode == GemmUniversalMode::kGemm) {
// If performing a reduction via split-K, fetch the initial synchronization
if (params.grid_tiled_shape.k() > 1) {
// Fetch the synchronization lock initially but do not block.
semaphore.fetch();
// Indicate which position in a serial reduction the output operator is currently updating
output_op.set_k_partition(threadblock_tile_offset.k(), params.grid_tiled_shape.k());
}
}
else if (params.mode == GemmUniversalMode::kGemmSplitKParallel) {
ptr_D += threadblock_tile_offset.k() * params.batch_stride_D;
}
else if (params.mode == GemmUniversalMode::kBatched) {
ptr_C1 += threadblock_tile_offset.k() * params.batch_stride_C1;
if (ptr_C2) {
ptr_C2 += threadblock_tile_offset.k() * params.batch_stride_C2;
}
ptr_D += threadblock_tile_offset.k() * params.batch_stride_D;
if (ptr_Tensor) {
ptr_Tensor = ReferenceFactory<typename Epilogue::ElementTensor>::add_pointer_offset(
ptr_Tensor,
threadblock_tile_offset.k() * params.batch_stride_Tensor);
}
if (ptr_Vector) {
ptr_Vector += threadblock_tile_offset.k() * params.batch_stride_Vector;
}
}
else if (params.mode == GemmUniversalMode::kArray) {
ptr_C1 = static_cast<ElementC * const *>(params.ptr_C1)[threadblock_tile_offset.k()];
if (ptr_C2) {
ptr_C2 = static_cast<ElementC * const *>(params.ptr_C2)[threadblock_tile_offset.k()];
}
ptr_D = static_cast<ElementC * const *>(params.ptr_D)[threadblock_tile_offset.k()];
if (ptr_Tensor) {
ptr_Tensor = static_cast<typename Epilogue::ElementTensor * const *>(params.ptr_Tensor)[threadblock_tile_offset.k()];
}
if (ptr_Vector) {
ptr_Vector = static_cast<typename Epilogue::ElementVector * const *>(params.ptr_Vector)[threadblock_tile_offset.k()];
}
}
#endif
// Tile iterators loading from source tensors.
typename Epilogue::OutputTileIterator iterator_C1(
params.params_C1,
ptr_C1,
params.problem_size.mn(),
thread_idx,
threadblock_offset
);
typename Epilogue::OutputTileIterator iterator_C2(
params.params_C2,
ptr_C2,
params.problem_size.mn(),
thread_idx,
threadblock_offset
);
// Tile iterator writing to destination tensor.
typename Epilogue::OutputTileIterator iterator_D(
params.params_D,
ptr_D,
params.problem_size.mn(),
thread_idx,
threadblock_offset
);
// Additional tensor to load from
typename Epilogue::TensorTileIterator tensor_iterator(
params.params_Tensor,
// Only the final block outputs Tensor
((params.mode == GemmUniversalMode::kGemm && params.grid_tiled_shape.k() > 1) &&
(params.grid_tiled_shape.k() != threadblock_tile_offset.k() + 1))
? nullptr
: ptr_Tensor,
params.problem_size.mn(),
thread_idx,
threadblock_offset);
// Construct the epilogue
Epilogue epilogue(
shared_storage.epilogue,
thread_idx,
warp_idx,
lane_idx);
#if SPLIT_K_ENABLED
// Wait on the semaphore - this latency may have been covered by iterator construction
if ((params.mode == GemmUniversalMode::kGemm) && params.grid_tiled_shape.k() > 1) {
// For subsequent threadblocks, the source matrix is held in the 'D' tensor.
if (threadblock_tile_offset.k()) {
iterator_C1 = iterator_D;
}
semaphore.wait(threadblock_tile_offset.k());
}
#endif
// Move to appropriate location for this output tile
if (ptr_Vector) {
ptr_Vector += threadblock_offset.column() + threadblock_tile_offset.m() * params.ldr;
}
// Execute the epilogue operator to update the destination tensor.
epilogue(output_op,
// Only the final block uses Vector
((params.mode == GemmUniversalMode::kGemm && params.grid_tiled_shape.k() > 1) &&
(params.grid_tiled_shape.k() != threadblock_tile_offset.k() + 1))
? nullptr
: ptr_Vector,
iterator_D,
accumulators,
iterator_C1,
iterator_C2,
tensor_iterator,
params.problem_size.mn(),
threadblock_offset);
//
// Release the semaphore
//
#if SPLIT_K_ENABLED
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);
}
#endif
}
};
// GemmWithFusedEpilogue with one source
template <
typename Mma_, ///! Threadblock-scoped matrix multiply-accumulate
typename Epilogue_, ///! Epilogue
typename ThreadblockSwizzle_ ///! Threadblock swizzling function
>
struct GemmWithFusedEpilogue<Mma_, Epilogue_, ThreadblockSwizzle_, true> {
public:
using Mma = Mma_;
using Epilogue = Epilogue_;
using EpilogueOutputOp = typename Epilogue::OutputOp;
using ThreadblockSwizzle = ThreadblockSwizzle_;
using ElementA = typename Mma::IteratorA::Element;
using LayoutA = typename Mma::IteratorA::Layout;
using ElementB = typename Mma::IteratorB::Element;
using LayoutB = typename Mma::IteratorB::Layout;
using ElementC = typename Epilogue::OutputTileIterator::Element;
using LayoutC = typename Epilogue::OutputTileIterator::Layout;
static ComplexTransform const kTransformA = Mma::kTransformA;
static ComplexTransform const kTransformB = Mma::kTransformB;
using Operator = typename Mma::Operator;
using OperatorClass = typename Mma::Operator::OperatorClass;
using ThreadblockShape = typename Mma::Shape;
using WarpShape = typename Mma::Operator::Shape;
using InstructionShape = typename Mma::Policy::Operator::InstructionShape;
using ArchTag = typename Mma::ArchTag;
static int const kStages = Mma::kStages;
static int const kAlignmentA = Mma::IteratorA::AccessType::kElements;
static int const kAlignmentB = Mma::IteratorB::AccessType::kElements;
static int const kAlignmentC = Epilogue::OutputTileIterator::kElementsPerAccess;
/// Warp count (concept: GemmShape)
using WarpCount = typename Mma::WarpCount;
static int const kThreadCount = 32 * WarpCount::kCount;
/// Split-K preserves splits that are 128b aligned
static int const kSplitKAlignment = const_max(
128 / sizeof_bits<ElementA>::value,
128 / sizeof_bits<ElementB>::value
);
//
// Structures
//
/// Argument structure
struct Arguments : UniversalArgumentsBase
{
//
// Data members
//
typename EpilogueOutputOp::Params epilogue;
void const * ptr_A;
void const * ptr_B;
void const * ptr_C;
void * ptr_D;
void * ptr_Vector;
void * ptr_Tensor;
int64_t batch_stride_A;
int64_t batch_stride_B;
int64_t batch_stride_C;
int64_t batch_stride_Vector;
int64_t batch_stride_Tensor;
typename LayoutA::Stride::Index lda;
typename LayoutB::Stride::Index ldb;
typename LayoutC::Stride::Index ldc;
typename LayoutC::Stride::Index ldd;
typename LayoutC::Stride::Index ldr;
typename LayoutC::Stride::Index ldt;
//
// Methods
//
Arguments():
ptr_A(nullptr),
ptr_B(nullptr),
ptr_C(nullptr),
ptr_D(nullptr)
{}
/// constructs an arguments structure
Arguments(
GemmUniversalMode mode,
GemmCoord problem_size,
int batch_count,
typename EpilogueOutputOp::Params epilogue,
void const * ptr_A,
void const * ptr_B,
void const * ptr_C,
void * ptr_D,
void * ptr_Vector,
void * ptr_Tensor,
int64_t batch_stride_A,
int64_t batch_stride_B,
int64_t batch_stride_C,
int64_t batch_stride_D,
int64_t batch_stride_Vector,
int64_t batch_stride_Tensor,
typename LayoutA::Stride::Index lda,
typename LayoutB::Stride::Index ldb,
typename LayoutC::Stride::Index ldc,
typename LayoutC::Stride::Index ldd,
typename LayoutC::Stride::Index ldr,
typename LayoutC::Stride::Index ldt)
:
UniversalArgumentsBase(mode, problem_size, batch_count, batch_stride_D),
epilogue(epilogue),
ptr_A(ptr_A), ptr_B(ptr_B), ptr_C(ptr_C), ptr_D(ptr_D),
ptr_Vector(ptr_Vector),
ptr_Tensor(ptr_Tensor),
batch_stride_A(batch_stride_A),
batch_stride_B(batch_stride_B),
batch_stride_C(batch_stride_C),
batch_stride_Vector(batch_stride_Vector),
batch_stride_Tensor(batch_stride_Tensor),
lda(lda), ldb(ldb), ldc(ldc), ldd(ldd), ldr(ldr), ldt(ldt)
{
CUTLASS_TRACE_HOST("GemmWithFusedEpilogue::Arguments::Arguments() - problem_size: " << problem_size);
CUTLASS_TRACE_HOST(" ptr_Vector: " << (void *)this->ptr_Vector);
CUTLASS_TRACE_HOST(" ptr_Tensor: " << (void *)this->ptr_Tensor);
CUTLASS_TRACE_HOST(" ldr: " << this->ldr);
CUTLASS_TRACE_HOST(" ldt: " << this->ldt);
}
/// Returns arguments for the transposed problem
Arguments transposed_problem() const {
Arguments args(*this);
std::swap(args.problem_size.m(), args.problem_size.n());
std::swap(args.ptr_A, args.ptr_B);
std::swap(args.lda, args.ldb);
std::swap(args.batch_stride_A, args.batch_stride_B);
return args;
}
};
//
// Structure for precomputing values in host memory and passing to kernels
//
/// Parameters structure
struct Params : UniversalParamsBase<
ThreadblockSwizzle,
ThreadblockShape,
ElementA,
ElementB,
ElementC,
LayoutA,
LayoutB>
{
using ParamsBase = UniversalParamsBase<
ThreadblockSwizzle,
ThreadblockShape,
ElementA,
ElementB,
ElementC,
LayoutA,
LayoutB>;
//
// Data members
//
typename Mma::IteratorA::Params params_A;
typename Mma::IteratorB::Params params_B;
typename Epilogue::OutputTileIterator::Params params_C;
typename Epilogue::OutputTileIterator::Params params_D;
typename Epilogue::TensorTileIterator::Params params_Tensor;
typename EpilogueOutputOp::Params output_op;
void * ptr_A;
void * ptr_B;
void * ptr_C;
void * ptr_D;
void * ptr_Vector;
typename LayoutC::Stride::Index ldr;
void * ptr_Tensor;
int64_t batch_stride_A;
int64_t batch_stride_B;