cutlass/include/cutlass/gemm/kernel/gemm_universal_with_visitor.h
2024-01-16 14:37:22 -05:00

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/*! \file
\brief Gemm kernel with an epilogue defined under the epilogue visitor concept
*/
#pragma once
#include "cutlass/cutlass.h"
#include "cutlass/gemm/kernel/gemm_universal.h"
/////////////////////////////////////////////////////////////////////////////////////////////////
namespace cutlass {
namespace gemm {
namespace kernel {
/////////////////////////////////////////////////////////////////////////////////////////////////
// Gemm that compute the epilogue visitor functor
template <
typename Mma, ///! Threadblock-scoped matrix multiply-accumulate
typename Epilogue, ///! Epilogue
typename ThreadblockSwizzle_ ///! Threadblock swizzling function
>
class GemmWithEpilogueVisitor: GemmUniversal<Mma,Epilogue, ThreadblockSwizzle_> {
public:
using ThreadblockSwizzle = ThreadblockSwizzle_;
using Base = GemmUniversal<Mma,Epilogue, ThreadblockSwizzle>;
using Base::Base;
using FusionCallbacks = typename Epilogue::FusionCallbacks;
using ElementA = typename Base::ElementA;
using LayoutA = typename Base::LayoutA;
using ElementB = typename Base::ElementB;
using LayoutB = typename Base::LayoutB;
using ElementC = typename Base::ElementC;
using LayoutC = typename Base::LayoutC;
using ThreadblockShape = typename Mma::Shape;
//
// Structures
//
using SharedStorage = typename Base::SharedStorage;
using Arguments = typename Base::Arguments;
//
// 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
//
cute::Shape<int32_t,int32_t,int32_t> problem_shape;
typename Mma::IteratorA::Params params_A;
typename Mma::IteratorB::Params params_B;
typename FusionCallbacks::Params output_op;
void * ptr_A;
void * ptr_B;
int64_t batch_stride_A;
int64_t batch_stride_B;
int * ptr_gather_A_indices;
int * ptr_gather_B_indices;
//
// 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 ? make_Coord_with_padding<LayoutA::kStrideRank>(args.lda) : args.stride_a),
params_B(args.ldb ? make_Coord_with_padding<LayoutB::kStrideRank>(args.ldb) : args.stride_b),
output_op(FusionCallbacks::to_underlying_arguments(args.problem_size, args.epilogue, nullptr /*workspace*/)),
problem_shape({args.problem_size.m(), args.problem_size.n(), args.batch_count}),
ptr_A(const_cast<void *>(args.ptr_A)),
ptr_B(const_cast<void *>(args.ptr_B)),
batch_stride_A(args.batch_stride_A),
batch_stride_B(args.batch_stride_B),
ptr_gather_A_indices(const_cast<int *>(args.ptr_gather_A_indices)),
ptr_gather_B_indices(const_cast<int *>(args.ptr_gather_B_indices))
{
// Raise error on unsupported modes
assert(args.mode != GemmUniversalMode::kGemmSplitKParallel && "Sm80 EVT does not support SplitKParallel.");
assert(!(args.mode == GemmUniversalMode::kGemm && this->grid_tiled_shape.k() > 1 )
&& "Sm80 EVT does not support SplitKSerial.");
assert(args.mode != GemmUniversalMode::kArray && "Sm80 EVT does not support Array Gemm.");
}
/// Lightweight update given a subset of arguments.
void update(Arguments const &args)
{
CUTLASS_TRACE_HOST("GemmUniversalwithVisitor::Params::update()");
// Update input pointers
ptr_A = const_cast<void *>(args.ptr_A);
ptr_B = const_cast<void *>(args.ptr_B);
batch_stride_A = args.batch_stride_A;
batch_stride_B = args.batch_stride_B;
this->batch_stride_D = args.batch_stride_D;
ptr_gather_A_indices = const_cast<int *>(args.ptr_gather_A_indices);
ptr_gather_B_indices = const_cast<int *>(args.ptr_gather_B_indices);
output_op = FusionCallbacks::to_underlying_arguments(args.problem_size, args.epilogue, nullptr /*workspace*/);
problem_shape = make_shape(args.problem_size.m(), args.problem_size.n(), args.batch_count);
}
};
public:
//
// Device-only API
//
// Factory invocation
CUTLASS_DEVICE
static void invoke(
Params const &params,
SharedStorage &shared_storage)
{
GemmWithEpilogueVisitor op;
op(params, shared_storage);
}
/// Executes one GEMM
CUTLASS_DEVICE
void operator()(Params const &params, SharedStorage &shared_storage) {
ThreadblockSwizzle threadblock_swizzle;
run_with_swizzle(params, shared_storage, threadblock_swizzle);
}
/// Executes one GEMM with an externally-provided swizzling function
CUTLASS_DEVICE
void run_with_swizzle(Params const &params, SharedStorage &shared_storage, 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);
//
// Fetch pointers based on mode.
//
if (params.mode == GemmUniversalMode::kGemm) {
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;
}
__syncthreads();
// 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,
params.ptr_gather_A_indices);
typename Mma::IteratorB iterator_B(
params.params_B,
ptr_B,
{problem_size_k, params.problem_size.n()},
thread_idx,
tb_offset_B,
params.ptr_gather_B_indices);
// Broadcast the warp_id computed by lane 0 to ensure dependent code
// is compiled as warp-uniform.
int warp_idx = canonical_warp_idx_sync();
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
//
threadblock_tile_offset = threadblock_swizzle.get_tile_offset(params.swizzle_log_tile);
Epilogue epilogue(
params.output_op,
shared_storage.epilogue,
thread_idx,
warp_idx,
lane_idx);
// Execute the epilogue operator to update the destination tensor.
epilogue(accumulators, threadblock_tile_offset, params.problem_shape, thread_idx);
}
};
/////////////////////////////////////////////////////////////////////////////////////////////////
} // namespace kernel
} // namespace gemm
} // namespace cutlass
/////////////////////////////////////////////////////////////////////////////////////////////////