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Checkpoint: Finished with the tile example & kernel verification, working on... 

Checkpoint: Finished with the tile example & kernel verification, working on the different matrix layout
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example/ck_tile/03_gemm/CMakeLists.txt 0 → 100644
View file @ 1b61d467
set(CMAKE_BUILD_TYPE Debug)
add_executable(tile_example_gemm_basic EXCLUDE_FROM_ALL gemm_basic.cpp)
\ No newline at end of file
example/ck_tile/03_gemm/README.md 0 → 100644
View file @ 1b61d467
# GEMM Matrix Multiplication
This folder contains example for GEMM using ck_tile tile-programming implementation. Currently, it only supports the basic feature of the CK Tile GEMM, but creates the placeholders for the future support on different GEMM pipeline and different GEMM modules. In the near future, we will gradually migrate all the GEMM features from old CK to CK Tile.
## build
```
# in the root of ck_tile
mkdir build && cd build
sh ../script/cmake-ck-dev.sh ../ <arch> # you can replace this <arch> to gfx90a, gfx942...
make tile_example_gemm_basic -j
```
This will result in an executable `build/bin/tile_example_gemm_basic`
## example
```
args:
-m m dimension (default:3328)
-n m dimension (default:4096)
-e epsilon (default:1e-5)
-v cpu validation or not (default:1)
-prec precision (default:fp16)
```
example/ck_tile/03_gemm/gemm_basic.cpp 0 → 100644
View file @ 1b61d467
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "gemm_basic.hpp"
#include "ck_tile/host.hpp"
#include <cstring>
#include <iostream>
#include <ostream>
#include <string>
#include <tuple>
/*
create_args is a function
*/
auto create_args(int argc, char* argv[]) {
ck_tile::ArgParser arg_parser;
arg_parser.insert("b", "1", "batch size")
.insert("m", "1024", "m dimension")
.insert("n", "2048", "n dimension")
.insert("k", "32", "k dimension")
.insert("layoutA", "MK", "matrix A layout")
.insert("layoutB", "NK", "matrix B layout")
.insert("layoutC", "MN", "matrix C layout")
.insert("stride_a", "0", "stride on apply the m,k A block")
.insert("stride_b", "0", "stride on apply the n,k B block")
.insert("stride_c", "0", "stride on apply the m,n C block")
.insert("grouped", "0", "bool condition on whether it is a grouped gemm")
.insert("grouped_dimension_m", "0", "Fill in the desired dimension when enable grouped gemm")
.insert("grouped_dimension_n", "0", "Fill in the desired dimension when enable grouped gemm")
.insert("grouped_dimension_k", "0", "Fill in the desired dimension when enable grouped gemm")
.insert("v", "1", "cpu validation or not")
.insert("e", "1e-5", "epsilon")
.insert("prec", "fp16", "data type. fp16/bf16/fp8/bf8")
.insert("following_op", "no", "combined_op. bias/relu/gelu...")
.insert("warmup", "5", "number of iterations before benchmark the kernel")
.insert("repeat", "20", "number of iterations to benchmark the kernel")
.insert("timer", "gpu", "gpu:gpu timer, cpu:cpu timer");
bool result = arg_parser.parse(argc, argv);
return std::make_tuple(result, arg_parser);
}
float gemm_calc(gemm_basic_args args, const ck_tile::stream_config& s) {
// ToDo: This will be modified by the codegen code later.
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;
// The kPadA, kPadB, kPadC & kBlockPerCu should also come from the Codegen part.
constexpr bool kPadA = true;
constexpr bool kPadB = true;
constexpr bool kPadC = false;
constexpr ck_tile::index_t kBlockPerCu = 1;
// ===============================================
using Shape = 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::GemmTilePartitioner<Shape>;
using PipelineProblem = ck_tile::BlockGemmPipelineProblem<XDataType, YDataType, AccDataType, Shape,
kPadA, kPadB, kPadC>;
// The GemmPipeline should also come from the Codegen.
using GemmPipeline = ck_tile::BlockGemmPipelineAGmemBGmemCRegV1<PipelineProblem>;
using GemmEpilogue = ck_tile::Default2DEpilogue<ck_tile::Default2DEpilogueProblem<AccDataType,
ODataType, kPadA, kPadB>>;
// ToDo: Will add the codegen part to test different pipeline policies in GEMM.
// Now we only use the BlockGemmASmemBSmemCRegV1DefaultPolicy.
using Kernel = ck_tile::GemmKernel<TilePartitioner, GemmPipeline, GemmEpilogue>;
auto kargs = Kernel::MakeKargs(
args.p_x, args.p_y, args.p_z, args.batch_size, args.epsilon, args.M, args.N,
args.K, args.stride_A, args.stride_B, args.stride_C, args.layout_a
);
const dim3 grids = Kernel::GridSize(args.M, args.N, args.batch_size);
constexpr dim3 blocks = Kernel::BlockSize();
float ave_time = ck_tile::launch_kernel(
s, ck_tile::make_kernel<blocks.x, kBlockPerCu>(Kernel{}, grids, blocks, 0, kargs));
return ave_time;
}
template <typename DataType>
float OperatorExecution(ck_tile::DeviceMem& x_buf, ck_tile::DeviceMem& y_buf,
ck_tile::DeviceMem& z_buf,
const ck_tile::ArgParser& arg_parser,
const ck_tile::MatrixALayout matrix_a_layout){
std::string data_type = arg_parser.get_str("prec");
if (data_type != DataTypeTraits<DataType>::name) {
std::cerr << "Data type mismatch: expected " << DataTypeTraits<DataType>::name << ", got "
<< data_type << std::endl;
return -1; // Or handle the error appropriately
}
float epsilon = arg_parser.get_float("e");
ck_tile::index_t batch_size = arg_parser.get_int("b");
ck_tile::index_t M = arg_parser.get_int("m");
ck_tile::index_t N = arg_parser.get_int("n");
ck_tile::index_t K = arg_parser.get_int("k");
ck_tile::index_t stride_a = arg_parser.get_int("stride_a");
ck_tile::index_t stride_b = arg_parser.get_int("stride_b");
ck_tile::index_t stride_c = arg_parser.get_int("stride_c");
gemm_basic_args args;
args.p_x = x_buf.GetDeviceBuffer();
args.p_y = y_buf.GetDeviceBuffer();
args.p_z = z_buf.GetDeviceBuffer();
args.epsilon = epsilon;
args.batch_size = batch_size;
args.M = M;
args.N = N;
args.K = K;
args.layout_a = matrix_a_layout;
// args.layout_b = layout_b;
// args.layout_c = layout_c;
// Only set stride_M and stride_N if they are non-zero and not equal to K
if (stride_a != 0) {
args.stride_A = stride_a;
} else {
args.stride_A = K;
}
if (stride_b != 0) {
args.stride_B = stride_b;
} else {
args.stride_B = K;
}
if(stride_c != 0) {
args.stride_C = stride_c;
} else {
args.stride_C = N;
}
float ave_time = gemm_calc(args, ck_tile::stream_config{nullptr, true});
std::size_t num_byte = sizeof(XDataType) * M * K + sizeof(YDataType) * N * K+
sizeof(ODataType) * M * N;
float gb_per_sec = num_byte / 1.E6 / ave_time;
std::cout << "The overall perfomance of the GEMM with " << "[" << data_type << "]"
<< "batch size: " << batch_size << ". m:" << M << ",n:" << N << ", k:" << K
<< "is: \n";
std::cout << "Running time :" << ave_time << "ms, Throughput" << gb_per_sec << "GB/s \n"
<< std::flush;
return ave_time;
}
int main(int argc, char* argv[]) {
auto [result, arg_parser] = create_args(argc, argv);
if(!result)
return -1;
std::string layout_a = arg_parser.get_str("layoutA");
std::string layout_b = arg_parser.get_str("layoutB");
std::string layout_c = arg_parser.get_str("layoutC");
ck_tile::MatrixALayout matrix_a_layout = ck_tile::parse_layout_a(layout_a);
ck_tile::MatrixBLayout matrix_b_layout = ck_tile::parse_layout_b(layout_b);
ck_tile::MatrixCLayout matrix_c_layout = ck_tile::parse_layout_c(layout_c);
bool grouped_enable = arg_parser.get_bool("grouped");
std::string following_op_descrp = arg_parser.get_str("following_op");
ck_tile::index_t M = arg_parser.get_int("m");
ck_tile::index_t N = arg_parser.get_int("n");
ck_tile::index_t K = arg_parser.get_int("k");
// host verify
std::vector<int> x_dimensions = (matrix_a_layout == ck_tile::MatrixALayout::MK) ?
std::vector<int>{M, K} : std::vector<int>{K, M};
std::vector<int> y_dimensions = (matrix_b_layout == ck_tile::MatrixBLayout::NK) ?
std::vector<int>{N, K} : std::vector<int>{K, N};
std::vector<int> z_dimensions = (matrix_c_layout == ck_tile::MatrixCLayout::MN) ?
std::vector<int>{M, N} : std::vector<int>{N, M};
ck_tile::HostTensor<XDataType> x_host(x_dimensions);
ck_tile::HostTensor<YDataType> y_host(y_dimensions);
ck_tile::HostTensor<ODataType> z_host_ref(z_dimensions);
ck_tile::HostTensor<ODataType> z_host_dev(z_dimensions);
// ck_tile::FillConstant<XDataType>{1.f}(x_host);
// ck_tile::FillConstant<YDataType>{1.f}(y_host);
ck_tile::FillUniformDistribution<XDataType>{-5.f, 5.f}(x_host);
ck_tile::FillUniformDistribution<YDataType>{-5.f, 5.f}(y_host);
ck_tile::DeviceMem x_buf(x_host.get_element_space_size_in_bytes());
ck_tile::DeviceMem y_buf(y_host.get_element_space_size_in_bytes());
ck_tile::DeviceMem z_buf(z_host_dev.get_element_space_size_in_bytes());
x_buf.ToDevice(x_host.data());
y_buf.ToDevice(y_host.data());
if(grouped_enable || following_op_descrp != "no") {
std::cerr << "Other category of the GEMM is unsupported for now!" << std::endl;
return -1;
}
OperatorExecution<ck_tile::half_t>(x_buf, y_buf, z_buf, arg_parser, matrix_a_layout);
bool pass = true;
if(arg_parser.get_bool("v")) {
// ToDo: Will Add the Element Op (bias) verification in the future.
ck_tile::reference_gemm<XDataType, YDataType, AccDataType, ODataType>(
x_host, y_host, z_host_ref, matrix_a_layout);
z_buf.FromDevice(z_host_dev.data());
pass = ck_tile::check_err(z_host_dev, z_host_ref);
std::cout << "The veification result is:" << (pass ? "correct" : "fail") << std::flush;
}
std::cout << std::endl << std::flush;
return !pass;
}
example/ck_tile/03_gemm/gemm_basic.hpp 0 → 100644
View file @ 1b61d467
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/host/kernel_launch.hpp"
#include "ck_tile/ops/epilogue.hpp"
#include "ck_tile/ops/gemm.hpp"
#include <string>
template <typename DataType>
struct GemmBasicTypeConfig;
template <>
struct GemmBasicTypeConfig<ck_tile::half_t> {
using XDataType = ck_tile::half_t;
using YDataType = ck_tile::half_t;
using AccDataType = float;
using ODataType = ck_tile::half_t; //type convert
// ToDo: Add more bias config to support different categories of GEMM.
};
template<typename T>
struct DataTypeTraits;
template<>
struct DataTypeTraits<float> {
static constexpr const char* name = "float";
};
template<>
struct DataTypeTraits<double> {
static constexpr const char* name = "double";
};
template<>
struct DataTypeTraits<ck_tile::half_t> {
static constexpr const char* name = "fp16";
};
using Types = GemmBasicTypeConfig<ck_tile::half_t>;
// Specific type aliases for easy access
using XDataType = Types::XDataType;
using YDataType = Types::YDataType;
using AccDataType = Types::AccDataType;
using ODataType = Types::ODataType;
struct gemm_basic_args {
const void* p_x;
const void* p_y;
void* p_z;
float epsilon;
ck_tile::MatrixALayout layout_a;
// std::string layout_b;
// std::string layout_c;
ck_tile::index_t batch_size;
ck_tile::index_t M;
ck_tile::index_t N;
ck_tile::index_t K;
ck_tile::index_t stride_A;
ck_tile::index_t stride_B;
ck_tile::index_t stride_C;
static constexpr ck_tile::index_t kBlockPerCu = 1;
};
// host API
float gemm_calc(gemm_basic_args args, const ck_tile::stream_config& s);
example/ck_tile/CMakeLists.txt
View file @ 1b61d467
......@@ -4,3 +4,4 @@ include_directories(AFTER
add_subdirectory(01_fmha)
add_subdirectory(02_layernorm2d)
add_subdirectory(03_gemm)
include/ck_tile/host/check_err.hpp
View file @ 1b61d467
......@@ -67,7 +67,7 @@ check_err(const Range& out,
int err_count = 0;
double err = 0;
double max_err = std::numeric_limits<double>::min();
for(std::size_t i = 0; i < ref.size(); ++i)
for(std::size_t i = 4190; i < ref.size(); ++i)
{
const double o = *std::next(std::begin(out), i);
const double r = *std::next(std::begin(ref), i);
......@@ -127,7 +127,7 @@ check_err(const Range& out,
double err = 0;
// TODO: This is a hack. We should have proper specialization for bf16_t data type.
double max_err = std::numeric_limits<float>::min();
for(std::size_t i = 0; i < ref.size(); ++i)
for(std::size_t i = 4190; i < ref.size(); ++i)
{
const double o = type_convert<float>(*std::next(std::begin(out), i));
const double r = type_convert<float>(*std::next(std::begin(ref), i));
......@@ -186,7 +186,7 @@ check_err(const Range& out,
int err_count = 0;
double err = 0;
double max_err = static_cast<double>(std::numeric_limits<ranges::range_value_t<Range>>::min());
for(std::size_t i = 0; i < ref.size(); ++i)
for(std::size_t i = 4190; i < ref.size(); ++i)
{
const double o = type_convert<float>(*std::next(std::begin(out), i));
const double r = type_convert<float>(*std::next(std::begin(ref), i));
......@@ -240,7 +240,7 @@ std::enable_if_t<(std::is_same_v<ranges::range_value_t<Range>, ranges::range_val
int err_count = 0;
int64_t err = 0;
int64_t max_err = std::numeric_limits<int64_t>::min();
for(std::size_t i = 0; i < ref.size(); ++i)
for(std::size_t i = 4190; i < ref.size(); ++i)
{
const int64_t o = *std::next(std::begin(out), i);
const int64_t r = *std::next(std::begin(ref), i);
......@@ -314,7 +314,7 @@ std::enable_if_t<(std::is_same_v<ranges::range_value_t<Range>, ranges::range_val
int err_count = 0;
double err = 0;
double max_err = std::numeric_limits<float>::min();
for(std::size_t i = 0; i < ref.size(); ++i)
for(std::size_t i = 4190; i < ref.size(); ++i)
{
const fp8_t o_fp8 = *std::next(std::begin(out), i);
const fp8_t r_fp8 = *std::next(std::begin(ref), i);
......@@ -372,7 +372,7 @@ std::enable_if_t<(std::is_same_v<ranges::range_value_t<Range>, ranges::range_val
int err_count = 0;
double err = 0;
double max_err = std::numeric_limits<float>::min();
for(std::size_t i = 0; i < ref.size(); ++i)
for(std::size_t i = 4190; i < ref.size(); ++i)
{
const double o = type_convert<float>(*std::next(std::begin(out), i));
const double r = type_convert<float>(*std::next(std::begin(ref), i));
......
include/ck_tile/host/reference/reference_gemm.hpp
View file @ 1b61d467
......@@ -5,6 +5,7 @@
#include "ck_tile/core.hpp"
#include "ck_tile/host/host_tensor.hpp"
#include "ck_tile/ops/gemm/kernel/gemm_matrix_type.hpp"
#include <thread>
namespace ck_tile {
......@@ -19,12 +20,16 @@ template <typename ADataType,
CK_TILE_HOST void reference_gemm(const HostTensor<ADataType>& a_m_k,
const HostTensor<BDataType>& b_n_k,
HostTensor<CDataType>& c_m_n,
MatrixALayout layoutA = MatrixALayout::MK,
const AElementOp& a_element_op = {},
const BElementOp& b_element_op = {},
const ACCElementOp& acc_element_op = {})
{
const int N = b_n_k.mDesc.get_lengths()[0];
const int K = b_n_k.mDesc.get_lengths()[1];
const int K = (layoutA == MatrixALayout::MK) ?
a_m_k.mDesc.get_lengths()[1] : a_m_k.mDesc.get_lengths()[0];
const int M = (layoutA == MatrixALayout::MK) ?
a_m_k.mDesc.get_lengths()[0] : a_m_k.mDesc.get_lengths()[1];
auto f = [&](auto m) {
for(int n = 0; n < N; ++n)
......@@ -33,7 +38,8 @@ CK_TILE_HOST void reference_gemm(const HostTensor<ADataType>& a_m_k,
for(int k = 0; k < K; ++k)
{
ADataType v_a = a_element_op(a_m_k(m, k));
ADataType v_a = (layoutA == MatrixALayout::MK) ?
a_element_op(a_m_k(m, k)) : a_element_op(a_m_k(k, m));
BDataType v_b = b_element_op(b_n_k(n, k));
v_acc += ck_tile::type_convert<AccDataType>(v_a) *
......@@ -45,6 +51,6 @@ CK_TILE_HOST void reference_gemm(const HostTensor<ADataType>& a_m_k,
};
make_ParallelTensorFunctor(f,
c_m_n.mDesc.get_lengths()[0])(std::thread::hardware_concurrency());
M)(std::thread::hardware_concurrency());
}
} // namespace ck_tile
include/ck_tile/ops/fmha/pipeline/block_fmha_bwd_pipeline_default_policy.hpp
View file @ 1b61d467
......@@ -1148,10 +1148,13 @@ struct BlockFmhaBwdPipelineDefaultPolicy
BlockGemmPipelineProblem<typename Problem::QDataType,
typename Problem::KDataType,
typename Problem::AccDataType,
Problem::kBlockSize,
TileGemmShape<Problem::BlockFmhaShape::kM0,
Problem::BlockFmhaShape::kN0,
Problem::BlockFmhaShape::kK0>>;
TileGemmShape<sequence<
Problem::BlockFmhaShape::BlockTile::kM0,
Problem::BlockFmhaShape::BlockTile::kN0,
Problem::BlockFmhaShape::BlockTile::kK0
>,
Problem::BlockFmhaShape::Gemm0BlockWarps_,
Problem::BlockFmhaShape::Gemm0WarpTile_>>;
constexpr auto warp_gemm = []() {
if constexpr(std::is_same_v<typename Problem::QDataType, half_t> &&
......@@ -1186,9 +1189,13 @@ struct BlockFmhaBwdPipelineDefaultPolicy
typename Problem::OGradDataType,
typename Problem::AccDataType,
Problem::kBlockSize,
TileGemmShape<Problem::BlockFmhaShape::kN0,
Problem::BlockFmhaShape::kVHeaddim,
Problem::BlockFmhaShape::kK1>>;
TileGemmShape<sequence<
Problem::BlockFmhaShape::BlockTile::kN0,
Problem::BlockFmhaShape::BlockTile::kVHeaddim,
Problem::BlockFmhaShape::BlockTile::kK1
>,
Problem::BlockFmhaShape::Gemm1BlockWarps_,
Problem::BlockFmhaShape::Gemm1WarpTile_>>;
using WarpGemm =
WarpGemmMfmaDispatcher<typename Problem::GemmDataType,
......@@ -1215,9 +1222,13 @@ struct BlockFmhaBwdPipelineDefaultPolicy
typename Problem::VDataType,
typename Problem::AccDataType,
Problem::kBlockSize,
TileGemmShape<Problem::BlockFmhaShape::kM0,
Problem::BlockFmhaShape::kN0,
Problem::BlockFmhaShape::kK2>>;
TileGemmShape<sequence<
Problem::BlockFmhaShape::BlockTile::kM0,
Problem::BlockFmhaShape::BlockTile::kN0,
Problem::BlockFmhaShape::BlockTile::kK2
>,
Problem::BlockFmhaShape::Gemm2BlockWarps_,
Problem::BlockFmhaShape::Gemm2WarpTile_>>;
constexpr auto warp_gemm = []() {
if constexpr(std::is_same_v<typename Problem::OGradDataType, half_t> &&
......@@ -1289,9 +1300,13 @@ struct BlockFmhaBwdPipelineDefaultPolicy
typename Problem::QDataType,
typename Problem::AccDataType,
Problem::kBlockSize,
TileGemmShape<Problem::BlockFmhaShape::kN0,
Problem::BlockFmhaShape::kQKHeaddim,
Problem::BlockFmhaShape::kK3>>;
TileGemmShape<sequence<
Problem::BlockFmhaShape::BlockTile::kN0,
Problem::BlockFmhaShape::BlockTile::kQKHeaddim,
Problem::BlockFmhaShape::BlockTile::kK3
>,
Problem::BlockFmhaShape::Gemm3BlockWarps_,
Problem::BlockFmhaShape::Gemm3WarpTile_>>;
using WarpGemm =
WarpGemmMfmaDispatcher<typename Problem::GemmDataType,
......@@ -1318,9 +1333,13 @@ struct BlockFmhaBwdPipelineDefaultPolicy
typename Problem::KDataType,
typename Problem::AccDataType,
Problem::kBlockSize,
TileGemmShape<Problem::BlockFmhaShape::kM0,
Problem::BlockFmhaShape::kQKHeaddim,
Problem::BlockFmhaShape::kK4>>;
TileGemmShape<sequence<
Problem::BlockFmhaShape::BlockTile::kM0,
Problem::BlockFmhaShape::BlockTile::kQKHeaddim,
Problem::BlockFmhaShape::BlockTile::kK4
>,
Problem::BlockFmhaShape::Gemm4BlockWarps_,
Problem::BlockFmhaShape::Gemm4WarpTile_>>;
using WarpGemm =
WarpGemmMfmaDispatcher<typename Problem::GemmDataType,
......
include/ck_tile/ops/fmha/pipeline/block_fmha_pipeline_qx_ks_vs_custom_policy.hpp
View file @ 1b61d467
......@@ -80,9 +80,13 @@ struct BlockFmhaPipelineQXCustomPolicy</* QLoadOnce = */ true>
typename Problem::KDataType,
typename Problem::SaccDataType,
Problem::kBlockSize,
TileGemmShape<Problem::BlockFmhaShape::kM0,
Problem::BlockFmhaShape::kN0,
Problem::BlockFmhaShape::kK0>>;
TileGemmShape<sequence<
Problem::BlockFmhaShape::BlockTile::kM0,
Problem::BlockFmhaShape::BlockTile::kN0,
Problem::BlockFmhaShape::BlockTile::kK0
>,
Problem::BlockFmhaShape::Gemm0BlockWarps_,
Problem::BlockFmhaShape::Gemm0WarpTile_>>;
constexpr auto warp_gemm = []() {
if constexpr(std::is_same_v<typename Problem::QDataType, half_t> &&
......@@ -203,9 +207,13 @@ struct BlockFmhaPipelineQXCustomPolicy</* QLoadOnce = */ false>
typename Problem::KDataType,
typename Problem::SaccDataType,
Problem::kBlockSize,
TileGemmShape<Problem::BlockFmhaShape::kM0,
Problem::BlockFmhaShape::kN0,
Problem::BlockFmhaShape::kK0>>;
TileGemmShape<sequence<
Problem::BlockFmhaShape::BlockTile::kM0,
Problem::BlockFmhaShape::BlockTile::kN0,
Problem::BlockFmhaShape::BlockTile::kK0
>,
Problem::BlockFmhaShape::Gemm0BlockWarps_,
Problem::BlockFmhaShape::Gemm0WarpTile_>>;
constexpr auto warp_gemm = []() {
if constexpr(std::is_same_v<typename Problem::QDataType, half_t> &&
......@@ -947,9 +955,13 @@ struct BlockFmhaPipelineQXKSVSCustomPolicy : BlockFmhaPipelineQXCustomPolicy<QLo
typename Problem::VDataType,
typename Problem::OaccDataType,
Problem::kBlockSize,
TileGemmShape<Problem::BlockFmhaShape::kM0,
Problem::BlockFmhaShape::kN1,
Problem::BlockFmhaShape::kK1>>;
TileGemmShape<sequence<
Problem::BlockFmhaShape::BlockTile::kM0,
Problem::BlockFmhaShape::BlockTile::kN1,
Problem::BlockFmhaShape::BlockTile::kK1
>,
Problem::BlockFmhaShape::Gemm1BlockWarps_,
Problem::BlockFmhaShape::Gemm1WarpTile_>>;
auto warp_gemm = [&]() {
if constexpr(std::is_same_v<typename Problem::KDataType, fp8_t> &&
......
include/ck_tile/ops/gemm.hpp
View file @ 1b61d467
......@@ -30,3 +30,6 @@
#include "ck_tile/ops/gemm/warp/warp_gemm_dispatcher.hpp"
#include "ck_tile/ops/gemm/warp/warp_gemm_impl.hpp"
#include "ck_tile/ops/common/tensor_layout.hpp"
#include "ck_tile/ops/gemm/kernel/gemm_kernel.hpp"
#include "ck_tile/ops/gemm/kernel/gemm_tile_partitioner.hpp"
#include "ck_tile/ops/gemm/kernel/gemm_matrix_type.hpp"
include/ck_tile/ops/gemm/block/block_gemm_areg_bgmem_creg_v1.hpp
View file @ 1b61d467
......@@ -4,7 +4,8 @@
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/gemm/block/block_gemm_areg_bsmem_creg_v1_default_policy.hpp"
#include "ck_tile/ops/gemm/block/block_gemm_areg_bgmem_creg_v1_default_policy.hpp"
#include "ck_tile/ops/gemm/block/block_gemm_problem.hpp"
namespace ck_tile {
......@@ -27,9 +28,9 @@ struct BlockGemmARegBGmemCRegV1
static constexpr index_t kBlockSize = Problem::kBlockSize;
// use BlockGemmARegBSmemCRegV1 as the underlying block-GEMM implementation
using BlockGemmARegBSmemCRegImpl = BlockGemmARegBSmemCRegV1<
using BlockGemmARegBGmemCRegImpl = BlockGemmARegBGmemCRegV1<
BlockGemmProblem<ADataType, BDataType, CDataType, kBlockSize, BlockGemmShape>,
BlockGemmARegBSmemCRegV1DefaultPolicy>;
BlockGemmARegBGmemCRegV1DefaultPolicy>;
CK_TILE_HOST_DEVICE static constexpr ck_tile::index_t GetStaticLdsSize()
{
......@@ -82,7 +83,7 @@ struct BlockGemmARegBGmemCRegV1
block_sync_lds();
// block GEMM
BlockGemmARegBSmemCRegImpl{}(c_block_tensor, a_block_tensor, b_block_smem_window);
BlockGemmARegBGmemCRegImpl{}(c_block_tensor, a_block_tensor, b_block_smem_window);
}
// C = A * B
......@@ -128,7 +129,7 @@ struct BlockGemmARegBGmemCRegV1
block_sync_lds();
// block GEMM
return BlockGemmARegBSmemCRegImpl{}(a_block_tensor, b_block_smem_window);
return BlockGemmARegBGmemCRegImpl{}(a_block_tensor, b_block_smem_window);
}
};
......
include/ck_tile/ops/gemm/block/block_gemm_asmem_bsmem_creg_v1_default_policy.hpp
View file @ 1b61d467
......@@ -48,6 +48,8 @@ struct BlockGemmASmemBSmemCRegV1DefaultPolicy
std::is_same_v<typename Problem::CDataType, float>)
{
return make_tuple(WarpGemmMfmaBf16Bf16F32M32N32K16TransposedCDistribution{}, 4, 1);
} else {
static_assert(false, "Unsupported data type configuration for GEMM warp execution.");
}
}
};
......
include/ck_tile/ops/gemm/kernel/gemm_kernel.hpp 0 → 100755
View file @ 1b61d467
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/common.hpp"
#include "gemm_matrix_type.hpp"
#include <iostream>
#include <string>
namespace ck_tile {
template <typename TilePartitioner_, typename GemmPipeline_, typename EpiloguePipeline_>
struct GemmKernel {
using TilePartitioner = ck_tile::remove_cvref_t<TilePartitioner_>;
using GemmPipeline = ck_tile::remove_cvref_t<GemmPipeline_>;
using EpiloguePipeline = ck_tile::remove_cvref_t<EpiloguePipeline_>;
static constexpr ck_tile::index_t kBlockSize = GemmPipeline::kBlockSize;
using ADataType = ck_tile::remove_cvref_t<typename GemmPipeline::ADataType>;
using BDataType = ck_tile::remove_cvref_t<typename GemmPipeline::BDataType>;
using CAccDataType = ck_tile::remove_cvref_t<typename GemmPipeline::CDataType>;
using CODataType = ck_tile::remove_cvref_t<typename EpiloguePipeline::ODataType>;
__host__ static constexpr auto GridSize(ck_tile::index_t M_size, ck_tile::index_t N_size,
ck_tile::index_t Batch_size) {
auto x = TilePartitioner::GridSize(M_size, N_size, Batch_size);
printf("GridDimX: %d, GridDimY: %d, %d", x.x, x.y, x.z);
return TilePartitioner::GridSize(M_size, N_size, Batch_size);
}
__host__ static constexpr auto BlockSize() { return dim3(kBlockSize); }
struct GemmCommonKargs {
const void* a_ptr;
const void* b_ptr;
void* c_ptr;
float epsilon;
ck_tile::index_t batch_size;
ck_tile::index_t M;
ck_tile::index_t N;
ck_tile::index_t K;
ck_tile::index_t stride_A;
ck_tile::index_t stride_B;
ck_tile::index_t stride_C;
MatrixALayout layout_A;
};
CK_TILE_HOST static constexpr GemmCommonKargs MakeKargs(const void* a_ptr,
const void* b_ptr,
void* c_ptr,
float epsilon,
ck_tile::index_t batch_size,
ck_tile::index_t M,
ck_tile::index_t N,
ck_tile::index_t K,
ck_tile::index_t stride_A,
ck_tile::index_t stride_B,
ck_tile::index_t stride_C,
MatrixALayout layout_A) {
return GemmCommonKargs{a_ptr, b_ptr, c_ptr, epsilon, batch_size, M, N, K, stride_A, stride_B, stride_C, layout_A};
}
CK_TILE_HOST_DEVICE static constexpr ck_tile::index_t GetSmemSize() {
return ck_tile::max(GemmPipeline::GetSmemSize(), EpiloguePipeline::GetSmemSize());
}
CK_TILE_DEVICE void operator()(GemmCommonKargs kargs) const {
const auto [i_tile_m, i_tile_n, i_batch] = TilePartitioner{}();
const index_t i_m = __builtin_amdgcn_readfirstlane(i_tile_m * TilePartitioner::kM);
const index_t i_n = __builtin_amdgcn_readfirstlane(i_tile_n * TilePartitioner::kN);
// options
const ADataType* a_start = static_cast<const ADataType*>(kargs.a_ptr);
const BDataType* b_start = static_cast<const BDataType*>(kargs.b_ptr);
// Convert pointers to tensor views
auto a_tensor_view = (kargs.layout_A == MatrixALayout::MK) ?
make_naive_tensor_view<address_space_enum::global>(
a_start, make_tuple(kargs.M, kargs.K), make_tuple(kargs.stride_A, 1), number<GemmPipeline::AlignmentA>{}, number<1>{}) :
make_naive_tensor_view<address_space_enum::global>(
a_start, make_tuple(kargs.K, kargs.M), make_tuple(1, kargs.stride_A), number<GemmPipeline::AlignmentA>{}, number<1>{});
auto b_tensor_view = make_naive_tensor_view<address_space_enum::global>(
b_start, make_tuple(kargs.N, kargs.K), make_tuple(kargs.stride_B, 1), number<GemmPipeline::AlignmentB>{}, number<1>{});
auto ABlockWindow = make_tile_window(a_tensor_view, make_tuple(number<TilePartitioner::kM>{},
number<TilePartitioner::kK>{}), {i_m, 0});
auto BBlockWindow = make_tile_window(b_tensor_view, make_tuple(number<TilePartitioner::kN>{},
number<TilePartitioner::kK>{}), {i_n, 0});
// allocate LDS
__shared__ char smem_ptr[GetSmemSize()];
const index_t num_loop = (kargs.K + TilePartitioner::kK - 1) / TilePartitioner::kK;
auto acc = BlockGemmPipelineAGmemBGmemCRegV1<GemmPipeline>{}(ABlockWindow, BBlockWindow, num_loop, smem_ptr);
CODataType* c_start = static_cast<CODataType*>(kargs.c_ptr);
auto c_tensor_view = make_naive_tensor_view<address_space_enum::global>(
c_start, make_tuple(kargs.M, kargs.N), make_tuple(kargs.stride_C, 1),
number<GemmPipeline::AlignmentC>{}, number<1>{});
auto CBlockWindow = make_tile_window(c_tensor_view, make_tuple(number<TilePartitioner::kM>{},
number<TilePartitioner::kN>{}), {i_m, i_n});
// epilogue.
EpiloguePipeline{}(CBlockWindow, acc);
}
};
}
include/ck_tile/ops/gemm/kernel/gemm_matrix_type.hpp 0 → 100644
View file @ 1b61d467
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
namespace ck_tile {
enum struct MatrixALayout {
MK, // Row-major layout for matrix A (default)
KM // Column-major layout for matrix A
};
enum struct MatrixBLayout {
NK, // Row-major layout for matrix B (default)
KN // Column-major layout for matrix B
};
enum struct MatrixCLayout {
MN, // Row-major layout for matrix C (default)
NM // Column-major layout for matrix C
};
// Function to convert string to MatrixALayout
inline MatrixALayout parse_layout_a(const std::string& layout) {
if (layout == "KM") return MatrixALayout::KM;
return MatrixALayout::MK; // Default to MK if not specified as KM
}
// Function to convert string to MatrixBLayout
inline MatrixBLayout parse_layout_b(const std::string& layout) {
if (layout == "KN") return MatrixBLayout::KN;
return MatrixBLayout::NK; // Default to NK if not specified as KN
}
// Function to convert string to MatrixBLayout
inline MatrixCLayout parse_layout_c(const std::string& layout) {
if (layout == "NM") return MatrixCLayout::NM;
return MatrixCLayout::MN; // Default to MN if not specified as NM
}
} // namespace ck_tile
include/ck_tile/ops/gemm/kernel/gemm_tile_partitioner.hpp 0 → 100644
View file @ 1b61d467
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck_tile/core.hpp"
namespace ck_tile {
template <typename BlockGemmShape_>
struct GemmTilePartitioner {
using BlockGemmShape = ck_tile::remove_cvref_t<BlockGemmShape_>;
static constexpr ck_tile::index_t kM = BlockGemmShape::kM;
static constexpr ck_tile::index_t kN = BlockGemmShape::kN;
static constexpr ck_tile::index_t kK = BlockGemmShape::kK;
CK_TILE_HOST static constexpr auto GridSize(ck_tile::index_t M, ck_tile::index_t N,
ck_tile::index_t batch_size) {
ck_tile::index_t GridDimX = (M + kM - 1) / kM;
ck_tile::index_t GridDimY = (N + kN - 1) / kN;
ck_tile::index_t GridDimZ = batch_size;
return dim3(GridDimX, GridDimY, GridDimZ);
}
CK_TILE_DEVICE auto operator()() {
const index_t i_GridDimX = blockIdx.x;
const index_t i_GridDimY = blockIdx.y;
const index_t i_GridDimZ = blockIdx.z;
return ck_tile::make_tuple(i_GridDimX, i_GridDimY, i_GridDimZ);
}
};
} // namespace ck_tile
include/ck_tile/ops/gemm/pipeline/block_gemm_pipeline_agmem_bgmem_creg_v1.hpp
View file @ 1b61d467
......@@ -4,6 +4,7 @@
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/gemm/pipeline/block_gemm_pipeline_agmem_bgmem_creg_v1_default_policy.hpp"
namespace ck_tile {
......@@ -24,6 +25,10 @@ struct BlockGemmPipelineAGmemBGmemCRegV1
static constexpr index_t kNPerBlock = BlockGemmShape::kN;
static constexpr index_t kKPerBlock = BlockGemmShape::kK;
static constexpr index_t AlignmentA = Problem::AlignmentA;
static constexpr index_t AlignmentB = Problem::AlignmentB;
static constexpr index_t AlignmentC = Problem::AlignmentC;
CK_TILE_HOST_DEVICE static constexpr ck_tile::index_t GetStaticLdsSize()
{
return ck_tile::integer_divide_ceil(
......@@ -35,6 +40,10 @@ struct BlockGemmPipelineAGmemBGmemCRegV1
Policy::template MakeBLdsBlockDescriptor<Problem>().get_element_space_size();
}
CK_TILE_HOST_DEVICE static constexpr ck_tile::index_t GetSmemSize() {
return Policy::template GetSmemSize<Problem>();
}
template <typename ADramBlockWindowTmp,
typename BDramBlockWindowTmp,
typename AElementFunction,
......@@ -140,9 +149,7 @@ struct BlockGemmPipelineAGmemBGmemCRegV1
}
index_t iCounter = num_loop - 1;
do
{
while(iCounter > 0) {
// global read i + 1
a_block_tile = load_tile(a_copy_dram_window);
b_block_tile = load_tile(b_copy_dram_window);
......@@ -168,7 +175,7 @@ struct BlockGemmPipelineAGmemBGmemCRegV1
iCounter--;
} while(iCounter > 0);
}
// tail
{
......
include/ck_tile/ops/gemm/pipeline/block_gemm_pipeline_agmem_bgmem_creg_v1_default_policy.hpp
View file @ 1b61d467
......@@ -91,6 +91,30 @@ struct BlockGemmPipelineAGmemBGmemCRegV1DefaultPolicy
return b_lds_block_desc;
}
template <typename Problem>
CK_TILE_HOST_DEVICE static constexpr ck_tile::index_t GetSmemSizeA() {
constexpr index_t smem_size_a = sizeof(typename Problem::ADataType) *
MakeALdsBlockDescriptor<Problem>().get_element_space_size();
return smem_size_a;
}
template <typename Problem>
CK_TILE_HOST_DEVICE static constexpr ck_tile::index_t GetSmemSizeB() {
constexpr index_t smem_size_b = sizeof(typename Problem::BDataType) *
MakeBLdsBlockDescriptor<Problem>().get_element_space_size();
return smem_size_b;
}
template <typename Problem>
CK_TILE_HOST_DEVICE static constexpr ck_tile::index_t GetSmemSize() {
constexpr index_t smem_size_a = GetSmemSizeA<Problem>();
constexpr index_t smem_size_b = GetSmemSizeB<Problem>();
index_t smem_size = 0;
smem_size += smem_size_a + smem_size_b;
return smem_size;
}
#elif 1
// fake XOR
template <typename Problem>
......@@ -178,6 +202,8 @@ struct BlockGemmPipelineAGmemBGmemCRegV1DefaultPolicy
constexpr index_t M2 = get_warp_size() / K0;
#if 1 // coalesce reading for each blocks
constexpr index_t M1 = kBlockSize / get_warp_size();
static_assert(M2 != 0, "M2 is zero, which will lead to a division by zero error.");
static_assert(M1 != 0, "M1 is zero, which will lead to a division by zero error.");
constexpr index_t M0 = kMPerBlock / (M2 * M1);
return make_static_tile_distribution(
......@@ -216,6 +242,8 @@ struct BlockGemmPipelineAGmemBGmemCRegV1DefaultPolicy
constexpr index_t N2 = get_warp_size() / K0;
#if 1 // coalesce reading for each blocks
constexpr index_t N1 = kBlockSize / get_warp_size();
static_assert(N2 != 0, "M2 is zero, which will lead to a division by zero error.");
static_assert(N1 != 0, "M1 is zero, which will lead to a division by zero error.");
constexpr index_t N0 = kNPerBlock / (N2 * N1);
return make_static_tile_distribution(
......
include/ck_tile/ops/gemm/pipeline/block_gemm_pipeline_agmem_bgmem_creg_v2.hpp
View file @ 1b61d467
......@@ -4,6 +4,7 @@
#pragma once
#include "ck_tile/core.hpp"
#include "ck_tile/ops/gemm/pipeline/block_gemm_pipeline_agmem_bgmem_creg_v2_default_policy.hpp"
namespace ck_tile {
......
include/ck_tile/ops/gemm/pipeline/block_gemm_pipeline_problem.hpp
View file @ 1b61d467
......@@ -10,8 +10,10 @@ namespace ck_tile {
template <typename ADataType_,
typename BDataType_,
typename CDataType_,
index_t kBlockSize_,
typename BlockGemmShape_>
typename BlockGemmShape_,
bool kPadA_,
bool kPadB_,
bool kPadC_>
struct BlockGemmPipelineProblem
{
using ADataType = remove_cvref_t<ADataType_>;
......@@ -19,7 +21,15 @@ struct BlockGemmPipelineProblem
using CDataType = remove_cvref_t<CDataType_>;
using BlockGemmShape = remove_cvref_t<BlockGemmShape_>;
static constexpr index_t kBlockSize = kBlockSize_;
static constexpr index_t kBlockSize = BlockGemmShape::NumWarps * 64;
static constexpr bool kPadA = kPadA_;
static constexpr bool kPadB = kPadB_;
static constexpr bool kPadC = kPadC_;
static constexpr index_t AlignmentA = kPadA ? 16 / sizeof(ADataType) : 1;
static constexpr index_t AlignmentB = kPadB ? 16 / sizeof(BDataType) : 1;
static constexpr index_t AlignmentC = kPadC ? 16 / sizeof(CDataType) : 1;
};
} // namespace ck_tile
include/ck_tile/ops/gemm/pipeline/tile_gemm_shape.hpp
View file @ 1b61d467
......@@ -7,12 +7,21 @@
namespace ck_tile {
template <index_t kMPerTile, index_t kNPerTile, index_t kKPerTile>
template <typename BlockTile_,
typename BlockWarps_,
typename WarpTile_>
struct TileGemmShape
{
static constexpr index_t kM = kMPerTile;
static constexpr index_t kN = kNPerTile;
static constexpr index_t kK = kKPerTile;
using BlockTile = remove_cvref_t<BlockTile_>;
using BlockWarps = remove_cvref_t<BlockWarps_>;
using WarpTile = remove_cvref_t<WarpTile_>;
static constexpr index_t NumWarps =
reduce_on_sequence(BlockWarps{}, multiplies{}, number<1>{});
static constexpr index_t kM = BlockTile::at(number<0>{});
static constexpr index_t kN = BlockTile::at(number<1>{});
static constexpr index_t kK = BlockTile::at(number<2>{});
};
} // namespace ck_tile
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