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Commit d43cd4ad authored by Mirza Halilcevic's avatar Mirza Halilcevic
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Introduce gemm_softmax_gemm to codegen.

parent 3528a523
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Showing with 1221 additions and 68 deletions
CMakeLists.txt
View file @ d43cd4ad
......@@ -128,6 +128,8 @@ list(APPEND CMAKE_PREFIX_PATH ${CMAKE_INSTALL_PREFIX} ${CMAKE_INSTALL_PREFIX}/ll
message("GPU_TARGETS= ${GPU_TARGETS}")
option(CK_BUILD_HOST_LIB, "Only build the CK JIT Helper Library" OFF)
find_package(hip)
# No assumption that HIP kernels are launched with uniform block size for backward compatibility
# SWDEV-413293 and https://reviews.llvm.org/D155213
......@@ -254,6 +256,7 @@ elseif(CK_PARALLEL_COMPILE_JOBS)
message(WARNING "Job pooling is only available with Ninja generators.")
endif()
if (NOT CK_BUILD_HOST_LIB)
option(USE_BITINT_EXTENSION_INT4 "Whether to enable clang's BitInt extension to provide int4 data type." OFF)
option(USE_OPT_GFX11 "Whether to enable LDS cumode and Wavefront32 mode for GFX11 silicons." OFF)
......@@ -275,6 +278,8 @@ set(THREADS_PREFER_PTHREAD_FLAG ON)
find_package(Threads REQUIRED)
link_libraries(Threads::Threads)
endif() # NOT CK_BUILD_HOST_LIB
## C++
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
......@@ -291,6 +296,8 @@ if(USE_GLIBCXX_ASSERTIONS)
add_compile_options(-Wp,-D_GLIBCXX_ASSERTIONS)
endif()
if (NOT CK_BUILD_HOST_LIB)
## HIP
set(CMAKE_HIP_PLATFORM amd)
set(CMAKE_HIP_COMPILER ${CMAKE_CXX_COMPILER})
......@@ -346,6 +353,8 @@ else()
add_compile_definitions(__HIP_PLATFORM_HCC__=1)
endif()
endif() # NOT CK_BUILD_HOST_LIB
## tidy
include(EnableCompilerWarnings)
set(CK_TIDY_ERRORS ERRORS * -readability-inconsistent-declaration-parameter-name)
......@@ -499,6 +508,8 @@ include_directories(BEFORE
${HIP_INCLUDE_DIRS}
)
if (NOT CK_BUILD_HOST_LIB)
SET(BUILD_DEV ON CACHE BOOL "BUILD_DEV")
if(BUILD_DEV)
add_compile_options(-Werror)
......@@ -506,6 +517,8 @@ if(BUILD_DEV)
endif()
message("CMAKE_CXX_FLAGS: ${CMAKE_CXX_FLAGS}")
endif() # NOT CK_BUILD_HOST_LIB
if("${CMAKE_CXX_COMPILER_ID}" MATCHES "Clang")
add_compile_options(-fcolor-diagnostics)
endif()
......@@ -515,6 +528,8 @@ endif()
add_custom_target(check COMMAND ${CMAKE_CTEST_COMMAND} --output-on-failure -C ${CMAKE_CFG_INTDIR})
if (NOT CK_BUILD_HOST_LIB)
file(GLOB_RECURSE INSTANCE_FILES "${PROJECT_SOURCE_DIR}/*/device_*_instance.cpp")
file(GLOB dir_list RELATIVE ${PROJECT_SOURCE_DIR}/library/src/tensor_operation_instance/gpu ${PROJECT_SOURCE_DIR}/library/src/tensor_operation_instance/gpu/*)
set(CK_DEVICE_INSTANCES)
......@@ -590,6 +605,18 @@ if(NOT DEFINED PROFILER_ONLY AND (GPU_TARGETS MATCHES "gfx9" OR DEFINED INSTANCE
add_subdirectory(codegen)
endif()
else() # NOT CK_BUILD_HOST_LIB
if(GPU_TARGETS MATCHES "gfx9")
rocm_package_setup_component(ck_host
LIBRARY_NAME composablekernel
PACKAGE_NAME ck_host
)
add_subdirectory(codegen)
endif()
endif() # NOT CK_BUILD_HOST_LIB
#Create an interface target for the include only files and call it "composablekernels"
include(CMakePackageConfigHelpers)
......@@ -627,4 +654,4 @@ rocm_create_package(
MAINTAINER "MIOpen Kernels Dev Team <dl.MIOpen@amd.com>"
LDCONFIG
HEADER_ONLY
)
)
\ No newline at end of file
Config.cmake.in
View file @ d43cd4ad
@PACKAGE_INIT@
set(_composable_kernel_supported_components device_other_operations device_gemm_operations device_conv_operations device_mha_operations device_contraction_operations device_reduction_operations utility)
set(_composable_kernel_supported_components device_other_operations device_gemm_operations device_conv_operations device_mha_operations device_contraction_operations device_reduction_operations utility ck_host)
foreach(_comp ${composable_kernel_FIND_COMPONENTS})
if(NOT _comp IN_LIST _composable_kernel_supported_components)
......
codegen/CMakeLists.txt
View file @ d43cd4ad
......@@ -31,12 +31,21 @@ file(GLOB SOURCES CONFIGURE_DEPENDS src/*.cpp)
##message(STATUS "SOURCE_FILES: ${SOURCES}")
# TODO: Use object library
add_library(ck_host STATIC ${SOURCES})
target_link_libraries(ck_host PRIVATE ck_headers)
add_library(composable_kernel::ck_host ALIAS ck_host)
set_target_properties(ck_host PROPERTIES
LINKER_LANGUAGE CXX
POSITION_INDEPENDENT_CODE ON)
target_include_directories(ck_host SYSTEM PRIVATE
$<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/include>
# $<BUILD_INTERFACE:${PROJECT_SOURCE_DIR}/library/src/jit_library/solution_instances>
$<BUILD_INTERFACE:${CMAKE_CURRENT_BINARY_DIR}/solution_instances>
$<BUILD_INTERFACE:${CMAKE_CURRENT_BINARY_DIR}/embed/ck_headers/include>
)
target_link_libraries(ck_host PRIVATE $<BUILD_INTERFACE:ck_headers>)
target_include_directories(ck_host PUBLIC
$<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}/include>
)
......@@ -45,9 +54,18 @@ add_executable(ck-template-driver driver/main.cpp)
target_link_libraries(ck-template-driver ck_host)
rocm_install(
TARGETS ck_host ck_headers
TARGETS ck_host
EXPORT ck_hostTargets
)
rocm_install(DIRECTORY include/ck DESTINATION ${CMAKE_INSTALL_INCLUDEDIR})
add_subdirectory(test)
rocm_install(
EXPORT ck_hostTargets
FILE composable_kernelck_hostTargets.cmake
NAMESPACE composable_kernel::
DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/composable_kernel
)
if (NOT CK_BUILD_HOST_LIB)
add_subdirectory(test)
endif()
codegen/include/ck/host/device_batched_gemm_softmax_gemm/operation.hpp 0 → 100644
View file @ d43cd4ad
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <cstdlib>
#include <vector>
#include <string>
#include "ck/host/types.hpp"
#include "ck/host/operation/gemm.hpp"
#include "ck/host/device_batched_gemm_softmax_gemm/problem.hpp"
namespace ck {
namespace host {
namespace device_batched_gemm_softmax_gemm {
// defines all values need for an instance of fwd conv
struct Operation_Xdl_CShuffle
{
// returns a vector of instances, only given fusion operators: will use default problem spec
static std::vector<std::vector<Operation_Xdl_CShuffle>>
CreateOperations(const std::string& prologue, const std::string& epilogue);
// returns a vector of instances, given a problem spec and fusion operators
static std::vector<Operation_Xdl_CShuffle>
CreateOperations(const Problem& prob, const std::string& prologue, const std::string& epilogue);
TensorDesc A{};
TensorDesc B{};
TensorDesc B1{};
TensorDesc C{};
std::string a_elem_op = PassThrough;
std::string b_elem_op = PassThrough;
std::string b1_elem_op = PassThrough;
std::string c_elem_op = PassThrough;
std::string acc_elem_op = Scale;
std::string prologue = "";
std::string epilogue = "";
std::string gemm_specialization = "ck::tensor_operation::device::GemmSpecialization::Default";
// tuning parameters
operation::TileDescGemmSoftmaxGemm tile_desc{};
operation::BlockTransferDesc a_block_transfer{};
operation::BlockTransferDesc b0_block_transfer{};
operation::BlockTransferDesc b1_block_transfer{};
operation::CShuffleDesc cshuffle{};
operation::CBlockTransferDesc c_block_transfer{};
bool mask_out_upper_triangle = false;
// functions to update fusion operators if provided
void update_prologue(const std::string& prologue);
void update_epilogue(const std::string& epilogue);
/**constexpr**/ bool IsSupported(std::size_t MRaw_, std::size_t NRaw_, std::size_t KRaw_);
// returns a templated instance
Solution ToSolution() const;
};
} // namespace device_batched_gemm_softmax_gemm
} // namespace host
} // namespace ck
codegen/include/ck/host/device_batched_gemm_softmax_gemm/problem.hpp 0 → 100644
View file @ d43cd4ad
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <cstdlib>
#include <vector>
#include <string>
#include "ck/host/types.hpp"
namespace ck {
namespace host {
namespace device_batched_gemm_softmax_gemm {
// defines the problem specification for a GEMM operation
struct Problem
{
std::size_t M = 0;
std::size_t N = 0;
std::size_t K = 0;
std::size_t O = 0;
bool TransA = false;
bool TransB = false;
bool TransB1 = false;
bool TransC = false;
DataType ADataType = DataType::Half;
DataType BDataType = DataType::Half;
DataType B1DataType = DataType::Half;
DataType CDataType = DataType::Half;
std::string AElementOp = PassThrough;
std::string BElementOp = PassThrough;
std::string B1ElementOp = PassThrough;
std::string CElementOp = PassThrough;
std::string AccElementOp = Scale;
// returns the correct device op file for the operation
std::string GetIncludeHeader() const;
// returns a list of instances based on the problem spec and provided fusion operations
std::vector<Solution> GetSolutions(const std::string& arch,
const std::string& prologue,
const std::string& epilogue) const;
};
} // namespace device_batched_gemm_softmax_gemm
} // namespace host
} // namespace ck
codegen/include/ck/host/device_gemm_multiple_d/operation.hpp
View file @ d43cd4ad
......@@ -41,6 +41,8 @@ struct Operation_Xdl_CShuffle
operation::BlockTransferDesc b_block_transfer{};
operation::CShuffleDesc cshuffle{};
operation::CBlockTransferDesc c_block_transfer{};
LoopScheduler loop_scheduler{};
PipelineVersion pipeline_version{};
// functions to update fusion operators if provided
void update_prologue(const std::string& prologue);
......
codegen/include/ck/host/operation/gemm.hpp
View file @ d43cd4ad
......@@ -23,6 +23,26 @@ struct TileDesc
int n_Xdl_per_wave = 0;
int num_gemmk_prefetch_stage = 0;
};
struct TileDescGemmSoftmaxGemm
{
int block_size = 0;
int gemm01_m_per_block = 0;
int gemm0_n_per_block = 0;
int gemm0_k_per_block = 0;
int gemm1_n_per_block = 0;
int gemm1_k_per_block = 0;
int ak1 = 0;
int bk1 = 0;
int b1k1 = 0;
int m_per_XDL = 0;
int n_per_XDL = 0;
int gemm0_m_Xdl_per_wave = 0;
int gemm0_n_Xdl_per_wave = 0;
int gemm1_n_Xdl_per_wave = 0;
int num_gemmk_prefetch_stage = 0;
};
struct BlockTransferDesc
{
std::string thread_cluster_length = "";
......
codegen/include/ck/host/types.hpp
View file @ d43cd4ad
......@@ -66,6 +66,20 @@ enum class GemmType
};
std::string ToString(GemmType gt);
enum class LoopScheduler
{
Default,
Interwave,
};
std::string ToString(LoopScheduler ls);
enum class PipelineVersion
{
v1,
v2
};
std::string ToString(PipelineVersion pv);
struct TensorDesc
{
DataType element;
......@@ -84,6 +98,7 @@ const std::string S = SequenceStr({xs...});
constexpr const char* PassThrough = "ck::tensor_operation::element_wise::PassThrough";
constexpr const char* Bilinear = "ck::tensor_operation::element_wise::Bilinear";
constexpr const char* Scale = "ck::tensor_operation::element_wise::Scale";
} // namespace host
} // namespace ck
codegen/src/device_batched_gemm_softmax_gemm.cpp 0 → 100644
View file @ d43cd4ad
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/host/device_batched_gemm_softmax_gemm/problem.hpp"
#include "ck/host/device_batched_gemm_softmax_gemm/operation.hpp"
#include "ck/host/utils.hpp"
#include <algorithm>
namespace ck {
namespace host {
namespace device_batched_gemm_softmax_gemm {
// return the relevant device op file based on the operation
std::string Problem::GetIncludeHeader() const
{
return "ck/tensor_operation/gpu/device/impl/device_batched_gemm_softmax_gemm_xdl_cshuffle.hpp";
}
// returns templated instances when provided with a problem specification
std::vector<Solution> Problem::GetSolutions(const std::string& arch,
const std::string& prologue,
const std::string& epilogue) const
{
if(get_xdlop_archs().count(arch) == 0)
return {};
auto ops = ck::host::device_batched_gemm_softmax_gemm::Operation_Xdl_CShuffle::CreateOperations(
*this, prologue, epilogue); // obtains vector of instances
std::vector<Solution> result;
std::transform(ops.begin(), ops.end(), std::back_inserter(result), [&](const auto& op) {
return op.ToSolution(); // template instance with correct values
});
return result;
}
} // namespace device_batched_gemm_softmax_gemm
} // namespace host
} // namespace ck
codegen/src/device_gemm_multiple_d_operation_xdl_cshuffle.cpp
View file @ d43cd4ad
......@@ -62,6 +62,13 @@ void Operation_Xdl_CShuffle::update_epilogue(const std::string& epi)
// accounts for all possible combinations of Row/Col major
static Layout ToLayout(bool Trans) { return Trans ? Layout::Column : Layout::Row; }
// DeviceGemmMultipleD_Xdl_CShuffle< Col, Row, Row_Row_Tuple, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmMNKPadding, 1, 64, 16, 16, 32, 8, 8, 16, 16, 1, 1, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 16, 1, 4>, 1,
// DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row_Row_Tuple, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmMNKPadding, 1, 64, 16, 16, 32, 8, 8, 16, 16, 1, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 1, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 1, 8, 1, 1, 1, S<1, 16, 1, 4>, 1, LoopScheduler::Default, PipelineVersion::v1>
// Hard-code tuning parameters in modularized fashion, string them together into a vector of
// instances
std::vector<Operation_Xdl_CShuffle> Operation_Xdl_CShuffle::CreateOperations(
......@@ -83,6 +90,8 @@ std::vector<Operation_Xdl_CShuffle> Operation_Xdl_CShuffle::CreateOperations(
{ 128, 64, 128, 32, 8, 8, 32, 32, 2, 2, 1},
{ 256, 128, 64, 32, 8, 8, 32, 32, 2, 1, 1},
{ 256, 64, 128, 32, 8, 8, 32, 32, 1, 2, 1},
// Irregular tile
{ 64, 16, 16, 32, 8, 8, 16, 16, 1, 1, 1},
// clang-format on
};
......@@ -100,6 +109,8 @@ std::vector<Operation_Xdl_CShuffle> Operation_Xdl_CShuffle::CreateOperations(
{ S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1},
{ S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1},
{ S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1},
// Irregular tile
{ S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 1, 8, 1},
// clang-format on
};
......@@ -109,15 +120,17 @@ std::vector<Operation_Xdl_CShuffle> Operation_Xdl_CShuffle::CreateOperations(
// ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM|
// Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| |
// | | | | | | |
{ S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1},
{ S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1},
{ S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1},
{ S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1},
{ S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1},
{ S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1},
{ S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1},
{ S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1},
// Irregular tile
{ S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1},
// clang-format on
{S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1},
{S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1},
{S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1},
{S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1},
{S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1},
{S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1},
{S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1},
{S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1},
};
std::vector<operation::BlockTransferDesc> b_block_descriptions_rowmajor = {
......@@ -134,6 +147,8 @@ std::vector<Operation_Xdl_CShuffle> Operation_Xdl_CShuffle::CreateOperations(
{ S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1},
{ S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1},
{ S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1},
// Irregular tile
{ S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1},
// clang-format on
};
......@@ -151,6 +166,8 @@ std::vector<Operation_Xdl_CShuffle> Operation_Xdl_CShuffle::CreateOperations(
{ S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1},
{ S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1},
{ S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1},
// Irregular tile
{ S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 1, 8, 1},
// clang-format on
};
......@@ -167,6 +184,7 @@ std::vector<Operation_Xdl_CShuffle> Operation_Xdl_CShuffle::CreateOperations(
{ 1, 1},
{ 1, 1},
{ 1, 1},
{ 1, 1},
{ 1, 1},
// clang-format on
};
......@@ -185,6 +203,8 @@ std::vector<Operation_Xdl_CShuffle> Operation_Xdl_CShuffle::CreateOperations(
{ S<1, 16, 1, 8>, 8},
{ S<1, 32, 1, 8>, 8},
{ S<1, 32, 1, 8>, 8},
// Irregular tile
{ S<1, 16, 1, 4>, 1},
// clang-format on
};
......@@ -199,33 +219,44 @@ std::vector<Operation_Xdl_CShuffle> Operation_Xdl_CShuffle::CreateOperations(
assert(tile_descriptions.size() == cshuffle_descriptions.size());
assert(tile_descriptions.size() == c_block_descriptions.size());
// Put all values together into a single operation > store into the result vector
for(std::size_t i = 0; i < tile_descriptions.size(); i++)
const std::vector<std::tuple<LoopScheduler, PipelineVersion>> scheduler_pipeline_descriptions =
{
{LoopScheduler::Default, PipelineVersion::v1},
{LoopScheduler::Interwave, PipelineVersion::v1},
{LoopScheduler::Default, PipelineVersion::v2},
};
for(auto [loop_scheduler, pipeline_version] : scheduler_pipeline_descriptions)
{
Operation_Xdl_CShuffle x;
x.tile_desc = tile_descriptions[i];
x.a_block_transfer = a_block_descriptions[i];
x.b_block_transfer = b_block_descriptions[i];
x.cshuffle = cshuffle_descriptions[i];
x.c_block_transfer = c_block_descriptions[i];
x.A = TensorDesc{prob.ADataType, ToLayout(prob.TransA)};
x.B = TensorDesc{prob.BDataType, ToLayout(prob.TransB)};
x.E = TensorDesc{prob.EDataType, ToLayout(prob.TransE)};
x.Ds = Transform(prob.DsTrans, prob.DsDataType, [](auto trans, auto dt) {
return TensorDesc{dt, ToLayout(trans)};
});
x.a_elem_op = prob.AElementOp;
x.b_elem_op = prob.BElementOp;
x.cde_elem_op = prob.CDEElementOp;
x.gemm_specialization = GetGemmSpec(prob.M,
prob.N,
prob.K,
x.tile_desc.m_per_block,
x.tile_desc.n_per_block,
x.tile_desc.k_per_block);
x.update_prologue(prologue);
x.update_epilogue(epilogue);
result.push_back(x);
// Put all values together into a single operation > store into the result vector
for(std::size_t i = 0; i < tile_descriptions.size(); i++)
{
Operation_Xdl_CShuffle x;
x.tile_desc = tile_descriptions[i];
x.a_block_transfer = a_block_descriptions[i];
x.b_block_transfer = b_block_descriptions[i];
x.cshuffle = cshuffle_descriptions[i];
x.c_block_transfer = c_block_descriptions[i];
x.A = TensorDesc{prob.ADataType, ToLayout(prob.TransA)};
x.B = TensorDesc{prob.BDataType, ToLayout(prob.TransB)};
x.E = TensorDesc{prob.EDataType, ToLayout(prob.TransE)};
x.Ds = Transform(prob.DsTrans, prob.DsDataType, [](auto trans, auto dt) {
return TensorDesc{dt, ToLayout(trans)};
});
x.a_elem_op = prob.AElementOp;
x.b_elem_op = prob.BElementOp;
x.cde_elem_op = prob.CDEElementOp;
x.gemm_specialization = GetGemmSpec(prob.M,
prob.N,
prob.K,
x.tile_desc.m_per_block,
x.tile_desc.n_per_block,
x.tile_desc.k_per_block);
x.loop_scheduler = loop_scheduler;
x.pipeline_version = pipeline_version;
x.update_prologue(prologue);
x.update_epilogue(epilogue);
result.push_back(x);
}
}
return result;
}
......@@ -263,7 +294,7 @@ static const char* const DeviceGemmMultipleD_Xdl_CShuffleTemplate =
"${BBlockTransferSrcScalarPerVector}, ${BBlockTransferDstScalarPerVector_BK1}, "
"${BBlockLdsExtraN}, ${CShuffleMXdlPerWavePerShuffle}, ${CShuffleNXdlPerWavePerShuffle}, "
"${CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock}, "
"${CDEBlockTransferScalarPerVector_NPerBlock}>";
"${CDEBlockTransferScalarPerVector_NPerBlock}, ${LoopScheduler}, ${PipelineVersion}>";
// use hardcoded instances from vector of operations to substitute values into instance template
Solution Operation_Xdl_CShuffle::ToSolution() const
......@@ -336,6 +367,8 @@ Solution Operation_Xdl_CShuffle::ToSolution() const
this->c_block_transfer.cluster_lengths_m_block_m_wave_m_per_Xdl_n_block_n_wave_n_per_Xdl},
{"CDEBlockTransferScalarPerVector_NPerBlock",
std::to_string(this->c_block_transfer.scalar_per_vector_n_wave_n_per_Xdl)},
{"LoopScheduler", ToString(this->loop_scheduler)},
{"PipelineVersion", ToString(this->pipeline_version)},
};
return Solution{InterpolateString(DeviceGemmMultipleD_Xdl_CShuffleTemplate, values),
......
codegen/src/types.cpp
View file @ d43cd4ad
......@@ -56,6 +56,26 @@ std::string ToString(GemmType gt)
throw std::runtime_error("Incorrect gemm type");
}
std::string ToString(LoopScheduler ls)
{
switch(ls)
{
case LoopScheduler::Default: return "ck::LoopScheduler::Default";
case LoopScheduler::Interwave: return "ck::LoopScheduler::Interwave";
}
throw std::runtime_error("Incorrect LoopScheduler type");
}
std::string ToString(PipelineVersion pv)
{
switch(pv)
{
case PipelineVersion::v1: return "ck::PipelineVersion::v1";
case PipelineVersion::v2: return "ck::PipelineVersion::v2";
}
throw std::runtime_error("Incorrect PipelineVersion type");
}
std::string SequenceStr(const std::vector<int>& v)
{
return "ck::Sequence<" +
......
codegen/test/common.hpp
View file @ d43cd4ad
......@@ -15,7 +15,8 @@ std::vector<rtc::src_file> get_headers_for_test()
auto hs = ck::host::GetHeaders();
std::transform(
hs.begin(), hs.end(), std::back_inserter(result), [&](const auto& p) -> rtc::src_file {
return {p.first, p.second};
std::string sec(p.second.begin(), p.second.end());
return {p.first, sec};
});
return result;
}
......
codegen/test/gemm_multiple_d.cpp
View file @ d43cd4ad
#include "ck/host/device_gemm_multiple_d/problem.hpp"
#include "ck/host/device_gemm_multiple_d/operation.hpp"
#include "ck/host/device_batched_gemm_softmax_gemm/problem.hpp"
#include "ck/host/device_batched_gemm_softmax_gemm/operation.hpp"
#include "ck/host/headers.hpp"
#include "ck/host/stringutils.hpp"
#include "ck/host/utils.hpp"
......@@ -15,13 +17,59 @@
using half = _Float16;
// using half = __fp16;
// NOLINTNEXTLINE
const char* const disable_warning_pragma = R"__migraphx__(
#pragma clang diagnostic push
#pragma clang diagnostic ignored "-Weverything"
${content}
#pragma clang diagnostic pop
)__migraphx__";
template <class P>
std::string ck_disable_warnings(P p)
{
return ck::host::InterpolateString(disable_warning_pragma,
{{"content", std::string{p.data(), p.size()}}});
}
static std::unordered_map<std::string, std::string> create_ck_header_strings()
{
std::unordered_map<std::string, std::string> result;
auto ck_headers = ck::host::GetHeaders();
std::transform(
ck_headers.begin(), ck_headers.end(), std::inserter(result, result.begin()), [&](auto& p) {
return std::pair<std::string, std::string>(p.first, ck_disable_warnings(p.second));
});
return result;
}
static std::vector<rtc::src_file> create_ck_headers()
{
static const auto& header_strings = create_ck_header_strings();
std::vector<rtc::src_file> srcs;
std::transform(
header_strings.begin(), header_strings.end(), std::back_inserter(srcs), [&](auto& p) -> rtc::src_file {
std::string sec(p.second.begin(), p.second.end());
return {p.first, sec};
});
return srcs;
}
static inline const std::vector<rtc::src_file>& ck_headers()
{
static const auto& headers = create_ck_headers();
return headers;
}
std::vector<rtc::src_file> get_headers_for_test()
{
std::vector<rtc::src_file> result;
auto hs = ck::host::GetHeaders();
std::transform(
hs.begin(), hs.end(), std::back_inserter(result), [&](const auto& p) -> rtc::src_file {
return {p.first, p.second};
std::string sec(p.second.begin(), p.second.end());
return {p.first, sec};
});
return result;
}
......@@ -130,10 +178,13 @@ const std::string gemm_compile_check = R"__ck__(
extern "C" __global__ void f(const ck::half_t* a, const ck::half_t* b, ck::half_t* c) {
using G = ${template};
constexpr auto desc = ${template}::make_descriptor(ck::make_naive_tensor_descriptor_packed(ck::make_tuple(${m}, ${k})),
ck::make_naive_tensor_descriptor(ck::make_tuple(${n}, ${k}), ck::make_tuple(1, ${n})),
ck::make_tuple(),
ck::make_naive_tensor_descriptor_packed(ck::make_tuple(${m}, ${n})));
constexpr auto desc =
G::make_descriptor(ck::make_naive_tensor_descriptor_packed(ck::make_tuple(${m},
${k})),
ck::make_naive_tensor_descriptor(ck::make_tuple(${n},
${k}), ck::make_tuple(1, ${n})), ck::make_tuple(),
ck::make_naive_tensor_descriptor_packed(ck::make_tuple(${m},
${n})));
static_assert(desc.IsValid(), "Invalid ck gemm.");
......@@ -163,23 +214,32 @@ TEST_CASE(test_problem_kernel)
std::string epilogue = "";
std::string prologue = "";
for(auto solution : prob.GetSolutions("gfx90a", prologue, epilogue))
auto solutions = prob.GetSolutions("gfx90a", prologue, epilogue);
std::cout << "Num solutions: " << solutions.size() << std::endl;
for(auto i = 0; i < solutions.size(); ++i)
{
auto src = ck::host::InterpolateString(gemm_compile_check,
{{"include", prob.GetIncludeHeader()},
{"template", solution.ToTemplateString()},
{"m", std::to_string(prob.M)},
{"n", std::to_string(prob.N)},
{"k", std::to_string(prob.K)}});
auto srcs = get_headers_for_test();
srcs.push_back({"main.cpp", src});
rtc::compile_options options;
std::cout << "Testing solution " << std::to_string(i + 1) << std::endl;
auto&& solution = solutions[i];
auto src = ck::host::InterpolateString(gemm_compile_check,
{{"include", prob.GetIncludeHeader()},
{"template", solution.ToTemplateString()},
{"m", std::to_string(prob.M)},
{"n", std::to_string(prob.N)},
{"k", std::to_string(prob.K)}});
// auto srcs = get_headers_for_test();
// srcs.push_back({"main.cpp", src});
// rtc::compile_options options;
// options.kernel_name = "f";
rtc::hip_compile_options options;
options.kernel_name = "f";
auto k = rtc::compile_kernel(srcs, options);
auto block_size = solution.GetTemplateParameter<std::size_t>("BlockSize");
auto m_per_block = solution.GetTemplateParameter<std::size_t>("MPerBlock");
auto n_per_block = solution.GetTemplateParameter<std::size_t>("NPerBlock");
auto grid_size = ck::host::integer_divide_ceil(prob.M, m_per_block) *
options.additional_src_files = ck_headers();
// auto k = rtc::compile_kernel(srcs, options);
std::cout << src << std::endl;
auto k = rtc::compile_hip_code_object(src, options);
auto block_size = solution.GetTemplateParameter<std::size_t>("BlockSize");
auto m_per_block = solution.GetTemplateParameter<std::size_t>("MPerBlock");
auto n_per_block = solution.GetTemplateParameter<std::size_t>("NPerBlock");
auto grid_size = ck::host::integer_divide_ceil(prob.M, m_per_block) *
ck::host::integer_divide_ceil(prob.N, n_per_block);
k.launch(nullptr, grid_size * block_size, block_size)(a.data(), b.data(), c.data());
......@@ -187,4 +247,34 @@ TEST_CASE(test_problem_kernel)
}
}
TEST_CASE(test_gemm_softmax_gemm)
{
ck::host::device_batched_gemm_softmax_gemm::Problem prob;
prob.TransA = false;
prob.TransB = true;
prob.TransB1 = false;
prob.TransC = false;
prob.M = 1024;
prob.N = 1024;
prob.K = 1024;
prob.O = 1024;
check_all<half> check;
auto a = to_gpu(generate_buffer<half>(1024 * 1024, 0));
auto b = to_gpu(generate_buffer<half>(1024 * 1024, 1));
auto b1 = to_gpu(generate_buffer<half>(1024 * 1024, 2));
auto c = to_gpu(generate_buffer<half>(1024 * 1024, 3));
std::string epilogue = "";
std::string prologue = "";
auto solutions = prob.GetSolutions("gfx90a", prologue, epilogue);
std::cout << "Num solutions: " << solutions.size() << std::endl;
for(auto i = 0; i < solutions.size(); ++i) {
std::cout << "Solution " << i << std::endl;
std::cout << solutions[i].ToTemplateString() << std::endl;
std::cout << std::endl;
}
}
int main(int argc, const char* argv[]) { test::run(argc, argv); }
codegen/test/rtc/include/rtc/compile_kernel.hpp
View file @ d43cd4ad
......@@ -4,6 +4,7 @@
#include <rtc/kernel.hpp>
#include <ck/filesystem.hpp>
#include <string>
#include <functional>
namespace rtc {
......@@ -19,9 +20,36 @@ struct compile_options
std::string kernel_name = "main";
};
struct hip_compile_options
{
std::size_t global;
std::size_t local;
std::string kernel_name = "kernel";
std::string params = "";
std::vector<src_file> additional_src_files = {};
/**
* @brief Set the launch parameters but allow v to override the values
*
* @param v A value class which can have a "global" and/or "local" keys to override the default
* global and local
* @param compute_global A function used to compute the global based on the local
* @param default_local The defaul local to use if its missing from the v parameter
*/
void set_launch_params(const std::function<std::size_t(std::size_t local)>& compute_global,
std::size_t default_local = 1024);
void set_launch_params(std::size_t default_global, std::size_t default_local = 1024)
{
set_launch_params([=](auto) { return default_global; }, default_local);
}
};
kernel compile_kernel(const std::vector<src_file>& src,
compile_options options = compile_options{});
kernel compile_hip_code_object(const std::string& content, hip_compile_options options);
} // namespace rtc
#endif
codegen/test/rtc/include/rtc/hip.hpp
View file @ d43cd4ad
......@@ -4,6 +4,7 @@
#include <hip/hip_runtime_api.h>
#include <memory>
#include <string>
#include <stdexcept>
namespace rtc {
......
codegen/test/rtc/src/compile_kernel.cpp
View file @ d43cd4ad
#include "rtc/hip.hpp"
#include <rtc/compile_kernel.hpp>
#include <hip/hiprtc.h>
#include <rtc/tmp_dir.hpp>
#include <stdexcept>
#include <iostream>
#include <fstream>
#include <cassert>
#include <deque>
#include <numeric>
namespace rtc {
......@@ -100,4 +103,345 @@ kernel compile_kernel(const std::vector<src_file>& srcs, compile_options options
return kernel{obj.data(), options.kernel_name};
}
struct hiprtc_src_file
{
hiprtc_src_file() = default;
hiprtc_src_file(const src_file& s) : path(s.path.string()), content(s.content) {}
std::string path;
std::string content;
template <class Self, class F>
static auto reflect(Self& self, F f)
{
return pack(f(self.path, "path"), f(self.content, "content"));
}
};
std::string hiprtc_error(hiprtcResult err, const std::string& msg)
{
return "hiprtc: " + (hiprtcGetErrorString(err) + (": " + msg));
}
void hiprtc_check_error(hiprtcResult err, const std::string& msg, const std::string& ctx)
{
if(err != HIPRTC_SUCCESS)
throw std::runtime_error(hiprtc_error(err, msg));
}
// NOLINTNEXTLINE
#define MIGRAPHX_HIPRTC(...) \
hiprtc_check_error(__VA_ARGS__, #__VA_ARGS__, "Lorem ipsum dolor sit amet")
#define MIGRAPHX_HIPRTC_THROW(error, msg) throw std::runtime_error(hiprtc_error(error, msg))
template <class F, F f> // NOLINT
struct manage_deleter
{
template <class T>
void operator()(T* x) const
{
if(x != nullptr)
{
(void)f(x);
}
}
};
template <class T, class F, F f> // NOLINT
using manage_ptr = std::unique_ptr<T, manage_deleter<F, f>>;
#define MIGRAPHX_MANAGE_PTR(T, F) manage_ptr<std::remove_pointer_t<T>, decltype(&F), &F> // NOLINT
// Workaround hiprtc's broken API
void hiprtc_program_destroy(hiprtcProgram prog) { hiprtcDestroyProgram(&prog); }
using hiprtc_program_ptr = MIGRAPHX_MANAGE_PTR(hiprtcProgram, hiprtc_program_destroy);
template <class... Ts>
hiprtc_program_ptr hiprtc_program_create(Ts... xs)
{
hiprtcProgram prog = nullptr;
auto result = hiprtcCreateProgram(&prog, xs...);
hiprtc_program_ptr p{prog};
if(result != HIPRTC_SUCCESS)
MIGRAPHX_HIPRTC_THROW(result, "Create program failed.");
return p;
}
bool starts_with(const std::string& value, const std::string& prefix)
{
if(prefix.size() > value.size())
return false;
else
return std::equal(prefix.begin(), prefix.end(), value.begin());
}
bool ends_with(const std::string& value, const std::string& suffix)
{
if(suffix.size() > value.size())
return false;
else
return std::equal(suffix.rbegin(), suffix.rend(), value.rbegin());
}
std::vector<std::string> split_string(const std::string& s, char delim)
{
std::vector<std::string> elems;
std::stringstream ss(s + delim);
std::string item;
while(std::getline(ss, item, delim))
{
elems.push_back(item);
}
return elems;
}
template <class Strings>
inline std::string join_strings(Strings strings, const std::string& delim)
{
auto it = strings.begin();
if(it == strings.end())
return "";
auto nit = std::next(it);
return std::accumulate(nit, strings.end(), *it, [&](std::string x, std::string y) {
return std::move(x) + delim + std::move(y);
});
}
struct hiprtc_program
{
struct string_array
{
std::deque<std::string> strings{};
std::vector<const char*> c_strs{};
string_array() {}
string_array(const string_array&) = delete;
std::size_t size() const { return strings.size(); }
const char** data() { return c_strs.data(); }
void push_back(std::string s)
{
strings.push_back(std::move(s));
c_strs.push_back(strings.back().c_str());
}
};
hiprtc_program_ptr prog = nullptr;
string_array headers{};
string_array include_names{};
std::string cpp_src = "";
std::string cpp_name = "";
hiprtc_program(const std::string& src, const std::string& name = "main.cpp")
: cpp_src(src), cpp_name(name)
{
create_program();
}
hiprtc_program(std::vector<src_file> srcs)
{
for(auto&& src : srcs)
{
if(ends_with(src.path, ".cpp"))
{
cpp_src = std::move(src.content);
cpp_name = std::move(src.path);
}
else
{
headers.push_back(std::move(src.content));
include_names.push_back(std::move(src.path));
}
}
create_program();
}
void create_program()
{
assert(not cpp_src.empty());
assert(not cpp_name.empty());
assert(headers.size() == include_names.size());
prog = hiprtc_program_create(cpp_src.c_str(),
cpp_name.c_str(),
headers.size(),
headers.data(),
include_names.data());
}
void compile(const std::vector<std::string>& options, bool quiet = false) const
{
// if(enabled(MIGRAPHX_TRACE_HIPRTC{}))
// std::cout << "hiprtc " << join_strings(options, " ") << " " << cpp_name << std::endl;
std::vector<const char*> c_options;
std::transform(options.begin(),
options.end(),
std::back_inserter(c_options),
[](const std::string& s) { return s.c_str(); });
std::cout << "BEFORE HIPRTC COMPILE" << std::endl;
auto result = hiprtcCompileProgram(prog.get(), c_options.size(), c_options.data());
auto prog_log = log();
if(not prog_log.empty() and not quiet)
{
std::cerr << prog_log << std::endl;
}
if(result != HIPRTC_SUCCESS)
throw std::runtime_error("Compilation failed.");
}
std::string log() const
{
std::size_t n = 0;
MIGRAPHX_HIPRTC(hiprtcGetProgramLogSize(prog.get(), &n));
if(n == 0)
return {};
std::string buffer(n, '\0');
MIGRAPHX_HIPRTC(hiprtcGetProgramLog(prog.get(), buffer.data()));
assert(buffer.back() != 0);
return buffer;
}
std::vector<char> get_code_obj() const
{
std::size_t n = 0;
MIGRAPHX_HIPRTC(hiprtcGetCodeSize(prog.get(), &n));
std::vector<char> buffer(n);
MIGRAPHX_HIPRTC(hiprtcGetCode(prog.get(), buffer.data()));
return buffer;
}
};
std::vector<std::vector<char>> compile_hip_src_with_hiprtc(std::vector<src_file> srcs,
const std::string& params,
const std::string& arch)
{
hiprtc_program prog(std::move(srcs));
auto options = split_string(params, ' ');
options.push_back("-DMIGRAPHX_USE_HIPRTC=1");
if(true)
{
options.push_back("-DMIGRAPHX_HAS_DPP=0");
options.push_back("-DMIGRAPHX_ENABLE_HIPRTC_WORKAROUNDS=1");
options.push_back("-Wno-reserved-identifier");
options.push_back("-Wno-unused-parameter");
options.push_back("-Wno-gnu-line-marker");
options.push_back("-Wno-old-style-cast");
}
if(true)
options.push_back("-DMIGRAPHX_DEBUG");
if(std::none_of(options.begin(), options.end(), [](const std::string& s) {
return starts_with(s, "--std=") or starts_with(s, "-std=");
}))
options.push_back("-std=c++17");
options.push_back("-fno-gpu-rdc");
options.push_back("-O3");
options.push_back("-Wno-cuda-compat");
options.push_back("--offload-arch=" + arch);
prog.compile(options);
return {prog.get_code_obj()};
}
bool hip_has_flags(const std::vector<std::string>& flags)
{
hiprtc_program prog{" "};
try
{
prog.compile(flags, true);
return true;
}
catch(...)
{
return false;
}
}
bool hip_accept_non_uniform_wg()
{
static bool non_uniform_wg = hip_has_flags({"-fno-offload-uniform-block"});
return non_uniform_wg;
}
static std::vector<std::string> get_compiler_warnings()
{
std::vector<std::string> warnings = {
"-Weverything",
"-Wno-c++98-compat",
"-Wno-c++98-compat-pedantic",
"-Wno-conversion",
"-Wno-double-promotion",
"-Wno-exit-time-destructors",
"-Wno-extra-semi",
"-Wno-extra-semi-stmt",
"-Wno-float-conversion",
"-Wno-gnu-anonymous-struct",
"-Wno-gnu-zero-variadic-macro-arguments",
"-Wno-missing-prototypes",
"-Wno-nested-anon-types",
"-Wno-padded",
"-Wno-shorten-64-to-32",
"-Wno-sign-conversion",
"-Wno-sign-compare",
"-Wno-unused-command-line-argument",
"-Wno-weak-vtables",
"-Wno-c99-extensions",
};
if(hip_has_flags({"-Werror", "-Wunsafe-buffer-usage"}))
warnings.push_back("-Wno-unsafe-buffer-usage");
return warnings;
}
const std::vector<std::string>& compiler_warnings()
{
static std::vector<std::string> warnings = get_compiler_warnings();
return warnings;
}
kernel compile_hip_code_object(const std::string& content, hip_compile_options options)
{
assert(options.global > 0);
assert(options.local > 0);
// assert(not options.inputs.empty());
// assert(options.inputs.size() == options.virtual_inputs.size() or
// options.virtual_inputs.empty());
std::vector<src_file> srcs = options.additional_src_files;
// Neko sranje
// static auto kernels{::migraphx_kernels()};
// std::transform(
// kernels.begin(),
// kernels.end(),
// std::back_inserter(srcs),
// [](const std::pair<std::string_view, std::string_view>& elem) { return src_file{elem};
// });
srcs.emplace_back("main.cpp", content);
for (auto src : srcs) {
std::cout << src.path << std::endl;
}
// auto args_hpp =
// generate_args_hpp(options.virtual_inputs.empty() ? options.inputs :
// options.virtual_inputs);
// srcs.emplace_back("args.hpp", args_hpp);
if(options.global % options.local != 0 and hip_accept_non_uniform_wg())
options.params += " -fno-offload-uniform-block";
else
assert(options.global % options.local == 0);
options.params += " -DMIGRAPHX_NGLOBAL=" + std::to_string(options.global);
options.params += " -DMIGRAPHX_NLOCAL=" + std::to_string(options.local);
options.params += " " + join_strings(compiler_warnings(), " ");
options.params += " -ftemplate-backtrace-limit=0";
options.params += " -Werror";
auto cos = compile_hip_src_with_hiprtc(srcs, options.params, get_device_name());
if(cos.size() != 1)
std::runtime_error("No code object");
auto& obj = cos.front();
return kernel{obj.data(), options.kernel_name};
}
} // namespace rtc
include/ck/ck.hpp
View file @ d43cd4ad
......@@ -4,16 +4,12 @@
#pragma once
#include "ck/config.h"
#include "ck/utility/env.hpp"
#ifndef __HIPCC_RTC__
#ifndef CK_DONT_USE_HIP_RUNTIME_HEADERS
#include "hip/hip_runtime.h"
#include "hip/hip_fp16.h"
#endif
// environment variable to enable logging:
// export CK_LOGGING=ON or CK_LOGGING=1 or CK_LOGGING=ENABLED
CK_DECLARE_ENV_VAR_BOOL(CK_LOGGING)
#endif
// to do: add various levels of logging with CK_LOG_LEVEL
......
include/ck/host_utility/device_prop.hpp
View file @ d43cd4ad
......@@ -3,6 +3,7 @@
#pragma once
#ifndef __HIPCC_RTC__
#include <string>
#include <map>
#include <hip/hip_runtime.h>
......@@ -96,3 +97,4 @@ inline bool is_gfx12_supported()
}
} // namespace ck
#endif
include/ck/host_utility/kernel_launch.hpp
View file @ d43cd4ad
......@@ -2,7 +2,7 @@
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#ifndef __HIPCC_RTC__
#include <hip/hip_runtime.h>
#include "ck/ck.hpp"
......@@ -160,3 +160,4 @@ float launch_and_time_kernel_with_preprocess(const StreamConfig& stream_config,
return 0;
#endif
}
#endif
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