mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-03 21:21:22 +00:00
39dc25a9b8
* Refactor universal gemm policy. * Adapt example to refactor changes. * Introduce static encoding pattern * Adding shuffled encoding patterns. * Fix err in reverse tuple. * Add transpose_tile2d * Small refactoring + doc * Enable reading on contiguous dimension in all layouts. * Transpose A/B register tile if needed for comp v3 pipeline. * Take contiguous dim size when calculating dram vector load size. * A/B smem pack size taken from WarpGemm attributes * Update B LDS layout and setup tile distribution pattern at class level. * Fix static assert. * Fix errors in examples. * Formatting & fix IsTranspose * Fix VectorSize & refactor. * Add error loging messages. * Fix VecLoadSize and TranspseC for mem pipeline. * Update unit-tests & disable mem pipeline. * Clang format * Update include/ck_tile/core/tensor/tile_window.hpp Co-authored-by: jakpiase <jakub.piasecki@amd.com> * Fix compilation and reviewers comments. * Refactor unit-test. Fallback to non-universal gemm. Need to use GemmPipelineAGmemBGmemCRegV1 for now, since GemmKernel is now supporting also non-K major vector reads. --------- Co-authored-by: jakpiase <jakub.piasecki@amd.com>
356 lines
15 KiB
C++
356 lines
15 KiB
C++
// SPDX-License-Identifier: MIT
|
|
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
|
|
#pragma once
|
|
|
|
#include <sstream>
|
|
#include <gtest/gtest.h>
|
|
|
|
#include "ck_tile/core.hpp"
|
|
#include "ck_tile/host.hpp"
|
|
#include "ck_tile/host/kernel_launch.hpp"
|
|
#include "ck_tile/ops/epilogue.hpp"
|
|
#include "ck_tile/ops/gemm.hpp"
|
|
|
|
enum struct GemmPipelineType
|
|
{
|
|
Mem,
|
|
Comp
|
|
};
|
|
|
|
template <typename Tuple>
|
|
class TestCkTileGemmPipeline : public ::testing::Test
|
|
{
|
|
protected:
|
|
using ALayout = std::tuple_element_t<0, Tuple>;
|
|
using BLayout = std::tuple_element_t<1, Tuple>;
|
|
using CLayout = std::tuple_element_t<2, Tuple>;
|
|
using ADataType = std::tuple_element_t<3, Tuple>;
|
|
using BDataType = std::tuple_element_t<4, Tuple>;
|
|
using AccDataType = std::tuple_element_t<5, Tuple>;
|
|
using CDataType = std::tuple_element_t<6, Tuple>;
|
|
static constexpr auto Scheduler = std::tuple_element_t<7, Tuple>::value;
|
|
static constexpr auto PipelineType = std::tuple_element_t<8, Tuple>::value;
|
|
// TODO: expose tile size through test t-param ?
|
|
|
|
template <bool PadM, bool PadN, bool PadK>
|
|
void invoke_gemm(const ck_tile::GemmHostArgs& args, const ck_tile::stream_config& s)
|
|
{
|
|
// TODO: This should be parameterized in tests
|
|
constexpr ck_tile::index_t M_Tile = 128;
|
|
constexpr ck_tile::index_t N_Tile = 128;
|
|
constexpr ck_tile::index_t K_Tile = 32;
|
|
|
|
constexpr ck_tile::index_t M_Warp = 2;
|
|
constexpr ck_tile::index_t N_Warp = 2;
|
|
constexpr ck_tile::index_t K_Warp = 1;
|
|
|
|
constexpr ck_tile::index_t M_Warp_Tile = 32;
|
|
constexpr ck_tile::index_t N_Warp_Tile = 32;
|
|
constexpr ck_tile::index_t K_Warp_Tile = 8;
|
|
|
|
constexpr bool kPadM = PadM;
|
|
constexpr bool kPadN = PadN;
|
|
constexpr bool kPadK = PadK;
|
|
|
|
// TODO: For now - but this should also be a test parameter
|
|
constexpr bool TransposeC = false;
|
|
|
|
constexpr int kBlockPerCu = 1;
|
|
|
|
// ===============================================
|
|
|
|
using GemmShape =
|
|
ck_tile::TileGemmShape<ck_tile::sequence<M_Tile, N_Tile, K_Tile>,
|
|
ck_tile::sequence<M_Warp, N_Warp, K_Warp>,
|
|
ck_tile::sequence<M_Warp_Tile, N_Warp_Tile, K_Warp_Tile>>;
|
|
using TilePartitioner = ck_tile::GemmTile2DPartitioner<GemmShape>;
|
|
|
|
using GemmEpilogue = ck_tile::Default2DEpilogue<
|
|
ck_tile::Default2DEpilogueProblem<AccDataType, CDataType, kPadM, kPadN>>;
|
|
|
|
using Traits = ck_tile::TileGemmTraits<kPadM, kPadN, kPadK, ALayout, BLayout, CLayout>;
|
|
using GemmUniversalTraits = ck_tile::
|
|
TileGemmUniversalTraits<kPadM, kPadN, kPadK, ALayout, BLayout, CLayout, TransposeC>;
|
|
|
|
using GemmPipelineProblem =
|
|
ck_tile::GemmPipelineProblem<ADataType, BDataType, AccDataType, GemmShape, Traits>;
|
|
|
|
using BaseGemmPipeline =
|
|
std::conditional_t<PipelineType == GemmPipelineType::Mem,
|
|
ck_tile::BaseGemmPipelineAgBgCrMem<GemmPipelineProblem>,
|
|
ck_tile::BaseGemmPipelineAgBgCrCompV3<GemmPipelineProblem>>;
|
|
|
|
const ck_tile::index_t k_grain = args.k_batch * K_Tile;
|
|
const ck_tile::index_t K_split = (args.K + k_grain - 1) / k_grain * 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);
|
|
|
|
const auto Run = [&](const auto has_hot_loop_, const auto tail_number_) {
|
|
constexpr bool has_hot_loop_v = has_hot_loop_.value;
|
|
constexpr auto tail_number_v = tail_number_.value;
|
|
|
|
using UniversalGemmProblem = ck_tile::UniversalGemmPipelineProblem<ADataType,
|
|
BDataType,
|
|
AccDataType,
|
|
GemmShape,
|
|
GemmUniversalTraits,
|
|
Scheduler,
|
|
has_hot_loop_v,
|
|
tail_number_v>;
|
|
|
|
using GemmPipeline = std::conditional_t<
|
|
PipelineType == GemmPipelineType::Mem,
|
|
ck_tile::GemmPipelineAgBgCrMem<UniversalGemmProblem,
|
|
ck_tile::UniversalGemmPipelineAgBgCrPolicy>,
|
|
ck_tile::GemmPipelineAgBgCrCompV3<UniversalGemmProblem,
|
|
ck_tile::UniversalGemmPipelineAgBgCrPolicy>>;
|
|
|
|
using Kernel = ck_tile::GemmKernel<TilePartitioner, GemmPipeline, GemmEpilogue>;
|
|
auto kargs = Kernel::MakeKernelArgs(args);
|
|
|
|
const dim3 grids = Kernel::GridSize(args.M, args.N, args.k_batch);
|
|
constexpr 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:"
|
|
<< " grid: {" << grids.x << ", " << grids.y << ", " << grids.z << "}"
|
|
<< ", blocks: {" << blocks.x << ", " << blocks.y << ", " << blocks.z
|
|
<< "}" << std::endl;
|
|
}
|
|
|
|
ck_tile::launch_kernel(
|
|
s, ck_tile::make_kernel<blocks.x, kBlockPerCu>(Kernel{}, grids, blocks, 0, kargs));
|
|
};
|
|
|
|
if(has_hot_loop)
|
|
{
|
|
if constexpr(PipelineType == GemmPipelineType::Comp)
|
|
{
|
|
if(tail_num == ck_tile::TailNumber::Full)
|
|
{
|
|
Run(ck_tile::bool_constant<true>{},
|
|
ck_tile::integral_constant<ck_tile::TailNumber,
|
|
ck_tile::TailNumber::Full>{});
|
|
}
|
|
else
|
|
{
|
|
std::ostringstream err;
|
|
err << "For compute pipeline tail number should always be Full, but have \""
|
|
<< tail_num << "\" which is not supported! PrefetchStages: "
|
|
<< BaseGemmPipeline::PrefetchStages << "\n File: " << __FILE__ << ":"
|
|
<< __LINE__ << ", in function: " << __func__;
|
|
throw std::runtime_error(err.str());
|
|
}
|
|
}
|
|
|
|
if constexpr(PipelineType == GemmPipelineType::Mem)
|
|
{
|
|
// Tail pipeline One to Seven
|
|
if(tail_num == ck_tile::TailNumber::One)
|
|
{
|
|
Run(ck_tile::bool_constant<true>{},
|
|
ck_tile::integral_constant<ck_tile::TailNumber,
|
|
ck_tile::TailNumber::One>{});
|
|
}
|
|
else if(tail_num == ck_tile::TailNumber::Full)
|
|
{
|
|
Run(ck_tile::bool_constant<true>{},
|
|
ck_tile::integral_constant<ck_tile::TailNumber,
|
|
ck_tile::TailNumber::Full>{});
|
|
}
|
|
|
|
if constexpr(BaseGemmPipeline::PrefetchStages > 2)
|
|
{
|
|
if(tail_num == ck_tile::TailNumber::Two)
|
|
{
|
|
Run(ck_tile::bool_constant<true>{},
|
|
ck_tile::integral_constant<ck_tile::TailNumber,
|
|
ck_tile::TailNumber::Two>{});
|
|
}
|
|
}
|
|
if constexpr(BaseGemmPipeline::PrefetchStages > 3)
|
|
{
|
|
if(tail_num == ck_tile::TailNumber::Three)
|
|
{
|
|
Run(ck_tile::bool_constant<true>{},
|
|
ck_tile::integral_constant<ck_tile::TailNumber,
|
|
ck_tile::TailNumber::Three>{});
|
|
}
|
|
}
|
|
if constexpr(BaseGemmPipeline::PrefetchStages > 4)
|
|
{
|
|
if(tail_num == ck_tile::TailNumber::Four)
|
|
{
|
|
Run(ck_tile::bool_constant<true>{},
|
|
ck_tile::integral_constant<ck_tile::TailNumber,
|
|
ck_tile::TailNumber::Four>{});
|
|
}
|
|
}
|
|
if constexpr(BaseGemmPipeline::PrefetchStages > 5)
|
|
{
|
|
if(tail_num == ck_tile::TailNumber::Five)
|
|
{
|
|
Run(ck_tile::bool_constant<true>{},
|
|
ck_tile::integral_constant<ck_tile::TailNumber,
|
|
ck_tile::TailNumber::Five>{});
|
|
}
|
|
}
|
|
if constexpr(BaseGemmPipeline::PrefetchStages > 6)
|
|
{
|
|
if(tail_num == ck_tile::TailNumber::Six)
|
|
{
|
|
Run(ck_tile::bool_constant<true>{},
|
|
ck_tile::integral_constant<ck_tile::TailNumber,
|
|
ck_tile::TailNumber::Six>{});
|
|
}
|
|
}
|
|
if constexpr(BaseGemmPipeline::PrefetchStages > 7)
|
|
{
|
|
if(tail_num == ck_tile::TailNumber::Seven)
|
|
{
|
|
Run(ck_tile::bool_constant<true>{},
|
|
ck_tile::integral_constant<ck_tile::TailNumber,
|
|
ck_tile::TailNumber::Seven>{});
|
|
}
|
|
}
|
|
}
|
|
}
|
|
else
|
|
{
|
|
// Tail number always Full - #PrefetchStages
|
|
if(tail_num == ck_tile::TailNumber::Full)
|
|
{
|
|
Run(ck_tile::bool_constant<false>{},
|
|
ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Full>{});
|
|
}
|
|
else
|
|
{
|
|
std::ostringstream err;
|
|
err << "When there's no hot loop, this tail number \"" << tail_num
|
|
<< "\" is not supported! " << __FILE__ << ":" << __LINE__
|
|
<< ", in function: " << __func__;
|
|
throw std::runtime_error(err.str());
|
|
}
|
|
}
|
|
}
|
|
|
|
public:
|
|
std::vector<int> k_batches_;
|
|
|
|
void SetUp() override { k_batches_ = {1}; }
|
|
|
|
template <bool PadM = true, bool PadN = true, bool PadK = true>
|
|
void Run(const int M,
|
|
const int N,
|
|
const int K,
|
|
const int StrideA = 0,
|
|
const int StrideB = 0,
|
|
const int StrideC = 0)
|
|
{
|
|
for(auto kb : k_batches_)
|
|
{
|
|
RunSingle<PadM, PadN, PadK>(M, N, K, StrideA, StrideB, StrideC, kb);
|
|
}
|
|
}
|
|
|
|
template <bool PadM, bool PadN, bool PadK>
|
|
void RunSingle(const int M,
|
|
const int N,
|
|
const int K,
|
|
const int StrideA,
|
|
const int StrideB,
|
|
const int StrideC,
|
|
int kbatch = 1)
|
|
{
|
|
using namespace ck_tile::literals;
|
|
|
|
auto f_host_tensor_descriptor = [](std::size_t row,
|
|
std::size_t col,
|
|
std::size_t stride,
|
|
auto layout) {
|
|
if constexpr(std::is_same_v<decltype(layout), ck_tile::tensor_layout::gemm::RowMajor>)
|
|
{
|
|
return ck_tile::HostTensorDescriptor({row, col}, {stride, 1_uz});
|
|
}
|
|
else
|
|
{
|
|
return ck_tile::HostTensorDescriptor({row, col}, {1_uz, stride});
|
|
}
|
|
};
|
|
|
|
auto f_get_default_stride =
|
|
[](std::size_t row, std::size_t col, std::size_t stride, auto layout) {
|
|
if(stride == 0)
|
|
{
|
|
// give a chance if stride is zero, return a default packed stride
|
|
if constexpr(std::is_same_v<decltype(layout),
|
|
ck_tile::tensor_layout::gemm::RowMajor>)
|
|
{
|
|
return col;
|
|
}
|
|
else
|
|
{
|
|
return row;
|
|
}
|
|
}
|
|
else
|
|
return stride;
|
|
};
|
|
|
|
std::size_t stride_A = f_get_default_stride(M, K, StrideA, ALayout{});
|
|
std::size_t stride_B = f_get_default_stride(K, N, StrideB, BLayout{});
|
|
std::size_t stride_C = f_get_default_stride(M, N, StrideC, CLayout{});
|
|
|
|
ck_tile::HostTensor<ADataType> a_m_k(f_host_tensor_descriptor(M, K, stride_A, ALayout{}));
|
|
ck_tile::HostTensor<BDataType> b_k_n(f_host_tensor_descriptor(K, N, stride_B, BLayout{}));
|
|
ck_tile::HostTensor<CDataType> c_m_n_dev_result(
|
|
f_host_tensor_descriptor(M, N, stride_C, CLayout{}));
|
|
|
|
ck_tile::FillUniformDistributionIntegerValue<ADataType>{-5, 5}(a_m_k);
|
|
ck_tile::FillUniformDistributionIntegerValue<BDataType>{-5, 5}(b_k_n);
|
|
|
|
ck_tile::DeviceMem a_m_k_dev_buf(a_m_k.get_element_space_size_in_bytes());
|
|
ck_tile::DeviceMem b_k_n_dev_buf(b_k_n.get_element_space_size_in_bytes());
|
|
ck_tile::DeviceMem c_m_n_dev_buf(c_m_n_dev_result.get_element_space_size_in_bytes());
|
|
|
|
a_m_k_dev_buf.ToDevice(a_m_k.data());
|
|
b_k_n_dev_buf.ToDevice(b_k_n.data());
|
|
c_m_n_dev_buf.SetZero();
|
|
c_m_n_dev_result.SetZero();
|
|
|
|
ck_tile::GemmHostArgs args;
|
|
args.a_ptr = a_m_k_dev_buf.GetDeviceBuffer();
|
|
args.b_ptr = b_k_n_dev_buf.GetDeviceBuffer();
|
|
args.c_ptr = c_m_n_dev_buf.GetDeviceBuffer();
|
|
args.k_batch = kbatch;
|
|
args.M = M;
|
|
args.N = N;
|
|
args.K = K;
|
|
args.stride_A = stride_A;
|
|
args.stride_B = stride_B;
|
|
args.stride_C = stride_C;
|
|
|
|
invoke_gemm<PadM, PadN, PadK>(args, ck_tile::stream_config{nullptr, false});
|
|
|
|
c_m_n_dev_buf.FromDevice(c_m_n_dev_result.data());
|
|
bool pass = true;
|
|
|
|
ck_tile::HostTensor<CDataType> c_m_n_host_ref(
|
|
f_host_tensor_descriptor(M, N, stride_C, CLayout{}));
|
|
c_m_n_host_ref.SetZero();
|
|
|
|
ck_tile::reference_gemm<ADataType, BDataType, AccDataType, CDataType>(
|
|
a_m_k, b_k_n, c_m_n_host_ref);
|
|
|
|
pass = ck_tile::check_err(c_m_n_dev_result, c_m_n_host_ref);
|
|
EXPECT_TRUE(pass);
|
|
}
|
|
};
|