Skip to content

GitLab

Commit 7a3b49e5 authored by Chao Liu's avatar Chao Liu
Browse files

Merge remote-tracking branch 'origin/develop' into contraction

parents e07b3d8e d3051d75
Show whitespace changes
Inline Side-by-side
Showing with 213 additions and 604 deletions
library/src/obselete_driver_offline/gemm_driver_offline.cpp deleted 100644 → 0
View file @ e07b3d8e
#include <iostream>
#include <numeric>
#include <initializer_list>
#include <cstdlib>
#include <stdlib.h>
#include <half.hpp>
#include "check_err.hpp"
#include "config.hpp"
#include "debug.hpp"
#include "print.hpp"
#include "device.hpp"
#include "host_tensor.hpp"
#include "host_tensor_generator.hpp"
#include "host_gemm.hpp"
#include "device_tensor.hpp"
#include "device_gemm_xdlops_mk_kn_mn.hpp"
#include "device_gemm_xdlops_mk_nk_mn.hpp"
#include "device_gemm_xdlops_km_kn_mn.hpp"
#include "device_gemm_xdlops_km_nk_mn.hpp"
#include "device_gemm_xdlops_mk_kn_nm.hpp"
#include "device_gemm_xdlops_mk_nk_nm.hpp"
#include "device_gemm_xdlops_km_kn_nm.hpp"
#include "device_gemm_xdlops_km_nk_nm.hpp"
#define USE_GEMM_XDL_MK_KN_MN 1
#define USE_GEMM_XDL_MK_NK_MN 1
#define USE_GEMM_XDL_KM_KN_MN 1
#define USE_GEMM_XDL_KM_NK_MN 1
#define USE_GEMM_XDL_MK_KN_NM 0
#define USE_GEMM_XDL_MK_NK_NM 0
#define USE_GEMM_XDL_KM_KN_NM 0
#define USE_GEMM_XDL_KM_NK_NM 0
enum struct GemmMatrixLayout
{
MK_KN_MN, // 0
MK_NK_MN, // 1
KM_KN_MN, // 2
KM_NK_MN, // 3
MK_KN_NM, // 4
MK_NK_NM, // 5
KM_KN_NM, // 6
KM_NK_NM // 7
};
enum struct GemmAlgo
{
Xdl_MK_KN_MN, // 0
Xdl_MK_NK_MN, // 1
Xdl_KM_KN_MN, // 2
Xdl_KM_NK_MN, // 3
Xdl_MK_KN_NM, // 4
Xdl_MK_NK_NM, // 5
Xdl_KM_KN_NM, // 6
Xdl_KM_NK_NM, // 7
};
template <typename AType, typename BType, typename CType>
void host_gemm(const Tensor<AType>& a,
const Tensor<BType>& b,
Tensor<CType>& c,
const GemmMatrixLayout layout)
{
if(layout == GemmMatrixLayout::MK_KN_MN)
{
auto f_mk_kn_mn = [&](auto m, auto n) {
const int K = a.mDesc.GetLengths()[1];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(m, k)) * static_cast<const double>(b(k, n));
}
c(m, n) = v;
};
make_ParallelTensorFunctor(f_mk_kn_mn, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::MK_NK_MN)
{
auto f_mk_nk_mn = [&](auto m, auto n) {
const int K = a.mDesc.GetLengths()[1];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(m, k)) * static_cast<const double>(b(n, k));
}
c(m, n) = v;
};
make_ParallelTensorFunctor(f_mk_nk_mn, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::KM_KN_MN)
{
auto f_km_kn_mn = [&](auto m, auto n) {
const int K = a.mDesc.GetLengths()[0];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(k, m)) * static_cast<const double>(b(k, n));
}
c(m, n) = v;
};
make_ParallelTensorFunctor(f_km_kn_mn, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::KM_NK_MN)
{
auto f_km_nk_mn = [&](auto m, auto n) {
const int K = a.mDesc.GetLengths()[0];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(k, m)) * static_cast<const double>(b(n, k));
}
c(m, n) = v;
};
make_ParallelTensorFunctor(f_km_nk_mn, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::MK_KN_NM)
{
auto f_mk_kn_nm = [&](auto n, auto m) {
const int K = a.mDesc.GetLengths()[1];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(m, k)) * static_cast<const double>(b(k, n));
}
c(n, m) = v;
};
make_ParallelTensorFunctor(f_mk_kn_nm, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::MK_NK_NM)
{
auto f_mk_nk_nm = [&](auto n, auto m) {
const int K = a.mDesc.GetLengths()[1];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(m, k)) * static_cast<const double>(b(n, k));
}
c(n, m) = v;
};
make_ParallelTensorFunctor(f_mk_nk_nm, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::KM_KN_NM)
{
auto f_km_kn_nm = [&](auto n, auto m) {
const int K = a.mDesc.GetLengths()[0];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(k, m)) * static_cast<const double>(b(k, n));
}
c(n, m) = v;
};
make_ParallelTensorFunctor(f_km_kn_nm, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else if(layout == GemmMatrixLayout::KM_NK_NM)
{
auto f_km_nk_nm = [&](auto n, auto m) {
const int K = a.mDesc.GetLengths()[0];
double v = 0;
for(int k = 0; k < K; ++k)
{
v += static_cast<const double>(a(k, m)) * static_cast<const double>(b(n, k));
}
c(n, m) = v;
};
make_ParallelTensorFunctor(f_km_nk_nm, c.mDesc.GetLengths()[0], c.mDesc.GetLengths()[1])(
std::thread::hardware_concurrency());
}
else
{
throw std::runtime_error("wrong! not supported layout");
}
}
int main(int argc, char* argv[])
{
using namespace ck;
if(argc != 12)
{
printf("arg1 to 6: layout, algo, do_verification, init_method, do_log, nrepeat\n");
printf("rest: M, N, K\n");
printf("debug_driver_gemm_xdlops_v2r3::M01, debug_driver_gemm_xdlops_v2r3::N01\n");
exit(1);
}
const auto layout = static_cast<GemmMatrixLayout>(std::stoi(argv[1]));
const auto algo = static_cast<GemmAlgo>(std::stoi(argv[2]));
const bool do_verification = std::stoi(argv[3]);
const int init_method = std::stoi(argv[4]);
const bool do_log = std::stoi(argv[5]);
const int nrepeat = std::stoi(argv[6]);
const index_t M = std::stoi(argv[7]);
const index_t N = std::stoi(argv[8]);
const index_t K = std::stoi(argv[9]);
debug::debug_driver_gemm_xdlops_v2r3::M01 = std::stoi(argv[10]);
debug::debug_driver_gemm_xdlops_v2r3::N01 = std::stoi(argv[11]);
#if 0
using ab_data_t = float;
using acc_data_t = float;
using c_data_t = float;
#elif 1
using ab_data_t = half_t;
using acc_data_t = float;
using c_data_t = half_t;
#elif 1
using ab_data_t = int8_t;
using acc_data_t = int32_t;
using c_data_t = int8_t;
#endif
std::vector<std::size_t> a_lengths_host(2), b_lengths_host(2), c_lengths_host(2);
std::vector<std::size_t> a_strides_host(2), b_strides_host(2), c_strides_host(2);
// A
if(layout == GemmMatrixLayout::MK_KN_MN || layout == GemmMatrixLayout::MK_NK_MN ||
layout == GemmMatrixLayout::MK_KN_NM || layout == GemmMatrixLayout::MK_NK_NM)
{
a_lengths_host[0] = static_cast<std::size_t>(M);
a_lengths_host[1] = static_cast<std::size_t>(K);
a_strides_host[0] = static_cast<std::size_t>(K);
a_strides_host[1] = static_cast<std::size_t>(1);
}
else
{
a_lengths_host[0] = static_cast<std::size_t>(K);
a_lengths_host[1] = static_cast<std::size_t>(M);
a_strides_host[0] = static_cast<std::size_t>(M);
a_strides_host[1] = static_cast<std::size_t>(1);
}
// B
if(layout == GemmMatrixLayout::MK_NK_MN || layout == GemmMatrixLayout::KM_NK_MN ||
layout == GemmMatrixLayout::MK_NK_NM || layout == GemmMatrixLayout::KM_NK_NM)
{
b_lengths_host[0] = static_cast<std::size_t>(N);
b_lengths_host[1] = static_cast<std::size_t>(K);
b_strides_host[0] = static_cast<std::size_t>(K);
b_strides_host[1] = static_cast<std::size_t>(1);
}
else
{
b_lengths_host[0] = static_cast<std::size_t>(K);
b_lengths_host[1] = static_cast<std::size_t>(N);
b_strides_host[0] = static_cast<std::size_t>(N);
b_strides_host[1] = static_cast<std::size_t>(1);
}
// C
if(layout == GemmMatrixLayout::MK_KN_MN || layout == GemmMatrixLayout::KM_KN_MN ||
layout == GemmMatrixLayout::MK_NK_MN || layout == GemmMatrixLayout::KM_NK_MN)
{
c_lengths_host[0] = static_cast<std::size_t>(M);
c_lengths_host[1] = static_cast<std::size_t>(N);
c_strides_host[0] = static_cast<std::size_t>(N);
c_strides_host[1] = static_cast<std::size_t>(1);
}
else
{
c_lengths_host[0] = static_cast<std::size_t>(N);
c_lengths_host[1] = static_cast<std::size_t>(M);
c_strides_host[0] = static_cast<std::size_t>(M);
c_strides_host[1] = static_cast<std::size_t>(1);
}
Tensor<ab_data_t> a(a_lengths_host, a_strides_host);
Tensor<ab_data_t> b(b_lengths_host, b_strides_host);
Tensor<c_data_t> c_host(c_lengths_host, c_strides_host);
Tensor<c_data_t> c_device(c_lengths_host, c_strides_host);
std::cout << "layout: " << layout << std::endl;
ostream_HostTensorDescriptor(a.mDesc, std::cout << "a: ");
ostream_HostTensorDescriptor(b.mDesc, std::cout << "b: ");
ostream_HostTensorDescriptor(c_host.mDesc, std::cout << "c: ");
std::size_t num_thread = 1;
switch(init_method)
{
case 0:
// no initialization
break;
case 1:
a.GenerateTensorValue(GeneratorTensor_1<ab_data_t>{}, num_thread);
b.GenerateTensorValue(GeneratorTensor_1<ab_data_t>{}, num_thread);
break;
case 2:
a.GenerateTensorValue(GeneratorTensor_1<ab_data_t>{}, num_thread);
b.GenerateTensorValue(GeneratorTensor_2<ab_data_t>{-5, 5}, num_thread);
break;
case 3:
a.GenerateTensorValue(GeneratorTensor_2<ab_data_t>{-5, 5}, num_thread);
b.GenerateTensorValue(GeneratorTensor_1<ab_data_t>{}, num_thread);
break;
case 4:
a.GenerateTensorValue(GeneratorTensor_2<ab_data_t>{-5, 5}, num_thread);
b.GenerateTensorValue(GeneratorTensor_2<ab_data_t>{-5, 5}, num_thread);
break;
default:
a.GenerateTensorValue(GeneratorTensor_3<ab_data_t>{0.0, 1.0}, num_thread);
b.GenerateTensorValue(GeneratorTensor_3<ab_data_t>{-0.5, 0.5}, num_thread);
}
#if USE_GEMM_XDL_MK_KN_MN
if(algo == GemmAlgo::Xdl_MK_KN_MN)
{
if(layout != GemmMatrixLayout::MK_KN_MN)
{
throw std::runtime_error("wrong! layout");
}
device_gemm_xdlops_mk_kn_mn<ab_data_t, acc_data_t, c_data_t>(a, b, c_device, nrepeat);
}
#endif
#if USE_GEMM_XDL_MK_NK_MN
if(algo == GemmAlgo::Xdl_MK_NK_MN)
{
if(layout != GemmMatrixLayout::MK_NK_MN)
{
throw std::runtime_error("wrong! layout");
}
device_gemm_xdlops_mk_nk_mn<ab_data_t, acc_data_t, c_data_t>(a, b, c_device, nrepeat);
}
#endif
#if USE_GEMM_XDL_KM_KN_MN
if(algo == GemmAlgo::Xdl_KM_KN_MN)
{
if(layout != GemmMatrixLayout::KM_KN_MN)
{
throw std::runtime_error("wrong! layout");
}
device_gemm_xdlops_km_kn_mn<ab_data_t, acc_data_t, c_data_t>(a, b, c_device, nrepeat);
}
#endif
#if USE_GEMM_XDL_KM_NK_MN
if(algo == GemmAlgo::Xdl_KM_NK_MN)
{
if(layout != GemmMatrixLayout::KM_NK_MN)
{
throw std::runtime_error("wrong! layout");
}
device_gemm_xdlops_km_nk_mn<ab_data_t, acc_data_t, c_data_t>(a, b, c_device, nrepeat);
}
#endif
#if USE_GEMM_XDL_MK_KN_NM
if(algo == GemmAlgo::Xdl_MK_KN_NM)
{
if(layout != GemmMatrixLayout::MK_KN_NM)
{
throw std::runtime_error("wrong! layout");
}
device_gemm_xdlops_mk_kn_nm<ab_data_t, acc_data_t, c_data_t>(a, b, c_device, nrepeat);
}
#endif
#if USE_GEMM_XDL_MK_NK_NM
if(algo == GemmAlgo::Xdl_MK_NK_NM)
{
if(layout != GemmMatrixLayout::MK_NK_NM)
{
throw std::runtime_error("wrong! layout");
}
device_gemm_xdlops_mk_nk_nm<ab_data_t, acc_data_t, c_data_t>(a, b, c_device, nrepeat);
}
#endif
#if USE_GEMM_XDL_KM_KN_NM
if(algo == GemmAlgo::Xdl_KM_KN_NM)
{
if(layout != GemmMatrixLayout::KM_KN_NM)
{
throw std::runtime_error("wrong! layout");
}
device_gemm_xdlops_km_kn_nm<ab_data_t, acc_data_t, c_data_t>(a, b, c_device, nrepeat);
}
#endif
#if USE_GEMM_XDL_KM_NK_NM
if(algo == GemmAlgo::Xdl_KM_NK_NM)
{
if(layout != GemmMatrixLayout::KM_NK_NM)
{
throw std::runtime_error("wrong! layout");
}
device_gemm_xdlops_km_nk_nm<ab_data_t, acc_data_t, c_data_t>(a, b, c_device, nrepeat);
}
#endif
if(do_verification)
{
host_gemm(a, b, c_host, layout);
ck::utils::check_err(c_device.mData, c_host.mData);
if(do_log)
{
LogRangeAsType<float>(std::cout << "a : ", a.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "b: ", b.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "c_host : ", c_host.mData, ",") << std::endl;
LogRangeAsType<float>(std::cout << "c_device: ", c_device.mData, ",") << std::endl;
}
}
}
library/src/tensor_operation_instance/gpu/CMakeLists.txt
View file @ 7a3b49e5
include_directories(BEFORE
${PROJECT_SOURCE_DIR}/include/ck
${PROJECT_SOURCE_DIR}/include/ck/utility
${PROJECT_SOURCE_DIR}/include/ck/host_utility
${PROJECT_SOURCE_DIR}/include/ck/tensor_description
${PROJECT_SOURCE_DIR}/include/ck/tensor
${PROJECT_SOURCE_DIR}/include/ck/problem_transform
${PROJECT_SOURCE_DIR}/include/ck/tensor_operation/gpu/device
${PROJECT_SOURCE_DIR}/include/ck/tensor_operation/gpu/grid
${PROJECT_SOURCE_DIR}/include/ck/tensor_operation/gpu/block
${PROJECT_SOURCE_DIR}/include/ck/tensor_operation/gpu/warp
${PROJECT_SOURCE_DIR}/include/ck/tensor_operation/gpu/thread
${PROJECT_SOURCE_DIR}/include/ck/tensor_operation/gpu/element
${PROJECT_SOURCE_DIR}/library/include/ck/library/host_tensor
${PROJECT_SOURCE_DIR}/library/include/ck/library/host
${PROJECT_SOURCE_DIR}/library/include/ck/library/tensor_operation_instance
${PROJECT_SOURCE_DIR}/library/include/ck/library/tensor_operation_instance/gpu/reduce
${PROJECT_SOURCE_DIR}/external/include/half
)
function(add_instance_library INSTANCE_NAME)
message("adding instance ${INSTANCE_NAME}")
add_library(${INSTANCE_NAME} OBJECT ${ARGN})
......@@ -30,19 +10,20 @@ add_subdirectory(gemm_bias2d)
add_subdirectory(gemm_bias_relu)
add_subdirectory(gemm_bias_relu_add)
add_subdirectory(gemm_reduce)
add_subdirectory(gemm_bias_add_reduce)
add_subdirectory(batched_gemm)
add_subdirectory(conv1d_fwd)
add_subdirectory(conv2d_fwd)
add_subdirectory(conv3d_fwd)
add_subdirectory(conv2d_fwd_bias_relu)
add_subdirectory(conv2d_fwd_bias_relu_add)
add_subdirectory(conv2d_fwd_bias_relu_atomic_add)
add_subdirectory(conv2d_bwd_data)
add_subdirectory(reduce)
add_subdirectory(convnd_bwd_data)
add_subdirectory(grouped_gemm)
add_subdirectory(conv2d_bwd_weight)
add_subdirectory(batched_gemm_reduce)
add_subdirectory(gemm_add_add_fastgelu)
add_library(device_operations STATIC
$<TARGET_OBJECTS:device_conv1d_fwd_instance>
......@@ -51,7 +32,6 @@ add_library(device_operations STATIC
$<TARGET_OBJECTS:device_conv2d_fwd_instance>
$<TARGET_OBJECTS:device_conv2d_fwd_bias_relu_instance>
$<TARGET_OBJECTS:device_conv2d_fwd_bias_relu_add_instance>
$<TARGET_OBJECTS:device_conv2d_fwd_bias_relu_atomic_add_instance>
$<TARGET_OBJECTS:device_gemm_instance>
$<TARGET_OBJECTS:device_gemm_bias_relu_instance>
$<TARGET_OBJECTS:device_gemm_bias_relu_add_instance>
......@@ -62,7 +42,7 @@ add_library(device_operations STATIC
$<TARGET_OBJECTS:device_conv2d_bwd_weight_instance>
$<TARGET_OBJECTS:device_batched_gemm_reduce_instance>
$<TARGET_OBJECTS:device_conv3d_fwd_instance>
device_conv2d.cpp
$<TARGET_OBJECTS:device_gemm_add_add_fastgelu_instance>
)
add_library(composablekernels::device_operations ALIAS device_operations)
......@@ -70,8 +50,8 @@ add_library(composablekernels::device_operations ALIAS device_operations)
set(DEV_OPS_INC_DIRS
${PROJECT_SOURCE_DIR}/include/ck/
${PROJECT_SOURCE_DIR}/library/include/ck/
${PROJECT_SOURCE_DIR}/external/include/
)
target_compile_features(device_operations PUBLIC)
set_target_properties(device_operations PROPERTIES POSITION_INDEPENDENT_CODE ON)
target_include_directories(device_operations PUBLIC
......@@ -90,15 +70,16 @@ target_include_directories(device_operations PUBLIC
$<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}/ck/library/host>
$<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}/ck/library/tensor_operation_instance>
$<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}/ck/library/tensor_operation_instance/gpu/reduce>
$<INSTALL_INTERFACE:${CMAKE_INSTALL_INCLUDEDIR}/ck/half>
)
#once new arches are enabled make this an option on the main cmake file
# and pass down here to be exported
target_compile_options(device_operations
PRIVATE --offload-arch=gfx908
target_compile_options(device_operations PRIVATE
--offload-arch=gfx908
--offload-arch=gfx90a
)
# install(TARGETS device_operations LIBRARY DESTINATION lib)
install(TARGETS device_operations
EXPORT device_operationsTargets
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_bf16_bf16_bf16_gkm_gkn_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_bf16_bf16_bf16_gkm_gnk_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_bf16_bf16_bf16_gmk_gkn_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_bf16_bf16_bf16_gmk_gnk_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_f16_f16_f16_gkm_gkn_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_f16_f16_f16_gkm_gnk_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_f16_f16_f16_gmk_gkn_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_f16_f16_f16_gmk_gnk_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_f32_f32_f32_gkm_gkn_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_f32_f32_f32_gkm_gnk_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_f32_f32_f32_gmk_gkn_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_f32_f32_f32_gmk_gnk_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_int8_int8_int8_gkm_gkn_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_int8_int8_int8_gkm_gnk_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_int8_int8_int8_gmk_gkn_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_int8_int8_int8_gmk_gnk_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_xdl.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......
library/src/tensor_operation_instance/gpu/batched_gemm_reduce/device_batched_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_gkm_gkn_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_reduce_xdl_cshuffle.hpp"
#include "element_wise_operation.hpp"
#include "reduction_operator.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/utility/reduction_operator.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_reduce_xdl_cshuffle.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......@@ -21,11 +26,11 @@ template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using ReduceSum = ck::reduce::Add<F32>;
using ReduceSum = ck::reduce::Add;
using ReduceOps = ck::Tuple<ReduceSum, ReduceSum>;
using Identity = ck::tensor_operation::element_wise::UnaryIdentic<F32, F32, false>;
using Square = ck::tensor_operation::element_wise::UnarySquare<F32, F32, false>;
using Identity = ck::tensor_operation::element_wise::PassThrough;
using Square = ck::tensor_operation::element_wise::UnarySquare;
using DInElementOps = ck::Tuple<Identity, Square>;
using DOutElementOps = ck::Tuple<Identity, Identity>;
......@@ -62,12 +67,9 @@ using device_batched_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_gkm_gkn_gmn_in
>;
void add_device_batched_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_gkm_gkn_gmn_instances(
std::vector<DeviceGemmReducePtr<DPtrsGlobal,
PassThrough,
PassThrough,
PassThrough,
DInElementOps,
DOutElementOps>>& instances)
std::vector<
DeviceGemmReducePtr<PassThrough, PassThrough, PassThrough, DInElementOps, DOutElementOps>>&
instances)
{
add_device_operation_instances(
instances,
......
library/src/tensor_operation_instance/gpu/batched_gemm_reduce/device_batched_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_gkm_gnk_gmn_instance.cpp
View file @ 7a3b49e5
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_reduce_xdl_cshuffle.hpp"
#include "element_wise_operation.hpp"
#include "reduction_operator.hpp"
#include "device_operation_instance.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/utility/reduction_operator.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_batched_gemm_reduce_xdl_cshuffle.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......@@ -21,11 +26,11 @@ template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using ReduceSum = ck::reduce::Add<F32>;
using ReduceSum = ck::reduce::Add;
using ReduceOps = ck::Tuple<ReduceSum, ReduceSum>;
using Identity = ck::tensor_operation::element_wise::UnaryIdentic<F32, F32, false>;
using Square = ck::tensor_operation::element_wise::UnarySquare<F32, F32, false>;
using Identity = ck::tensor_operation::element_wise::PassThrough;
using Square = ck::tensor_operation::element_wise::UnarySquare;
using DInElementOps = ck::Tuple<Identity, Square>;
using DOutElementOps = ck::Tuple<Identity, Identity>;
......@@ -62,12 +67,9 @@ using device_batched_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_gkm_gnk_gmn_in
>;
void add_device_batched_gemm_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_gkm_gnk_gmn_instances(
std::vector<DeviceGemmReducePtr<DPtrsGlobal,
PassThrough,
PassThrough,
PassThrough,
DInElementOps,
DOutElementOps>>& instances)
std::vector<
DeviceGemmReducePtr<PassThrough, PassThrough, PassThrough, DInElementOps, DOutElementOps>>&
instances)
{
add_device_operation_instances(
instances,
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment