Skip to content

GitLab

Commit 4511f877 authored by Chao Liu's avatar Chao Liu
Browse files

refactor profiler

parent 519b6aaf
Expand all Hide whitespace changes
Inline Side-by-side
Showing with 434 additions and 739 deletions
library/include/ck/library/reference_tensor_operation/cpu/reference_gemm.hpp
View file @ 4511f877
......@@ -62,8 +62,8 @@ struct ReferenceGemm : public device::BaseOperator
float v_a;
float v_b;
arg.a_element_op_(v_a, static_cast<const float>(arg.a_m_k_(m, k)));
arg.b_element_op_(v_b, static_cast<const float>(arg.b_k_n_(k, n)));
arg.a_element_op_(v_a, ck::type_convert<const float>(arg.a_m_k_(m, k)));
arg.b_element_op_(v_b, ck::type_convert<const float>(arg.b_k_n_(k, n)));
v_acc += v_a * v_b;
}
......@@ -72,7 +72,7 @@ struct ReferenceGemm : public device::BaseOperator
arg.c_element_op_(v_c, v_acc);
arg.c_m_n_(m, n) = v_c;
arg.c_m_n_(m, n) = ck::type_convert<CDataType>(v_c);
};
make_ParallelTensorFunctor(
......
library/src/tensor_operation_instance/gpu/CMakeLists.txt
View file @ 4511f877
......@@ -24,6 +24,7 @@ function(add_instance_library INSTANCE_NAME)
endfunction(add_instance_library INSTANCE_NAME)
add_subdirectory(gemm)
add_subdirectory(gemm_splitk)
add_subdirectory(gemm_bias2d)
add_subdirectory(gemm_bias_relu)
add_subdirectory(gemm_bias_relu_add)
......@@ -34,7 +35,6 @@ 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)
......
library/src/tensor_operation_instance/gpu/batched_gemm/CMakeLists.txt
View file @ 4511f877
......@@ -12,10 +12,10 @@ set(DEVICE_BATCHED_GEMM_INSTANCE_SOURCE
device_batched_gemm_xdl_f32_f32_f32_gmk_gnk_gmn_instance.cpp;
device_batched_gemm_xdl_f32_f32_f32_gkm_gkn_gmn_instance.cpp;
device_batched_gemm_xdl_f32_f32_f32_gkm_gnk_gmn_instance.cpp;
device_batched_gemm_xdl_int8_int8_int8_gmk_gkn_gmn_instance.cpp;
device_batched_gemm_xdl_int8_int8_int8_gmk_gnk_gmn_instance.cpp;
device_batched_gemm_xdl_int8_int8_int8_gkm_gkn_gmn_instance.cpp;
device_batched_gemm_xdl_int8_int8_int8_gkm_gnk_gmn_instance.cpp;
device_batched_gemm_xdl_i8_i8_i8_gmk_gkn_gmn_instance.cpp;
device_batched_gemm_xdl_i8_i8_i8_gmk_gnk_gmn_instance.cpp;
device_batched_gemm_xdl_i8_i8_i8_gkm_gkn_gmn_instance.cpp;
device_batched_gemm_xdl_i8_i8_i8_gkm_gnk_gmn_instance.cpp;
)
add_library(device_batched_gemm_instance SHARED ${DEVICE_BATCHED_GEMM_INSTANCE_SOURCE})
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_int8_int8_int8_gkm_gkn_gmn_instance.cpp → library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_i8_i8_i8_gkm_gkn_gmn_instance.cpp
View file @ 4511f877
......@@ -23,7 +23,7 @@ using AccData = int32_t;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[m, k] * b[n, k] = c[m, n]
using device_batched_gemm_xdl_int8_int8_int8_gkm_gkn_gmn_instances = std::tuple<
using device_batched_gemm_xdl_i8_i8_i8_gkm_gkn_gmn_instances = std::tuple<
// clang-format off
//##########| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
//##########| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
......@@ -53,11 +53,11 @@ using device_batched_gemm_xdl_int8_int8_int8_gkm_gkn_gmn_instances = std::tuple<
// clang-format on
>;
void add_device_batched_gemm_xdl_int8_int8_int8_gkm_gkn_gmn_instances(
void add_device_batched_gemm_xdl_i8_i8_i8_gkm_gkn_gmn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_batched_gemm_xdl_int8_int8_int8_gkm_gkn_gmn_instances{});
device_batched_gemm_xdl_i8_i8_i8_gkm_gkn_gmn_instances{});
}
} // namespace device_batched_gemm_instance
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_i8_i8_i8_gkm_gnk_gmn_instance.cpp 0 → 100644
View file @ 4511f877
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_batched_gemm_instance {
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using AData = int8_t;
using BData = int8_t;
using CData = int8_t;
using AccData = int32_t;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[m, k] * b[n, k] = c[m, n]
using device_batched_gemm_xdl_i8_i8_i8_gkm_gnk_gmn_instances = std::tuple<
// clang-format off
//##################| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
//##################| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//##################| | | | | | | | Operation| Operation| Operation| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//##################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 64, 64, 64, 4, 16, 32, 32, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 32, 4, 16, 32, 32, 2, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 32, 128, 4, 16, 32, 32, 1, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 64, 64, 32, 4, 16, 32, 32, 2, 1, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 64, 32, 64, 4, 16, 32, 32, 1, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>
// clang-format on
>;
void add_device_batched_gemm_xdl_i8_i8_i8_gkm_gnk_gmn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_batched_gemm_xdl_i8_i8_i8_gkm_gnk_gmn_instances{});
}
} // namespace device_batched_gemm_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_int8_int8_int8_gmk_gkn_gmn_instance.cpp → library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_i8_i8_i8_gmk_gkn_gmn_instance.cpp
View file @ 4511f877
......@@ -23,7 +23,7 @@ using AccData = int32_t;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[m, k] * b[n, k] = c[m, n]
using device_batched_gemm_xdl_int8_int8_int8_gmk_gkn_gmn_instances = std::tuple<
using device_batched_gemm_xdl_i8_i8_i8_gmk_gkn_gmn_instances = std::tuple<
// clang-format off
//##########| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
//##########| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
......@@ -53,11 +53,11 @@ using device_batched_gemm_xdl_int8_int8_int8_gmk_gkn_gmn_instances = std::tuple<
// clang-format on
>;
void add_device_batched_gemm_xdl_int8_int8_int8_gmk_gkn_gmn_instances(
void add_device_batched_gemm_xdl_i8_i8_i8_gmk_gkn_gmn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_batched_gemm_xdl_int8_int8_int8_gmk_gkn_gmn_instances{});
device_batched_gemm_xdl_i8_i8_i8_gmk_gkn_gmn_instances{});
}
} // namespace device_batched_gemm_instance
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_int8_int8_int8_gmk_gnk_gmn_instance.cpp → library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_i8_i8_i8_gmk_gnk_gmn_instance.cpp
View file @ 4511f877
......@@ -23,7 +23,7 @@ using AccData = int32_t;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[m, k] * b[n, k] = c[m, n]
using device_batched_gemm_xdl_int8_int8_int8_gmk_gnk_gmn_instances = std::tuple<
using device_batched_gemm_xdl_i8_i8_i8_gmk_gnk_gmn_instances = std::tuple<
// clang-format off
//##########| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
//##########| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
......@@ -45,11 +45,11 @@ using device_batched_gemm_xdl_int8_int8_int8_gmk_gnk_gmn_instances = std::tuple<
// clang-format on
>;
void add_device_batched_gemm_xdl_int8_int8_int8_gmk_gnk_gmn_instances(
void add_device_batched_gemm_xdl_i8_i8_i8_gmk_gnk_gmn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_batched_gemm_xdl_int8_int8_int8_gmk_gnk_gmn_instances{});
device_batched_gemm_xdl_i8_i8_i8_gmk_gnk_gmn_instances{});
}
} // namespace device_batched_gemm_instance
......
library/src/tensor_operation_instance/gpu/batched_gemm/device_batched_gemm_xdl_int8_int8_int8_gkm_gnk_gmn_instance.cpp deleted 100644 → 0
View file @ 519b6aaf
#include <stdlib.h>
#include "config.hpp"
#include "device_batched_gemm_xdl.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_batched_gemm_instance {
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using AData = int8_t;
using BData = int8_t;
using CData = int8_t;
using AccData = int32_t;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[m, k] * b[n, k] = c[m, n]
using device_batched_gemm_xdl_int8_int8_int8_gkm_gnk_gmn_instances = std::tuple<
// clang-format off
//##########| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
//##########| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//##########| | | | | | | | Operation| Operation| Operation| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//##########| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 64, 64, 64, 4, 16, 32, 32, 2, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 32, 4, 16, 32, 32, 2, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 32, 128, 4, 16, 32, 32, 1, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 64, 64, 32, 4, 16, 32, 32, 2, 1, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 64, 32, 64, 4, 16, 32, 32, 1, 2, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 16, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 256, 128, 4, 16, 32, 32, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 256, 4, 16, 32, 32, 2, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 128, 4, 16, 32, 32, 4, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 128, 4, 16, 32, 32, 2, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 64, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 64, 128, 4, 16, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 16, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 64, 4, 16, 32, 32, 2, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>,
DeviceBatchedGemmXdl< AData, BData, CData, AccData, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 64, 128, 4, 16, 32, 32, 1, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 16, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, true, 7, 1>
// clang-format on
>;
void add_device_batched_gemm_xdl_int8_int8_int8_gkm_gnk_gmn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_batched_gemm_xdl_int8_int8_int8_gkm_gnk_gmn_instances{});
}
} // namespace device_batched_gemm_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/conv2d_fwd_bias_relu_atomic_add/CMakeLists.txt deleted 100644 → 0
View file @ 519b6aaf
# device_conv2d_fwd_bias_relu_atomic_add_instance
set(DEVICE_CONV2D_FWD_BIAS_RELU_ATOMIC_ADD_INSTANCE_SOURCE
device_conv2d_fwd_xdl_c_shuffle_bias_relu_atomic_add_nhwc_kyxc_nhwk_f16_instance.cpp;
)
add_library(device_conv2d_fwd_bias_relu_atomic_add_instance SHARED ${DEVICE_CONV2D_FWD_BIAS_RELU_ATOMIC_ADD_INSTANCE_SOURCE})
target_compile_features(device_conv2d_fwd_bias_relu_atomic_add_instance PUBLIC)
set_target_properties(device_conv2d_fwd_bias_relu_atomic_add_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
install(TARGETS device_conv2d_fwd_bias_relu_atomic_add_instance LIBRARY DESTINATION lib)
clang_tidy_check(device_conv2d_fwd_bias_relu_atomic_add_instance)
library/src/tensor_operation_instance/gpu/conv2d_fwd_bias_relu_atomic_add/device_conv2d_fwd_xdl_c_shuffle_bias_relu_atomic_add_nhwc_kyxc_nhwk_f16_instance.cpp deleted 100644 → 0
View file @ 519b6aaf
#include <stdlib.h>
#include "config.hpp"
#include "device_conv2d_fwd_xdl_c_shuffle_bias_activation_nhwc_kyxc_nhwk.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_conv2d_fwd_bias_activation_atomic_add_instance {
using F16 = ck::half_t;
using F32 = float;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using AddRelu = ck::tensor_operation::element_wise::AddRelu;
static constexpr auto InMemoryAtomicAdd = ck::InMemoryDataOperationEnum::AtomicAdd;
static constexpr auto ConvFwdDefault =
ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
using device_conv2d_fwd_xdl_c_shuffle_bias_relu_atomic_add_nhwc_kyxc_nhwk_f16_instances = std::tuple<
// clang-format off
//##########################################################################################| InData| WeiData| OutData| AccData| In| Wei| Out| Out| ConvForward| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
//##########################################################################################| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| GlobalMemory| Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector|
//##########################################################################################| | | | | Operation| Operation| Operation| DataOperation| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NXdlPerWave_NWaveNPerXdl| _NWaveNPerXdl|
//##########################################################################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 8, 1, 1, 32>, 2>,
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 8, 1, 1, 32>, 2>,
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 4, 1, 1, 32>, 2>,
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 8, 1, 1, 32>, 2>,
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 8, 1, 1, 16>, 2>,
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 4, 1, 1, 32>, 2>,
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 4, 1, 1, 16>, 2>,
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 8, 1, 1, 32>, 2>,
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 8, 1, 1, 32>, 2>,
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 8, 1, 1, 16>, 2>,
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 4, 1, 1, 32>, 2>,
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 4, 1, 1, 16>, 2>,
DeviceConv2dFwdXdl_C_Shuffle_Bias_Activation_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K< F16, F16, F16, F32, PassThrough, PassThrough, AddRelu, InMemoryAtomicAdd, ConvFwdDefault, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 4, 1, 1, 16>, 2>
// clang-format on
>;
void add_device_conv2d_fwd_xdl_c_shuffle_bias_relu_atomic_add_nhwc_kyxc_nhwk_f16_instances(
std::vector<DeviceConvFwdBiasActivationPtr<PassThrough, PassThrough, AddRelu>>&
instance_container)
{
using Instances =
device_conv2d_fwd_xdl_c_shuffle_bias_relu_atomic_add_nhwc_kyxc_nhwk_f16_instances;
const auto instances = Instances{};
ck::static_for<0, std::tuple_size_v<Instances>, 1>{}([&](auto i) {
using Instance = remove_cvref_t<decltype(std::get<i>(instances))>;
auto instance = Instance{};
instance_container.push_back(std::make_unique<Instance>(instance));
});
}
} // namespace device_conv2d_fwd_bias_activation_atomic_add_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm/CMakeLists.txt
View file @ 4511f877
......@@ -8,10 +8,10 @@ set(DEVICE_GEMM_INSTANCE_SOURCE
device_gemm_xdl_f16_f16_f16_mk_nk_mn_instance.cpp;
device_gemm_xdl_f16_f16_f16_km_kn_mn_instance.cpp;
device_gemm_xdl_f16_f16_f16_km_nk_mn_instance.cpp;
device_gemm_xdl_c_shuffle_int8_int8_int8_mk_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_int8_int8_int8_mk_nk_mn_instance.cpp;
device_gemm_xdl_c_shuffle_int8_int8_int8_km_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_int8_int8_int8_km_nk_mn_instance.cpp;
device_gemm_xdl_c_shuffle_i8_i8_i8_mk_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_i8_i8_i8_mk_nk_mn_instance.cpp;
device_gemm_xdl_c_shuffle_i8_i8_i8_km_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_i8_i8_i8_km_nk_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bf16_bf16_bf16_mk_nk_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_kn_mn_instance.cpp;
......@@ -25,14 +25,6 @@ set(DEVICE_GEMM_INSTANCE_SOURCE
device_gemm_xdl_c_shuffle_f32_f32_f32_km_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_f32_f32_f32_km_nk_mn_instance.cpp;
device_gemm_xdl_c_shuffle_2_stage_f16_f16_f16_mk_nk_mn_instance.cpp;
device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_instance.cpp;
device_gemm_xdl_splitk_f32_f32_f32_mk_nk_mn_instance.cpp;
device_gemm_xdl_splitk_f32_f32_f32_km_kn_mn_instance.cpp;
device_gemm_xdl_splitk_f32_f32_f32_km_nk_mn_instance.cpp;
device_gemm_xdl_splitk_c_shuffle_f16_f16_f16_mk_kn_mn_instance.cpp;
device_gemm_xdl_splitk_c_shuffle_f16_f16_f16_mk_nk_mn_instance.cpp;
device_gemm_xdl_splitk_c_shuffle_f16_f16_f16_km_kn_mn_instance.cpp;
device_gemm_xdl_splitk_c_shuffle_f16_f16_f16_km_nk_mn_instance.cpp;
)
add_library(device_gemm_instance SHARED ${DEVICE_GEMM_INSTANCE_SOURCE})
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_int8_int8_int8_km_kn_mn_instance.cpp → library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_i8_i8_i8_km_kn_mn_instance.cpp
View file @ 4511f877
......@@ -22,7 +22,7 @@ using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// Compilation parameters for a[k, m] * b[k, n] = c[m, n]
using device_gemm_xdl_c_shuffle_int8_int8_int8_km_kn_mn_instances =
using device_gemm_xdl_c_shuffle_i8_i8_i8_km_kn_mn_instances =
std::tuple<
// clang-format off
//#####################| ALayout| BLayout| CLayout| AData| BData| CData| AccData| CShuffle| A| B| C| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
......@@ -48,11 +48,11 @@ using device_gemm_xdl_c_shuffle_int8_int8_int8_km_kn_mn_instances =
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_int8_int8_int8_km_kn_mn_instances(
void add_device_gemm_xdl_c_shuffle_i8_i8_i8_km_kn_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_gemm_xdl_c_shuffle_int8_int8_int8_km_kn_mn_instances{});
device_gemm_xdl_c_shuffle_i8_i8_i8_km_kn_mn_instances{});
}
} // namespace device_gemm_instance
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_int8_int8_int8_km_nk_mn_instance.cpp → library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_i8_i8_i8_km_nk_mn_instance.cpp
View file @ 4511f877
......@@ -22,7 +22,7 @@ using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// Compilation parameters for a[k, m] * b[n, k] = c[m, n]
using device_gemm_xdl_c_shuffle_int8_int8_int8_km_nk_mn_instances =
using device_gemm_xdl_c_shuffle_i8_i8_i8_km_nk_mn_instances =
std::tuple<
// clang-format off
//#####################| ALayout| BLayout| CLayout| AData| BData| CData| AccData| CShuffle| A| B| C| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
......@@ -48,11 +48,11 @@ using device_gemm_xdl_c_shuffle_int8_int8_int8_km_nk_mn_instances =
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_int8_int8_int8_km_nk_mn_instances(
void add_device_gemm_xdl_c_shuffle_i8_i8_i8_km_nk_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_gemm_xdl_c_shuffle_int8_int8_int8_km_nk_mn_instances{});
device_gemm_xdl_c_shuffle_i8_i8_i8_km_nk_mn_instances{});
}
} // namespace device_gemm_instance
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_int8_int8_int8_mk_kn_mn_instance.cpp → library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_i8_i8_i8_mk_kn_mn_instance.cpp
View file @ 4511f877
......@@ -22,7 +22,7 @@ using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_c_shuffle_int8_int8_int8_mk_kn_mn_instances =
using device_gemm_xdl_c_shuffle_i8_i8_i8_mk_kn_mn_instances =
std::tuple<
// clang-format off
//#####################| ALayout| BLayout| CLayout| AData| BData| CData| AccData| CShuffle| A| B| C| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
......@@ -48,11 +48,11 @@ using device_gemm_xdl_c_shuffle_int8_int8_int8_mk_kn_mn_instances =
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_int8_int8_int8_mk_kn_mn_instances(
void add_device_gemm_xdl_c_shuffle_i8_i8_i8_mk_kn_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_gemm_xdl_c_shuffle_int8_int8_int8_mk_kn_mn_instances{});
device_gemm_xdl_c_shuffle_i8_i8_i8_mk_kn_mn_instances{});
}
} // namespace device_gemm_instance
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_int8_int8_int8_mk_nk_mn_instance.cpp → library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_i8_i8_i8_mk_nk_mn_instance.cpp
View file @ 4511f877
......@@ -22,7 +22,7 @@ using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// Compilation parameters for a[m, k] * b[n, k] = c[m, n]
using device_gemm_xdl_c_shuffle_int8_int8_int8_mk_nk_mn_instances =
using device_gemm_xdl_c_shuffle_i8_i8_i8_mk_nk_mn_instances =
std::tuple<
// clang-format off
//#####################| ALayout| BLayout| CLayout| AData| BData| CData| AccData| CShuffle| A| B| C| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
......@@ -45,11 +45,11 @@ using device_gemm_xdl_c_shuffle_int8_int8_int8_mk_nk_mn_instances =
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_int8_int8_int8_mk_nk_mn_instances(
void add_device_gemm_xdl_c_shuffle_i8_i8_i8_mk_nk_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_gemm_xdl_c_shuffle_int8_int8_int8_mk_nk_mn_instances{});
device_gemm_xdl_c_shuffle_i8_i8_i8_mk_nk_mn_instances{});
}
} // namespace device_gemm_instance
......
library/src/tensor_operation_instance/gpu/gemm_splitk/CMakeLists.txt 0 → 100644
View file @ 4511f877
# device_gemm_instance
set(DEVICE_GEMM_SPLITK_INSTANCE_SOURCE
device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_instance.cpp;
device_gemm_xdl_splitk_f32_f32_f32_mk_nk_mn_instance.cpp;
device_gemm_xdl_splitk_f32_f32_f32_km_kn_mn_instance.cpp;
device_gemm_xdl_splitk_f32_f32_f32_km_nk_mn_instance.cpp;
device_gemm_xdl_splitk_c_shuffle_f16_f16_f16_mk_kn_mn_instance.cpp;
device_gemm_xdl_splitk_c_shuffle_f16_f16_f16_mk_nk_mn_instance.cpp;
device_gemm_xdl_splitk_c_shuffle_f16_f16_f16_km_kn_mn_instance.cpp;
device_gemm_xdl_splitk_c_shuffle_f16_f16_f16_km_nk_mn_instance.cpp;
)
add_library(device_gemm_splitk_instance SHARED ${DEVICE_GEMM_SPLITK_INSTANCE_SOURCE})
target_compile_features(device_gemm_splitk_instance PUBLIC)
set_target_properties(device_gemm_splitk_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
install(TARGETS device_gemm_splitk_instance LIBRARY DESTINATION lib)
clang_tidy_check(device_gemm_splitk_instance)
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