ROCm/composable_kernel
1
0
Fork 0
mirror of https://github.com/ROCm/composable_kernel.git synced 2026-05-11 17:00:18 +00:00
Code Issues Packages Projects Releases Wiki Activity

disabling some fp8 gemm instances to reduce build time (#1084)

Browse Source 
* disabling some fp8 gemm instances to reduce build time

* disable fp8 gemm instances to reduce build time

* remove the unused variable

* build fp8 gemm default and padded instances separately

* fix include pathsc
This commit is contained in:
Illia Silin
2023-12-11 17:49:27 -08:00
committed by GitHub
parent 89ee47460b
commit c004e0d990
5 changed files with 64 additions and 20 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_fp8_fp8_fp8_mk_kn_mn_instance.cpp → library/include/ck/library/tensor_operation_instance/gpu/device_gemm_xdl_c_shuffle_fp8_fp8_fp8_mk_kn_mn_instance.hpp
View File

@@ -25,10 +25,6 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
static constexpr auto MNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
template <ck::tensor_operation::device::GemmSpecialization GemmSpec>
using device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_instances = std::tuple<
@@ -37,7 +33,7 @@ using device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_instances = std::tuple<
//#####################| | | | Type| Type| Type| Type| DataType| Elementwise| Elementwise| Elementwise| Specialization| 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| | |
//#####################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
// pipeline v1, 1 wave
// pipeline v1, 1 wave
DeviceGemm_Xdl_CShuffle< Row, Row, Row, F8, F8, F8, F32, F8, PassThrough, PassThrough, PassThrough, GemmSpec, 1, 256, 256, 128, 64, 16, 4, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, 0, 1, 1, S<1, 64, 1, 4>, 16, LoopScheduler::Default, PipelineVersion::v1>,
DeviceGemm_Xdl_CShuffle< Row, Row, Row, F8, F8, F8, F32, F8, PassThrough, PassThrough, PassThrough, GemmSpec, 1, 256, 256, 128, 64, 16, 16, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 16, 1, 1, 1, S<1, 64, 1, 4>, 16, LoopScheduler::Default, PipelineVersion::v1>,
DeviceGemm_Xdl_CShuffle< Row, Row, Row, F8, F8, F8, F32, F8, PassThrough, PassThrough, PassThrough, GemmSpec, 1, 256, 128, 256, 64, 16, 4, 32, 32, 2, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, 0, 1, 1, S<1, 64, 1, 4>, 16, LoopScheduler::Default, PipelineVersion::v1>,
@@ -75,7 +71,8 @@ using device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_instances = std::tuple<
DeviceGemm_Xdl_CShuffle< Row, Row, Row, F8, F8, F8, F32, F8, PassThrough, PassThrough, PassThrough, GemmSpec, 1, 256, 64, 128, 64, 16, 16, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 16, 1, 1, 1, S<1, 64, 1, 4>, 16, LoopScheduler::Interwave, PipelineVersion::v1>
#endif
#if CK_EXPERIMENTAL_PIPELINE_V2_INSTANCES
#if 0
//CK_EXPERIMENTAL_PIPELINE_V2_INSTANCES
// pipeline v2, 1 wave
,
DeviceGemm_Xdl_CShuffle< Row, Row, Row, F8, F8, F8, F32, F8, PassThrough, PassThrough, PassThrough, GemmSpec, 1, 256, 256, 128, 64, 16, 4, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 16, 16, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, 0, 1, 1, S<1, 64, 1, 4>, 16, LoopScheduler::Default, PipelineVersion::v2>,
@@ -98,17 +95,6 @@ using device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_instances = std::tuple<
// clang-format on
>;
void add_device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_instances(
std::vector<std::unique_ptr<
DeviceGemm<Row, Row, Row, F8, F8, F8, PassThrough, PassThrough, PassThrough>>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_instances<GemmDefault>{});
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_instances<MNKPadding>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation

9
library/include/ck/library/tensor_operation_instance/gpu/gemm.hpp
View File

@@ -345,7 +345,11 @@ void add_device_gemm_xdl_c_shuffle_f8_f8_f8_km_nk_mn_instances(
std::vector<std::unique_ptr<
DeviceGemm<Col, Col, Row, F8, F8, F8, PassThrough, PassThrough, PassThrough>>>& instances);
void add_device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_instances(
void add_device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_default_instances(
std::vector<std::unique_ptr<
DeviceGemm<Row, Row, Row, F8, F8, F8, PassThrough, PassThrough, PassThrough>>>& instances);
void add_device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_padded_instances(
std::vector<std::unique_ptr<
DeviceGemm<Row, Row, Row, F8, F8, F8, PassThrough, PassThrough, PassThrough>>>& instances);
@@ -575,7 +579,8 @@ struct DeviceOperationInstanceFactory<
if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Row> &&
is_same_v<CLayout, Row>)
{
add_device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_instances(op_ptrs);
add_device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_padded_instances(op_ptrs);
add_device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_default_instances(op_ptrs);
}
else if constexpr(is_same_v<ALayout, Row> && is_same_v<BLayout, Col> &&
is_same_v<CLayout, Row>)

3
library/src/tensor_operation_instance/gpu/gemm/CMakeLists.txt
View File

@@ -101,7 +101,8 @@ list(APPEND GEMM_INSTANCES
device_gemm_xdl_c_shuffle_bf16_bf16_bf16_km_nk_mn_instance.cpp)
list(APPEND GEMM_INSTANCES
device_gemm_xdl_c_shuffle_fp8_fp8_fp8_mk_kn_mn_instance.cpp
device_gemm_xdl_c_shuffle_fp8_fp8_fp8_mk_kn_mn_default_instance.cpp
device_gemm_xdl_c_shuffle_fp8_fp8_fp8_mk_kn_mn_padded_instance.cpp
device_gemm_xdl_c_shuffle_fp8_fp8_fp8_mk_nk_mn_instance.cpp
device_gemm_xdl_c_shuffle_fp8_fp8_fp8_km_kn_mn_instance.cpp
device_gemm_xdl_c_shuffle_fp8_fp8_fp8_km_nk_mn_instance.cpp)

26
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_fp8_fp8_fp8_mk_kn_mn_default_instance.cpp Normal file
View File

@@ -0,0 +1,26 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/device_gemm_xdl_c_shuffle_fp8_fp8_fp8_mk_kn_mn_instance.hpp"
#ifdef CK_ENABLE_FP8
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
void add_device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_default_instances(
std::vector<std::unique_ptr<
DeviceGemm<Row, Row, Row, F8, F8, F8, PassThrough, PassThrough, PassThrough>>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_instances<GemmDefault>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
#endif

26
library/src/tensor_operation_instance/gpu/gemm/device_gemm_xdl_c_shuffle_fp8_fp8_fp8_mk_kn_mn_padded_instance.cpp Normal file
View File

@@ -0,0 +1,26 @@
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/device_gemm_xdl_c_shuffle_fp8_fp8_fp8_mk_kn_mn_instance.hpp"
#ifdef CK_ENABLE_FP8
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
static constexpr auto MNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
void add_device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_padded_instances(
std::vector<std::unique_ptr<
DeviceGemm<Row, Row, Row, F8, F8, F8, PassThrough, PassThrough, PassThrough>>>& instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_c_shuffle_f8_f8_f8_mk_kn_mn_instances<MNKPadding>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
#endif