Files
composable_kernel/example/ck_tile/03_gemm/universal_gemm_invoker.hpp
SamiAario-AMD 1acd8e041c [CK Tile] gemm splitk two stage (#2697)
* Fix a typo

* Use std::variant to call run_gemm_example_with_layouts with the available layout variant combinations

* Use a unified run_gemm_example_prec_type for basic gemm and universal gemm

* Factor out run_gemm_example_prec_type

* Refactor argument parsing in gemm_splitk_two_stage_reduce.cpp

* Parse arguments outside of create_args

* Move the gemm operators to separate structs to facilitate their reuse

* Move the invokers to separate files to facilitate their reuse

* Rename the invoker files for consistency with the examples that use them

* Add fp32 support to the elementwise examples, and produce an error message for unsupported types

* Get rid of four unused variables

* Make two variables const

* Add support for different input-output type combinations in elementwise examples

* Test support for different input and output types in elementwise examples

* Add support for different operations in the elementwise unary tests

* Add support for UnaryConvert in the elementwise unary tests

* Add support for bf16 in elementwise examples, excluding unsupported type combinations

* Make some operator parameters const in ElementWiseKernel

* Remove some unnecessary include statements

* Implement a two-stage GEMM that does a type conversion in the second stage using the elementwise kernel

* Clear workspace instead of output when flushing the cache in SplitKTwoStageInvoker::gemm

* Fix formatting issues reported by clang

* Add back CK_TILE_USE_WMMA related changes

* Use the right prec type for bf16 in the universal GEMM and two stage split K examples

* Add some brackets

* Add some brackets

* Separate the clearing of the GEMM output memory from the cache flushing in the universal GEMM example

* Separate the clearing of the GEMM output memory from the cache flushing in the split K two stage example

* Fix formatting

* No need to call SetZero on ws_m_n_dev_buf here, as clear_gemm_output now does this as part of the kernel preprocessing

* Add fp16 data type to splitk two stage example

* Add preprocessing with optional cache flushing and clearing of output for k_batch > 1 to the basic GEMM example
2025-09-04 14:33:44 +03:00

198 lines
9.4 KiB
C++

// SPDX-License-Identifier: MIT
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <functional>
#include "gemm_utils.hpp"
struct UniversalInvoker
{
template <typename GemmConfig,
typename ADataType,
typename BDataType,
typename DsDataType,
typename AccDataType,
typename CDataType,
typename ALayout,
typename BLayout,
typename DsLayout,
typename ELayout,
bool Persistent,
typename CDEElementWise>
static float gemm(const ck_tile::GemmHostArgs& args, const ck_tile::stream_config& s)
{
using GemmShape = ck_tile::TileGemmShape<
ck_tile::sequence<GemmConfig::M_Tile, GemmConfig::N_Tile, GemmConfig::K_Tile>,
ck_tile::sequence<GemmConfig::M_Warp, GemmConfig::N_Warp, GemmConfig::K_Warp>,
ck_tile::
sequence<GemmConfig::M_Warp_Tile, GemmConfig::N_Warp_Tile, GemmConfig::K_Warp_Tile>,
GemmConfig::PermuteA,
GemmConfig::PermuteB>;
using TilePartitioner =
ck_tile::GemmSpatiallyLocalTilePartitioner<GemmShape,
GemmConfig::TileParitionerGroupNum,
GemmConfig::TileParitionerM01>;
using Traits = ck_tile::TileGemmTraits<GemmConfig::kPadM,
GemmConfig::kPadN,
GemmConfig::kPadK,
ALayout,
BLayout,
ELayout,
GemmConfig::NumWaveGroups>;
using GemmUniversalTraits =
ck_tile::TileGemmUniversalTraits<GemmConfig::kPadM,
GemmConfig::kPadN,
GemmConfig::kPadK,
GemmConfig::DoubleSmemBuffer,
ALayout,
BLayout,
ELayout,
GemmConfig::TransposeC,
GemmConfig::UseStructuredSparsity,
Persistent,
GemmConfig::NumWaveGroups,
GemmConfig::Preshuffle>;
using GemmPipelineProblem =
ck_tile::GemmPipelineProblem<ADataType, BDataType, AccDataType, GemmShape, Traits>;
using BaseGemmPipeline = typename PipelineTypeTraits<
GemmConfig::Pipeline>::template UniversalGemmPipeline<GemmPipelineProblem>;
const ck_tile::index_t k_grain = args.k_batch * GemmConfig::K_Tile;
const ck_tile::index_t K_split = (args.K + k_grain - 1) / k_grain * GemmConfig::K_Tile;
const ck_tile::index_t num_loop = TilePartitioner::GetLoopNum(K_split);
const bool has_hot_loop = BaseGemmPipeline::BlockHasHotloop(num_loop);
const ck_tile::TailNumber tail_num = BaseGemmPipeline::GetBlockLoopTailNum(num_loop);
float ave_time{0};
const auto Run = [&](const auto has_hot_loop_,
const auto tail_number_,
const auto memory_operation_) {
constexpr bool has_hot_loop_v = has_hot_loop_.value;
constexpr auto tail_number_v = tail_number_.value;
constexpr auto scheduler = GemmConfig::Scheduler;
constexpr auto memory_operation = memory_operation_.value;
using UniversalGemmProblem = ck_tile::UniversalGemmPipelineProblem<ADataType,
BDataType,
AccDataType,
GemmShape,
GemmUniversalTraits,
scheduler,
has_hot_loop_v,
tail_number_v>;
using GemmPipeline = typename PipelineTypeTraits<
GemmConfig::Pipeline>::template GemmPipeline<UniversalGemmProblem>;
using GemmEpilogue = ck_tile::CShuffleEpilogue<
ck_tile::CShuffleEpilogueProblem<ADataType,
BDataType,
DsDataType,
AccDataType,
CDataType,
DsLayout,
ELayout,
CDEElementWise,
TilePartitioner::MPerBlock,
TilePartitioner::NPerBlock,
GemmConfig::M_Warp,
GemmConfig::N_Warp,
GemmConfig::M_Warp_Tile,
GemmConfig::N_Warp_Tile,
GemmConfig::K_Warp_Tile,
UniversalGemmProblem::TransposeC,
memory_operation,
GemmConfig::NumWaveGroups>>;
using Kernel = ck_tile::GemmKernel<TilePartitioner, GemmPipeline, GemmEpilogue>;
auto kargs = Kernel::MakeKernelArgs(args);
const dim3 grids = Persistent ? Kernel::MaxOccupancyGridSize(s)
: Kernel::GridSize(args.M, args.N, args.k_batch);
const dim3 blocks = Kernel::BlockSize();
if(!Kernel::IsSupportedArgument(kargs))
{
throw std::runtime_error("Wrong! Arguments not supported! Skipping gemm!\n");
}
if(s.log_level_ > 0)
{
std::cout << "Launching kernel with args: " << Kernel::GetName() << '\n'
<< "shape: " << GemmShape::GetName() << '\n'
<< "problem: " << UniversalGemmProblem::GetName() << '\n'
<< "pipeline: " << GemmPipeline::GetName() << '\n'
<< "grid: {" << grids.x << ", " << grids.y << ", " << grids.z << "}"
<< ", blocks: {" << blocks.x << ", " << blocks.y << ", " << blocks.z
<< "}" << std::endl;
}
// Declare rotating_mem_ptr here so it stays in scope until it is needed
std::unique_ptr<ck_tile::RotatingMemWrapper<ADataType, BDataType>> rotating_mem_ptr;
std::function<void()> preprocess;
auto clear_gemm_output = [&]() {
if(args.k_batch > 1)
hipGetErrorString(hipMemsetAsync(
args.e_ptr, 0, args.M * args.N * sizeof(CDataType), s.stream_id_));
};
if(s.flush_cache_)
{
std::cout << "Flushing cache..." << std::endl;
ck_tile::HostTensor<ADataType> a_m(ck_tile::host_tensor_descriptor(
args.M, args.K, args.stride_A, is_row_major(ALayout{})));
ck_tile::HostTensor<BDataType> b_n(ck_tile::host_tensor_descriptor(
args.K, args.N, args.stride_B, is_row_major(BLayout{})));
auto size_a_buffer = a_m.get_element_space_size_in_bytes();
auto size_b_buffer = b_n.get_element_space_size_in_bytes();
rotating_mem_ptr =
std::make_unique<ck_tile::RotatingMemWrapper<ADataType, BDataType>>(
kargs.as_ptr[0],
kargs.bs_ptr[0],
s.rotating_count_,
size_a_buffer,
size_b_buffer);
rotating_mem_ptr->Print();
preprocess = [&]() {
ck_tile::flush_icache();
rotating_mem_ptr->Next();
clear_gemm_output();
};
}
else
{
preprocess = clear_gemm_output;
}
return ck_tile::launch_kernel_time_mask(
s,
preprocess,
ck_tile::make_kernel<GemmConfig::kBlockPerCu>(Kernel{}, grids, blocks, 0, kargs));
};
const auto RunSplitk = [&](const auto has_hot_loop_, const auto tail_number_) {
if(args.k_batch == 1)
{
Run(has_hot_loop_, tail_number_, MemoryOpSet{});
}
else
{
Run(has_hot_loop_, tail_number_, MemoryOpAtomicAdd{});
}
};
BaseGemmPipeline::TailHandler(RunSplitk, has_hot_loop, tail_num);
return ave_time;
}
};