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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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library/src/tensor_operation_instance/gpu/gemm_bias2d/device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_mk_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_mk_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, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 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<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, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 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<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, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 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<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, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 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<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, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 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<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, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 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<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, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 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<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, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 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<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_mk_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_mk_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_mk_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_mk_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, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 32, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 16, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 32, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 16, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 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, 16, 1, 1, 4>, 8>
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_bias_2d_f16_f16_f16_mk_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_mk_nk_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_f32_f32_f32_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 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_f32_f32_f32_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< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 256, 128, 4, 4, 32, 32, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 256, 4, 4, 32, 32, 2, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 128, 4, 4, 32, 32, 4, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, true, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 128, 4, 4, 32, 32, 2, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 64, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, true, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, 1, 1, S<1, 1, 32, 1, 1, 4>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 64, 128, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 64, 4, 4, 32, 32, 2, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 4, true, 1, 1, S<1, 1, 16, 1, 1, 4>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 64, 128, 4, 4, 32, 32, 1, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 4, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_bias_2d_f32_f32_f32_km_kn_mn_instances(
std::vector<DeviceGemmBiasPtr<PassThrough, PassThrough, AlphaBetaAdd>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_2d_f32_f32_f32_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_f32_f32_f32_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 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_f32_f32_f32_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< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 256, 128, 4, 4, 32, 32, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 256, 4, 4, 32, 32, 2, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 128, 4, 4, 32, 32, 4, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 128, 4, 4, 32, 32, 2, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 64, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 4>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 64, 128, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 64, 4, 4, 32, 32, 2, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 4>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 64, 128, 4, 4, 32, 32, 1, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 4, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_bias_2d_f32_f32_f32_km_nk_mn_instances(
std::vector<DeviceGemmBiasPtr<PassThrough, PassThrough, AlphaBetaAdd>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_2d_f32_f32_f32_km_nk_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_f32_f32_f32_mk_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 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_f32_f32_f32_mk_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< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 256, 128, 4, 4, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 256, 4, 4, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 128, 4, 4, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 128, 4, 4, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 64, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, 1, 1, S<1, 1, 32, 1, 1, 4>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 64, 128, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 64, 4, 4, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 4, true, 1, 1, S<1, 1, 16, 1, 1, 4>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 64, 128, 4, 4, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_bias_2d_f32_f32_f32_mk_kn_mn_instances(
std::vector<DeviceGemmBiasPtr<PassThrough, PassThrough, AlphaBetaAdd>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_2d_f32_f32_f32_mk_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_f32_f32_f32_mk_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 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_f32_f32_f32_mk_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< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 256, 4, 4, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 128, 4, 4, 32, 32, 4, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 256, 128, 4, 4, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 128, 4, 4, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 64, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 4>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 64, 128, 4, 4, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 64, 64, 64, 4, 4, 32, 32, 2, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 4>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 128, 64, 4, 4, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 256, 64, 128, 4, 4, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 128, 32, 4, 4, 32, 32, 2, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 32, 1, 1, 4>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 128, 32, 128, 4, 4, 32, 32, 1, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 8>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 64, 64, 32, 4, 4, 32, 32, 2, 1, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 4>, 4>,
DeviceGemmXdl_C_Shuffle_Bias_2d< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, AlphaBetaAdd, 64, 32, 64, 4, 4, 32, 32, 1, 2, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, S<4, 16, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 4, 4, true, 1, 1, S<1, 1, 16, 1, 1, 4>, 4>
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_bias_2d_f32_f32_f32_mk_nk_mn_instances(
std::vector<DeviceGemmBiasPtr<PassThrough, PassThrough, AlphaBetaAdd>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_2d_f32_f32_f32_mk_nk_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_bias_relu/CMakeLists.txt deleted 100644 → 0
View file @ c6891e12
# device_gemm_bias_relu_instance
set(DEVICE_GEMM_BIAS_RELU_INSTANCE_SOURCE
device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_mk_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_mk_nk_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_km_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_km_nk_mn_instance.cpp;
)
add_library(device_gemm_bias_relu_instance OBJECT ${DEVICE_GEMM_BIAS_RELU_INSTANCE_SOURCE})
set_target_properties(device_gemm_bias_relu_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
clang_tidy_check(device_gemm_bias_relu_instance)
library/src/tensor_operation_instance/gpu/gemm_bias_relu/device_gemm_xdl_c_shuffle_bias_relu_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_activation.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 AddRelu = ck::tensor_operation::element_wise::AddRelu;
// c[m, n] = ReLU(a[k, m] * b[k, n] + c0[n])
using device_gemm_xdl_c_shuffle_bias_relu_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_Activation< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddRelu, 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_relu_f16_f16_f16_km_kn_mn_instances(
std::vector<DeviceGemmBiasActivationPtr<PassThrough, PassThrough, AddRelu>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_km_kn_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_bias_relu/device_gemm_xdl_c_shuffle_bias_relu_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_activation.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 AddRelu = ck::tensor_operation::element_wise::AddRelu;
// c[m, n] = ReLU(a[k, m] * b[n, k] + c0[n])
using device_gemm_xdl_c_shuffle_bias_relu_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_Activation< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AddRelu, 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_Activation< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, AddRelu, 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_relu_f16_f16_f16_km_nk_mn_instances(
std::vector<DeviceGemmBiasActivationPtr<PassThrough, PassThrough, AddRelu>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_km_nk_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_bias_relu/device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_mk_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_activation.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 AddRelu = ck::tensor_operation::element_wise::AddRelu;
// c[m, n] = ReLU(a[m, k] * b[k, n] + c0[n])
using device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_mk_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_Activation< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, AddRelu, 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<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_Activation< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, AddRelu, 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<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_Activation< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, AddRelu, 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<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_Activation< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, AddRelu, 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<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_Activation< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, AddRelu, 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<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_Activation< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, AddRelu, 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<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_Activation< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, AddRelu, 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<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_Activation< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, AddRelu, 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<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_relu_f16_f16_f16_mk_kn_mn_instances(
std::vector<DeviceGemmBiasActivationPtr<PassThrough, PassThrough, AddRelu>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_mk_kn_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_bias_relu/device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_mk_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_activation.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 AddRelu = ck::tensor_operation::element_wise::AddRelu;
// c[m, n] = ReLU(a[m, k] * b[n, k] + c0[n])
using device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_mk_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_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 32, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 16, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 32, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 16, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddRelu, 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, 16, 1, 1, 4>, 8>
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_mk_nk_mn_instances(
std::vector<DeviceGemmBiasActivationPtr<PassThrough, PassThrough, AddRelu>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_relu_f16_f16_f16_mk_nk_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_bias_relu_add/CMakeLists.txt deleted 100644 → 0
View file @ c6891e12
# device_gemm_bias_relu_add_instance
set(DEVICE_GEMM_BIAS_RELU_ADD_INSTANCE_SOURCE
device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_mk_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_mk_nk_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_km_kn_mn_instance.cpp;
device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_km_nk_mn_instance.cpp;
)
add_library(device_gemm_bias_relu_add_instance OBJECT ${DEVICE_GEMM_BIAS_RELU_ADD_INSTANCE_SOURCE})
set_target_properties(device_gemm_bias_relu_add_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
clang_tidy_check(device_gemm_bias_relu_add_instance)
library/src/tensor_operation_instance/gpu/gemm_bias_relu_add/device_gemm_xdl_c_shuffle_bias_relu_add_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/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_gemm_xdl_c_shuffle_bias_activation_add.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.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 AddReluAdd = ck::tensor_operation::element_wise::AddReluAdd;
// c[m, n] = ReLU(a[k, m] * b[k, n] + c0[n]) + c1[m, n]
using device_gemm_xdl_c_shuffle_bias_relu_add_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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_relu_add_f16_f16_f16_km_kn_mn_instances(
std::vector<DeviceGemmBiasActivationAddPtr<PassThrough, PassThrough, AddReluAdd>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_km_kn_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_bias_relu_add/device_gemm_xdl_c_shuffle_bias_relu_add_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/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_gemm_xdl_c_shuffle_bias_activation_add.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.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 AddReluAdd = ck::tensor_operation::element_wise::AddReluAdd;
// c[m, n] = ReLU(a[k, m] * b[n, k] + c0[n]) + c1[m, n]
using device_gemm_xdl_c_shuffle_bias_relu_add_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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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_relu_add_f16_f16_f16_km_nk_mn_instances(
std::vector<DeviceGemmBiasActivationAddPtr<PassThrough, PassThrough, AddReluAdd>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_km_nk_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_bias_relu_add/device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_mk_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/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_gemm_xdl_c_shuffle_bias_activation_add.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.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 AddReluAdd = ck::tensor_operation::element_wise::AddReluAdd;
// c[m, n] = ReLU(a[m, k] * b[k, n] + c0[n]) + c1[m, n]
using device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_mk_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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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<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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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<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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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<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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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<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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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<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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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<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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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<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_Activation_Add< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, AddReluAdd, 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<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_relu_add_f16_f16_f16_mk_kn_mn_instances(
std::vector<DeviceGemmBiasActivationAddPtr<PassThrough, PassThrough, AddReluAdd>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_mk_kn_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_bias_relu_add/device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_mk_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/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_gemm_xdl_c_shuffle_bias_activation_add.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.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 AddReluAdd = ck::tensor_operation::element_wise::AddReluAdd;
// c[m, n] = ReLU(a[m, k] * b[n, k] + c0[n]) + c1[m, n]
using device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_mk_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_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 32, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 16, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 32, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 32, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 16, 1, 1, 8>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 16, 1, 1, 4>, 8>,
DeviceGemmXdl_C_Shuffle_Bias_Activation_Add< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, AddReluAdd, 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, 16, 1, 1, 4>, 8>
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_mk_nk_mn_instances(
std::vector<DeviceGemmBiasActivationAddPtr<PassThrough, PassThrough, AddReluAdd>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_bias_relu_add_f16_f16_f16_mk_nk_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_bilinear/CMakeLists.txt 0 → 100644
View file @ 28d60825
# device_gemm_bilinear_instance
set(DEVICE_GEMM_BILINEAR_INSTANCE_SOURCE
device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_km_kn_mn_instance.cpp;
device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_km_nk_mn_instance.cpp;
device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_mk_kn_mn_instance.cpp;
device_gemm_bilinear_xdl_c_shuffle_f16_f16_f16_mk_nk_mn_instance.cpp;
)
add_library(device_gemm_bilinear_instance OBJECT ${DEVICE_GEMM_BILINEAR_INSTANCE_SOURCE})
set_target_properties(device_gemm_bilinear_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
clang_tidy_check(device_gemm_bilinear_instance)
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