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Commit 28d60825 authored by Chao Liu's avatar Chao Liu
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Merge remote-tracking branch 'origin/develop' into standalone-layernorm

parents c6891e12 9e4429f9
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Showing with 295 additions and 851 deletions
include/ck/tensor_operation/gpu/device/gemm_specialization.hpp
View file @ 28d60825
......@@ -19,6 +19,22 @@ enum struct GemmSpecialization
MNKPadding,
};
inline std::string getGemmSpecializationString(const GemmSpecialization& s)
{
switch(s)
{
case GemmSpecialization::Default: return "Default";
case GemmSpecialization::MPadding: return "MPadding";
case GemmSpecialization::NPadding: return "NPadding";
case GemmSpecialization::KPadding: return "KPadding";
case GemmSpecialization::MNPadding: return "MNPadding";
case GemmSpecialization::MKPadding: return "MKPadding";
case GemmSpecialization::NKPadding: return "NKPadding";
case GemmSpecialization::MNKPadding: return "MNKPadding";
default: return "Unrecognized specialization!";
}
}
} // namespace device
} // namespace tensor_operation
} // namespace ck
include/ck/tensor_operation/gpu/element/binary_element_wise_operation.hpp
View file @ 28d60825
......@@ -35,7 +35,6 @@ struct Add
y = type_convert<half_t>(x0) + x1;
};
// Question: should half_t be supported ?
template <>
__host__ __device__ constexpr void
operator()<half_t>(half_t& y, const half_t& x0, const half_t& x1) const
......@@ -43,7 +42,6 @@ struct Add
y = x0 + x1;
};
// Question: should bhalf_t be supported ?
template <>
__host__ __device__ constexpr void
operator()<bhalf_t>(bhalf_t& y, const bhalf_t& x0, const bhalf_t& x1) const
......@@ -74,7 +72,6 @@ struct Subtract
y = x0 - x1;
};
// Question: should half_t be supported ?
template <>
__host__ __device__ constexpr void
operator()<half_t>(half_t& y, const half_t& x0, const half_t& x1) const
......@@ -82,7 +79,6 @@ struct Subtract
y = x0 - x1;
};
// Question: should bhalf_t be supported ?
template <>
__host__ __device__ constexpr void
operator()<bhalf_t>(bhalf_t& y, const bhalf_t& x0, const bhalf_t& x1) const
......@@ -94,33 +90,25 @@ struct Subtract
}
};
struct AlphaBetaAdd
struct Bilinear
{
AlphaBetaAdd(float alpha, float beta) : alpha_(alpha), beta_(beta){};
Bilinear(float alpha, float beta) : alpha_(alpha), beta_(beta){};
template <typename T>
__host__ __device__ constexpr void operator()(T& y, const T& x0, const T& x1) const;
template <typename Y, typename X0, typename X1>
__host__ __device__ constexpr void operator()(Y&, const X0&, const X1&) const;
template <>
__host__ __device__ constexpr void
operator()<float>(float& y, const float& x0, const float& x1) const
operator()<float, float, float>(float& y, const float& x0, const float& x1) const
{
y = alpha_ * x0 + beta_ * x1;
};
template <>
__host__ __device__ constexpr void
operator()<double>(double& y, const double& x0, const double& x1) const
{
y = static_cast<double>(alpha_) * x0 + static_cast<double>(beta_) * x1;
};
// Question: should half_t be supported ?
template <>
__host__ __device__ constexpr void
operator()<half_t>(half_t& y, const half_t& x0, const half_t& x1) const
operator()<half_t, float, half_t>(half_t& y, const float& x0, const half_t& x1) const
{
y = static_cast<half_t>(alpha_ * static_cast<float>(x0) + beta_ * static_cast<float>(x1));
y = type_convert<half_t>(alpha_ * x0 + beta_ * ck::type_convert<float>(x1));
};
float alpha_;
......@@ -148,13 +136,12 @@ struct AddRelu
y = a > 0.0 ? a : 0.0;
};
// Question: should half_t be supported ?
template <>
__host__ __device__ constexpr void
operator()<half_t>(half_t& y, const half_t& x0, const half_t& x1) const
{
const half_t a = x0 + x1;
y = a > static_cast<half_t>(0.0f) ? a : static_cast<half_t>(0.0f);
y = a > type_convert<half_t>(0.0f) ? a : type_convert<half_t>(0.0f);
};
};
......@@ -183,7 +170,6 @@ struct AddHardswish
y = c;
};
// Question: should half_t be supported ?
template <>
__host__ __device__ constexpr void
operator()<half_t>(half_t& y, const half_t& x0, const half_t& x1) const
......
include/ck/tensor_operation/gpu/element/element_wise_operation.hpp
View file @ 28d60825
......@@ -159,7 +159,7 @@ struct Normalize
using ck::math::sqrt;
float variance = mean_square - (mean * mean);
y = ((x - mean) / sqrt(variance + static_cast<float>(epsilon_))) * gamma + beta;
y = ((x - mean) / sqrt(variance + type_convert<float>(epsilon_))) * gamma + beta;
};
template <>
......
include/ck/utility/data_type.hpp
View file @ 28d60825
......@@ -932,14 +932,14 @@ using int8x64_t = typename vector_type<int8_t, 64>::type;
// Convert X to Y
template <typename Y, typename X>
__host__ __device__ Y type_convert(X x)
__host__ __device__ constexpr Y type_convert(X x)
{
return static_cast<Y>(x);
}
// convert bfp16 to fp32
template <>
inline __host__ __device__ float type_convert<float, bhalf_t>(bhalf_t x)
inline __host__ __device__ constexpr float type_convert<float, bhalf_t>(bhalf_t x)
{
union
{
......@@ -952,7 +952,7 @@ inline __host__ __device__ float type_convert<float, bhalf_t>(bhalf_t x)
// convert fp32 to bfp16
template <>
inline __host__ __device__ bhalf_t type_convert<bhalf_t, float>(float x)
inline __host__ __device__ constexpr bhalf_t type_convert<bhalf_t, float>(float x)
{
union
{
......
library/include/ck/library/tensor_operation_instance/device_operation_instance_factory.hpp
View file @ 28d60825
......@@ -16,12 +16,14 @@ using F32 = float;
using F16 = ck::half_t;
using BF16 = ck::bhalf_t;
using F16_F16 = ck::Tuple<F16, F16>;
using F16_TUPLE = ck::Tuple<F16>;
using F16_F16_TUPLE = ck::Tuple<F16, F16>;
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
using Bilinear = ck::tensor_operation::element_wise::Bilinear;
using AddAddFastGelu = ck::tensor_operation::element_wise::AddAddFastGelu;
template <typename DeviceOp>
......
library/include/ck/library/tensor_operation_instance/gpu/gemm_add_add_fastgelu.hpp
View file @ 28d60825
......@@ -25,7 +25,7 @@ void add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instanc
Row,
F16,
F16,
F16_F16,
F16_F16_TUPLE,
F16,
PassThrough,
PassThrough,
......@@ -37,7 +37,7 @@ void add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instanc
Row,
F16,
F16,
F16_F16,
F16_F16_TUPLE,
F16,
PassThrough,
PassThrough,
......@@ -49,7 +49,7 @@ void add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instanc
Row,
F16,
F16,
F16_F16,
F16_F16_TUPLE,
F16,
PassThrough,
PassThrough,
......@@ -61,7 +61,7 @@ void add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instanc
Row,
F16,
F16,
F16_F16,
F16_F16_TUPLE,
F16,
PassThrough,
PassThrough,
......@@ -73,7 +73,8 @@ template <typename ALayout,
typename DELayout,
typename ADataType,
typename BDataType,
typename DsDataType,
typename D0DataType,
typename D1DataType,
typename EDataType>
struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMultipleD<
ALayout,
......@@ -81,7 +82,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
DELayout,
ADataType,
BDataType,
DsDataType,
ck::Tuple<D0DataType, D1DataType>,
EDataType,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
......@@ -92,7 +93,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
DELayout,
ADataType,
BDataType,
DsDataType,
ck::Tuple<D0DataType, D1DataType>,
EDataType,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
......@@ -103,7 +104,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMu
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
is_same_v<DsDataType, Tuple<half_t, half_t>> && is_same_v<EDataType, half_t>)
is_same_v<D0DataType, half_t> && is_same_v<D1DataType, half_t> &&
is_same_v<EDataType, half_t>)
{
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
is_same_v<DELayout, Row>)
......
library/include/ck/library/tensor_operation_instance/gpu/gemm_bilinear.hpp 0 → 100644
View file @ 28d60825
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <cstdlib>
#include <vector>
#include <memory>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_gemm_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance_factory.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
void add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instances(
std::vector<std::unique_ptr<DeviceGemmMultipleD<Col,
Row,
Row,
F16,
F16,
F16_TUPLE,
F16,
PassThrough,
PassThrough,
Bilinear>>>& instances);
void add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instances(
std::vector<std::unique_ptr<DeviceGemmMultipleD<Col,
Col,
Row,
F16,
F16,
F16_TUPLE,
F16,
PassThrough,
PassThrough,
Bilinear>>>& instances);
void add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instances(
std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
Row,
Row,
F16,
F16,
F16_TUPLE,
F16,
PassThrough,
PassThrough,
Bilinear>>>& instances);
void add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instances(
std::vector<std::unique_ptr<DeviceGemmMultipleD<Row,
Col,
Row,
F16,
F16,
F16_TUPLE,
F16,
PassThrough,
PassThrough,
Bilinear>>>& instances);
// GEMM + Bilinear
template <typename ALayout,
typename BLayout,
typename DELayout,
typename ADataType,
typename BDataType,
typename DDataType,
typename EDataType>
struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGemmMultipleD<
ALayout,
BLayout,
DELayout,
ADataType,
BDataType,
ck::Tuple<DDataType>,
EDataType,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::Bilinear>>
{
using DeviceOp = DeviceGemmMultipleD<ALayout,
BLayout,
DELayout,
ADataType,
BDataType,
ck::Tuple<DDataType>,
EDataType,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::Bilinear>;
static auto GetInstances()
{
std::vector<std::unique_ptr<DeviceOp>> op_ptrs;
if constexpr(is_same_v<ADataType, half_t> && is_same_v<BDataType, half_t> &&
is_same_v<DDataType, half_t> && is_same_v<EDataType, half_t>)
{
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
is_same_v<DELayout, Row>)
{
add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instances(op_ptrs);
}
else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
is_same_v<DELayout, Row>)
{
add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instances(op_ptrs);
}
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Row> &&
is_same_v<DELayout, Row>)
{
add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instances(op_ptrs);
}
else if constexpr(is_same_v<ALayout, Col> && is_same_v<BLayout, Col> &&
is_same_v<DELayout, Row>)
{
add_device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instances(op_ptrs);
}
}
return op_ptrs;
}
};
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/CMakeLists.txt
View file @ 28d60825
......@@ -5,15 +5,12 @@ function(add_instance_library INSTANCE_NAME)
set_target_properties(${INSTANCE_NAME} PROPERTIES POSITION_INDEPENDENT_CODE ON)
endfunction(add_instance_library INSTANCE_NAME)
add_subdirectory(elementwise)
add_subdirectory(gemm)
add_subdirectory(gemm_splitk)
add_subdirectory(gemm_bias2d)
add_subdirectory(gemm_bias_relu)
add_subdirectory(gemm_bias_relu_add)
add_subdirectory(gemm_bilinear)
add_subdirectory(gemm_add_add_fastgelu)
add_subdirectory(gemm_reduce)
add_subdirectory(gemm_bias_add_reduce)
add_subdirectory(gemm_add_add_fastgelu)
add_subdirectory(batched_gemm)
add_subdirectory(batched_gemm_reduce)
add_subdirectory(grouped_gemm)
......@@ -25,17 +22,16 @@ add_subdirectory(conv2d_fwd_bias_relu_add)
add_subdirectory(conv2d_bwd_data)
add_subdirectory(convnd_bwd_data)
add_subdirectory(conv2d_bwd_weight)
add_subdirectory(normalization)
add_subdirectory(reduce)
add_subdirectory(normalization)
add_subdirectory(elementwise)
add_library(device_operations STATIC
$<TARGET_OBJECTS:device_gemm_instance>
$<TARGET_OBJECTS:device_gemm_splitk_instance>
$<TARGET_OBJECTS:device_gemm_bias_relu_instance>
$<TARGET_OBJECTS:device_gemm_bias_relu_add_instance>
$<TARGET_OBJECTS:device_gemm_bias_add_reduce_instance>
$<TARGET_OBJECTS:device_gemm_bias2d_instance>
$<TARGET_OBJECTS:device_gemm_bilinear_instance>
$<TARGET_OBJECTS:device_gemm_add_add_fastgelu_instance>
$<TARGET_OBJECTS:device_gemm_bias_add_reduce_instance>
$<TARGET_OBJECTS:device_batched_gemm_instance>
$<TARGET_OBJECTS:device_batched_gemm_reduce_instance>
$<TARGET_OBJECTS:device_grouped_gemm_instance>
......@@ -47,9 +43,9 @@ add_library(device_operations STATIC
$<TARGET_OBJECTS:device_conv2d_bwd_data_instance>
$<TARGET_OBJECTS:device_convnd_bwd_data_instance>
$<TARGET_OBJECTS:device_conv2d_bwd_weight_instance>
$<TARGET_OBJECTS:device_elementwise_instance>
$<TARGET_OBJECTS:device_gemm_add_add_fastgelu_instance>
$<TARGET_OBJECTS:device_reduce_instance>
$<TARGET_OBJECTS:device_normalization_instance>
$<TARGET_OBJECTS:device_elementwise_instance>
)
add_library(composablekernels::device_operations ALIAS device_operations)
......@@ -81,7 +77,6 @@ target_include_directories(device_operations PUBLIC
#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
--offload-arch=gfx90a
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instance.cpp
View file @ 28d60825
......@@ -7,6 +7,8 @@
#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_gemm_xdl_cshuffle.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instance.cpp
View file @ 28d60825
......@@ -7,6 +7,8 @@
#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_gemm_xdl_cshuffle.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instance.cpp
View file @ 28d60825
......@@ -7,6 +7,8 @@
#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_gemm_xdl_cshuffle.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
......
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instance.cpp
View file @ 28d60825
......@@ -7,6 +7,8 @@
#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_gemm_xdl_cshuffle.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
......
library/src/tensor_operation_instance/gpu/gemm_add_add_fastgelu/device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instance.cpp
View file @ 28d60825
......@@ -4,6 +4,8 @@
#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_gemm_multiple_d_xdl_cshuffle.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
......@@ -14,9 +16,9 @@ namespace tensor_operation {
namespace device {
namespace instance {
using F16 = ck::half_t;
using F32 = float;
using F16_F16 = ck::Tuple<F16, F16>;
using F16 = ck::half_t;
using F32 = float;
using F16_F16_Tuple = ck::Tuple<F16, F16>;
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
......@@ -34,23 +36,23 @@ static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecializa
// input: a[m, k], b[n, k], d0[m, n], d1[m ,n]
using device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instances = std::tuple<
// clang-format off
//##############################| ALayout| BLayout| CLayout| AData| BData| AccData| CShuffle| DsData| EData| A| B| CDE| 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|
//##############################| | | | Type| Type| Type| DataType| Type| Type| Elementwise| Elementwise| Elementwise| Spacialization| Prefetch| 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_MWaveMPerXdl| ScalarPerVector|
//##############################| | | | | | | | | | Operation| Operation| Operation| | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
//##############################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 256, 256, 128, 32, 8, 8, 32, 32, 4, 2, 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, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 256, 128, 256, 32, 8, 8, 32, 32, 2, 4, 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, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 128, 128, 128, 32, 8, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 256, 128, 128, 32, 8, 8, 32, 32, 2, 2, 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, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 128, 128, 64, 32, 8, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 128, 64, 128, 32, 8, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 64, 64, 64, 32, 8, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 256, 128, 64, 32, 8, 8, 32, 32, 2, 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, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 256, 64, 128, 32, 8, 8, 32, 32, 1, 2, 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, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 128, 128, 32, 32, 8, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 128, 32, 128, 32, 8, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 64, 64, 32, 32, 8, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 64, 32, 64, 32, 8, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>
//##############################| ALayout| BLayout| CLayout| AData| BData| AccData| CShuffle| DsData| EData| A| B| CDE| 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|
//##############################| | | | Type| Type| Type| DataType| Type| Type| Elementwise| Elementwise| Elementwise| Spacialization| Prefetch| 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_MWaveMPerXdl| ScalarPerVector|
//##############################| | | | | | | | | | Operation| Operation| Operation| | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
//##############################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 256, 256, 128, 32, 8, 8, 32, 32, 4, 2, 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, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 256, 128, 256, 32, 8, 8, 32, 32, 2, 4, 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, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 128, 128, 128, 32, 8, 8, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 256, 128, 128, 32, 8, 8, 32, 32, 2, 2, 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, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 128, 128, 64, 32, 8, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 128, 64, 128, 32, 8, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 64, 64, 64, 32, 8, 8, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 256, 128, 64, 32, 8, 8, 32, 32, 2, 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, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 256, 64, 128, 32, 8, 8, 32, 32, 1, 2, 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, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 128, 128, 32, 32, 8, 8, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 128, 32, 128, 32, 8, 8, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 64, 64, 32, 32, 8, 8, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
DeviceGemmMultipleD_Xdl_CShuffle< Row, Col, Row, F16, F16, F32, F32, F16_F16_Tuple, F16, PassThrough, PassThrough, AddAddFastGelu, GemmDefault, 1, 64, 32, 64, 32, 8, 8, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>
// clang-format on
>;
......@@ -60,7 +62,7 @@ void add_device_gemm_add_add_fastgelu_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instanc
Row,
F16,
F16,
F16_F16,
F16_F16_Tuple,
F16,
PassThrough,
PassThrough,
......
library/src/tensor_operation_instance/gpu/gemm_bias2d/CMakeLists.txt deleted 100644 → 0
View file @ c6891e12
# device_gemm_bias2d_instance
set(DEVICE_GEMM_BIAS2D_INSTANCE_SOURCE
device_gemm_xdl_c_shuffle_bias_2d_f32_f32_f32_km_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_2d_f32_f32_f32_km_nk_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_2d_f32_f32_f32_mk_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_2d_f32_f32_f32_mk_nk_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_km_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_km_nk_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_mk_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_mk_nk_mn_instance.cpp;
)
add_library(device_gemm_bias2d_instance OBJECT ${DEVICE_GEMM_BIAS2D_INSTANCE_SOURCE})
set_target_properties(device_gemm_bias2d_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
clang_tidy_check(device_gemm_bias2d_instance)
library/src/tensor_operation_instance/gpu/gemm_bias2d/device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_km_kn_mn_instance.cpp deleted 100644 → 0
View file @ c6891e12
// 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_gemm_xdl_c_shuffle_bias_2d.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using F16 = ck::half_t;
using F32 = float;
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 PassThrough = ck::tensor_operation::element_wise::PassThrough;
using AlphaBetaAdd = ck::tensor_operation::element_wise::AlphaBetaAdd;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_km_kn_mn_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| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
//#############################| 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| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector|
//#############################| | | | | | | | Operation| Operation| Operation| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NXdlPerWave_NWaveNPerXdl| _NWaveNPerXdl|
//#############################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, 1, 1, S<1, 1, 32, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, true, 1, 1, S<1, 1, 16, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 8>
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_km_kn_mn_instances(
std::vector<DeviceGemmBiasPtr<PassThrough, PassThrough, AlphaBetaAdd>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_km_kn_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_bias2d/device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_km_nk_mn_instance.cpp deleted 100644 → 0
View file @ c6891e12
// 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_gemm_xdl_c_shuffle_bias_2d.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using F16 = ck::half_t;
using F32 = float;
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 PassThrough = ck::tensor_operation::element_wise::PassThrough;
using AlphaBetaAdd = ck::tensor_operation::element_wise::AlphaBetaAdd;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_km_nk_mn_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| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
//#############################| 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| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector|
//#############################| | | | | | | | Operation| Operation| Operation| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NXdlPerWave_NWaveNPerXdl| _NWaveNPerXdl|
//#############################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 32, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 16, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 8>
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_km_nk_mn_instances(
std::vector<DeviceGemmBiasPtr<PassThrough, PassThrough, AlphaBetaAdd>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_km_nk_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
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