ROCm/composable_kernel
1
0
Fork 0
mirror of https://github.com/ROCm/composable_kernel.git synced 2026-05-14 02:02:46 +00:00
Code Issues Packages Projects Releases Wiki Activity

Grouped Conv Bwd Weight Direct Load (#3648)

Browse Source 
* Grouped Conv Bwd Weight Direct Load

* Update gridwise_gemm_xdl_cshuffle_conv_v3.hpp

* Implement group merging for bwd_weight and add instances

* Link direct load instances

* builder fixes

* fix

* fixes

* fix

---------

Co-authored-by: Graner, Johannes <johannes.graner@amd.com>
This commit is contained in:
Bartłomiej Kocot
2026-01-28 22:31:54 +01:00
committed by GitHub
parent 654bec3362
commit 83b58bb0c3
18 changed files with 578 additions and 194 deletions
Download Patch File Download Diff File Expand all files Collapse all files

49
library/include/ck/library/tensor_operation_instance/gpu/grouped_conv_bwd_weight/device_grouped_conv_bwd_weight_v3_xdl_instance.hpp
View File

@@ -101,6 +101,55 @@ using device_grouped_conv_bwd_weight_v3_xdl_c_shuffle_f16_instances = std::tuple
// clang-format on
>;
template <ck::index_t NDimSpatial,
typename ALayout,
typename BLayout,
typename ELayout,
ConvolutionBackwardWeightSpecialization ConvSpec,
BlockGemmPipelineScheduler Scheduler,
BlockGemmPipelineVersion PipelineVersion>
using device_grouped_conv_bwd_weight_v3_xdl_c_shuffle_f16_direct_load_instances = std::tuple<
// clang-format off
//#########################################| Num| InLayout| WeiLayout| OutLayout| InData| WeiData| OutData| AccData| In| Wei| Out| ConvBackward| 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| CBlockTransfer| CBlockTransfer| BlockGemm| BlockGemm| Compute| Compute| Direct|
//#########################################| Dim| | | | Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Weight| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| ClusterLengths| ScalarPerVector| Pipeline| Pipeline| Data| Data| Load|
//#########################################| Spatial| | | | | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| MBlock_MPerBlock| NWaveNPerXdl| Scheduler| Version| Type| Type| |
//#########################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | NBlock_NPerBlock| | | | | | |
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 16, 32, 64, 8, 16, 16, 1, 1, S<8, 2, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<4, 4, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 16, 1, 8>, 4, Scheduler, PipelineVersion, F16, F16, true>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 16, 32, 64, 8, 16, 16, 1, 1, S<8, 2, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<4, 4, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 16, 1, 8>, 4, Scheduler, PipelineVersion, F16, F16, true, 2>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 16, 64, 64, 8, 16, 16, 1, 2, S<8, 2, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<2, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 16, 1, 8>, 4, Scheduler, PipelineVersion, F16, F16, true>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 16, 64, 64, 8, 16, 16, 1, 2, S<8, 2, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<2, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 16, 1, 8>, 4, Scheduler, PipelineVersion, F16, F16, true, 2>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 256, 32, 64, 8, 32, 32, 2, 1, S<4, 32, 2>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<8, 4, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 64, 1, 4>, 8, Scheduler, PipelineVersion, F16, F16, true>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 64, 128, 64, 8, 32, 32, 1, 2, S<4, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<4, 16, 4>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 32, 1, 8>, 8, Scheduler, PipelineVersion, F16, F16, true>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 64, 128, 64, 8, 32, 32, 1, 2, S<4, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<4, 16, 4>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 32, 1, 8>, 8, Scheduler, PipelineVersion, F16, F16, true, 2>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 64, 64, 64, 8, 16, 16, 2, 2, S<4, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<4, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, 8, Scheduler, PipelineVersion, F16, F16, true>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 64, 64, 64, 8, 16, 16, 2, 2, S<4, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<4, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, 2, Scheduler, PipelineVersion, F16, F16, true>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 64, 64, 64, 8, 16, 16, 2, 2, S<4, 32, 2>, S<0, 2, 1>,S<0, 2, 1>, 1, 2, 1, 0, S<4, 32, 2>, S<0, 2, 1>,S<0, 2, 1>, 1, 2, 1, 0, 1, 1, S<1, 32, 1, 4>, 4, Scheduler, PipelineVersion, F16, F16, true>
// clang-format on
>;
template <ck::index_t NDimSpatial,
typename ALayout,
typename BLayout,
typename ELayout,
ConvolutionBackwardWeightSpecialization ConvSpec,
BlockGemmPipelineScheduler Scheduler,
BlockGemmPipelineVersion PipelineVersion>
using device_grouped_conv_bwd_weight_v3_xdl_c_shuffle_bf16_direct_load_instances = std::tuple<
// clang-format off
//#########################################| Num| InLayout| WeiLayout| OutLayout| InData| WeiData| OutData| AccData| In| Wei| Out| ConvBackward| 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| CBlockTransfer| CBlockTransfer| BlockGemm| BlockGemm| Compute| Compute| Direct|
//#########################################| Dim| | | | Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Weight| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| ClusterLengths| ScalarPerVector| Pipeline| Pipeline| Data| Data| Load|
//#########################################| Spatial| | | | | | | | Operation| Operation| Operation| Specialization| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| MBlock_MPerBlock| NWaveNPerXdl| Scheduler| Version| Type| Type| |
//#########################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | NBlock_NPerBlock| | | | | | |
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 16, 32, 64, 8, 16, 16, 1, 1, S<8, 2, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<4, 4, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 16, 1, 8>, 4, Scheduler, PipelineVersion, BF16, BF16, true>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 16, 64, 64, 8, 16, 16, 1, 2, S<8, 2, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<2, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 16, 1, 8>, 4, Scheduler, PipelineVersion, BF16, BF16, true>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 256, 32, 64, 8, 32, 32, 2, 1, S<4, 32, 2>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<8, 4, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 64, 1, 4>, 8, Scheduler, PipelineVersion, BF16, BF16, true>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 64, 128, 64, 8, 32, 32, 1, 2, S<4, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<4, 16, 4>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 32, 1, 8>, 8, Scheduler, PipelineVersion, BF16, BF16, true>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 64, 64, 64, 8, 16, 16, 2, 2, S<4, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<4, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, 8, Scheduler, PipelineVersion, BF16, BF16, true>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 64, 64, 64, 8, 16, 16, 2, 2, S<4, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, S<4, 8, 8>, S<0, 2, 1>,S<0, 2, 1>, 1, 8, 8, 0, 1, 1, S<1, 32, 1, 4>, 2, Scheduler, PipelineVersion, BF16, BF16, true>,
DeviceGroupedConvBwdWeight_Xdl_CShuffleV3< NDimSpatial, ALayout, BLayout, ELayout, BF16, BF16, BF16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 64, 64, 64, 8, 16, 16, 2, 2, S<4, 32, 2>, S<0, 2, 1>,S<0, 2, 1>, 1, 2, 1, 0, S<4, 32, 2>, S<0, 2, 1>,S<0, 2, 1>, 1, 2, 1, 0, 1, 1, S<1, 32, 1, 4>, 4, Scheduler, PipelineVersion, BF16, BF16, true>
// clang-format on
>;
template <ck::index_t NDimSpatial,
typename ALayout,
typename BLayout,

6
library/include/ck/library/tensor_operation_instance/gpu/grouped_convolution_backward_weight.hpp
View File

@@ -393,6 +393,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_f16_instances(
op_ptrs);
add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_f16_direct_load_instances(
op_ptrs);
add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_f16_default_pipev2_instances(
op_ptrs);
add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_f16_default_pipev5_instances(
@@ -453,6 +456,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_bf16_instances(
op_ptrs);
add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_bf16_direct_load_instances(
op_ptrs);
add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_bf16_default_pipev2_instances(
op_ptrs);
add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_bf16_default_pipev5_instances(

24
library/include/ck/library/tensor_operation_instance/gpu/grouped_convolution_backward_weight_xdl.inc
View File

@@ -184,6 +184,18 @@ void add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_bf16_default_pip
PassThrough,
PassThrough>>>& instances);
void add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_bf16_direct_load_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<2,
NHWGC,
GKYXC,
NHWGK,
BF16,
BF16,
BF16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_bf16_default_pipev5_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<2,
NHWGC,
@@ -389,6 +401,18 @@ void add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_f16_default_pipe
PassThrough,
PassThrough>>>& instances);
void add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_f16_direct_load_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<2,
NHWGC,
GKYXC,
NHWGK,
F16,
F16,
F16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_f16_default_pipev5_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<2,
NHWGC,