Skip to content

GitLab

Commit f0298581 authored by Harisankar Sadasivan's avatar Harisankar Sadasivan
Browse files

cmakelist changes to exclude navi cards for gemv splitk & merge changes from dev

parent 675aa69e
Hide whitespace changes
Inline Side-by-side
Showing with 674 additions and 143 deletions
library/include/ck/library/tensor_operation_instance/gpu/grouped_conv_bwd_weight/device_grouped_conv_bwd_weight_wmma_instance.hpp 0 → 100755
View file @ f0298581
// SPDX-License-Identifier: MIT
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_bwd_weight_wmma_cshuffle.hpp"
#include "ck/tensor_operation/gpu/device/convolution_backward_weight_specialization.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using F16 = ck::half_t;
using F32 = float;
using I8 = int8_t;
using I32 = int32_t;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using namespace ck::tensor_layout::convolution;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
static constexpr auto ConvBwdWeightDefault =
ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Default;
static constexpr auto ConvBwdWeightFilter1x1Stride1Pad0 =
ck::tensor_operation::device::ConvolutionBackwardWeightSpecialization::Filter1x1Stride1Pad0;
template <index_t NDSpatial,
typename ALayout,
typename BLayout,
typename CLayout,
ConvolutionBackwardWeightSpecialization ConvSpec>
using device_grouped_conv_bwd_weight_wmma_f16_instances =
std::tuple<
// clang-format off
//#####################################| NumDim| A| B| C| AData| BData| CData| AccData| A| B| C| ConvForward| Block| MPer| NPer| KPer| K1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
//#####################################| Spatial| Layout| Layout| Layout| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Size| Block| Block| Block| | WMMA| WMMA| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MRepeatPerWave| NRepeatPerWave| _MBlock_MPerBlock| ScalarPerVector|
//#####################################| | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NPerBlock| _NPerBlock|
//#####################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
// generic instance
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 64, 64, 4, 8, 16, 16, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, 1>,
// blocksize=256
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 128, 256, 8, 8, 16, 16, 2, 8, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 4>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 256, 128, 8, 8, 16, 16, 8, 2, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, 1, 1, S<1, 32, 1, 8>, 2>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 256, 64, 8, 8, 16, 16, 4, 2, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 1, S<1, 32, 1, 8>, 4>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 64, 256, 8, 8, 16, 16, 2, 4, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 16, 1, 16>, 4>,
// blocksize=128
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 64, 128, 8, 8, 16, 16, 2, 4, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 128, 128, 8, 8, 16, 16, 4, 4, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 32, 256, 8, 8, 16, 16, 1, 8, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 256, 32, 8, 8, 16, 16, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
// blocksize=64
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 64, 64, 32, 8, 8, 16, 16, 4, 1, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 64, 32, 64, 8, 8, 16, 16, 1, 4, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 32, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 64, 64, 64, 8, 8, 16, 16, 2, 4, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 32, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 64, 128, 32, 8, 8, 16, 16, 8, 1, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 64, 32, 128, 8, 8, 16, 16, 1, 8, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 32, 1, 2>, 8>,
// blocksize=32
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 32, 16, 32, 8, 8, 16, 16, 1, 2, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 16, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 32, 16, 64, 8, 8, 16, 16, 1, 4, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 16, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 32, 32, 64, 8, 8, 16, 16, 2, 4, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 16, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 32, 32, 32, 8, 8, 16, 16, 2, 2, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 16, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 32, 64, 32, 8, 8, 16, 16, 4, 2, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 16, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 32, 64, 16, 8, 8, 16, 16, 4, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, 1, 1, S<1, 16, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, F16, F16, F16, F32, PassThrough, PassThrough, PassThrough, ConvSpec, 32, 32, 16, 8, 8, 16, 16, 2, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, 1, 1, S<1, 16, 1, 2>, 8>
// clang-format on
>;
template <index_t NDSpatial,
typename ALayout,
typename BLayout,
typename CLayout,
ConvolutionBackwardWeightSpecialization ConvSpec>
using device_grouped_conv_bwd_weight_wmma_i8_instances =
std::tuple<
// clang-format off
//#####################################| NumDim| A| B| C| AData| BData| CData| AccData| A| B| C| ConvForward| Block| MPer| NPer| KPer| K1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
//#####################################| Spatial| Layout| Layout| Layout| Type| Type| Type| Type| Elementwise| Elementwise| Elementwise| Specialization| Size| Block| Block| Block| | WMMA| WMMA| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MRepeatPerWave| NRepeatPerWave| _MBlock_MPerBlock| ScalarPerVector|
//#####################################| | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NPerBlock| _NPerBlock|
//#####################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
// generic instance
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 64, 64, 4, 8, 16, 16, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 4>, 1>,
// blocksize=256
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 64, 256, 8, 8, 16, 16, 2, 4, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 256, 256, 64, 8, 8, 16, 16, 4, 2, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 1, S<1, 64, 1, 4>, 8>,
// blocksize=128
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 128, 256, 8, 8, 16, 16, 4, 8, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 64, 256, 8, 8, 16, 16, 2, 8, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 32, 256, 8, 8, 16, 16, 1, 8, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 64, 128, 8, 8, 16, 16, 2, 4, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 128, 64, 8, 8, 16, 16, 4, 2, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 256, 32, 8, 8, 16, 16, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 256, 64, 8, 8, 16, 16, 8, 2, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, 1, 1, S<1, 16, 1, 8>, 2>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 128, 256, 128, 8, 8, 16, 16, 8, 4, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
// blocksize=64
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 64, 32, 128, 8, 8, 16, 16, 1, 8, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, 1, 1, S<1, 32, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 64, 64, 128, 8, 8, 16, 16, 2, 8, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, 1, 1, S<1, 32, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 64, 128, 64, 8, 8, 16, 16, 8, 2, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 64, 128, 32, 8, 8, 16, 16, 8, 1, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, S<8, 8, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, 1, 1, S<1, 16, 1, 4>, 8>,
// blocksize=32
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 32, 16, 64, 8, 8, 16, 16, 1, 4, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, 1, 1, S<1, 16, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 32, 64, 64, 8, 8, 16, 16, 4, 4, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, 1, 1, S<1, 16, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 32, 32, 32, 8, 8, 16, 16, 2, 2, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 8, 8, 1, 1, 1, S<1, 16, 1, 2>, 8>,
DeviceGroupedConvBwdWeight_Wmma_CShuffle<NDSpatial, ALayout, BLayout, CLayout, I8, I8, I8, I32, PassThrough, PassThrough, PassThrough, ConvSpec, 32, 64, 16, 8, 8, 16, 16, 4, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 16, 8, 1, S<8, 4, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, 1, 1, S<1, 16, 1, 2>, 8>
// clang-format on
>;
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/include/ck/library/tensor_operation_instance/gpu/grouped_convolution_backward_weight.hpp
View file @ f0298581
...@@ -163,6 +163,30 @@ void add_device_grouped_conv3d_bwd_weight_xdl_gndhwc_gkzyxc_gndhwk_f16_instances ...@@ -163,6 +163,30 @@ void add_device_grouped_conv3d_bwd_weight_xdl_gndhwc_gkzyxc_gndhwk_f16_instances
PassThrough, PassThrough,
PassThrough, PassThrough,
PassThrough>>>& instances); PassThrough>>>& instances);
void add_device_grouped_conv3d_bwd_weight_wmma_gndhwc_gkzyxc_gndhwk_f16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<3,
GNDHWC,
GKZYXC,
GNDHWK,
F16,
F16,
F16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_grouped_conv3d_bwd_weight_wmma_gndhwc_gkzyxc_gndhwk_f16_1x1s1p0_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<3,
GNDHWC,
GKZYXC,
GNDHWK,
F16,
F16,
F16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
#endif #endif
#ifdef CK_ENABLE_FP32 #ifdef CK_ENABLE_FP32
void add_device_grouped_conv3d_bwd_weight_xdl_gndhwc_gkzyxc_gndhwk_f32_instances( void add_device_grouped_conv3d_bwd_weight_xdl_gndhwc_gkzyxc_gndhwk_f32_instances(
...@@ -177,6 +201,31 @@ void add_device_grouped_conv3d_bwd_weight_xdl_gndhwc_gkzyxc_gndhwk_f32_instances ...@@ -177,6 +201,31 @@ void add_device_grouped_conv3d_bwd_weight_xdl_gndhwc_gkzyxc_gndhwk_f32_instances
PassThrough, PassThrough,
PassThrough>>>& instances); PassThrough>>>& instances);
#endif #endif
#ifdef CK_ENABLE_INT8
void add_device_grouped_conv3d_bwd_weight_wmma_gndhwc_gkzyxc_gndhwk_i8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<3,
GNDHWC,
GKZYXC,
GNDHWK,
int8_t,
int8_t,
int8_t,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_grouped_conv3d_bwd_weight_wmma_gndhwc_gkzyxc_gndhwk_i8_1x1s1p0_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<3,
GNDHWC,
GKZYXC,
GNDHWK,
int8_t,
int8_t,
int8_t,
PassThrough,
PassThrough,
PassThrough>>>& instances);
#endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
void add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instances( void add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<3, std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<3,
...@@ -202,6 +251,30 @@ void add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f16_instances ...@@ -202,6 +251,30 @@ void add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f16_instances
PassThrough, PassThrough,
PassThrough, PassThrough,
PassThrough>>>& instances); PassThrough>>>& instances);
void add_device_grouped_conv3d_bwd_weight_wmma_ndhwgc_gkzyxc_ndhwgk_f16_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<3,
NDHWGC,
GKZYXC,
NDHWGK,
F16,
F16,
F16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_grouped_conv3d_bwd_weight_wmma_ndhwgc_gkzyxc_ndhwgk_f16_1x1s1p0_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<3,
NDHWGC,
GKZYXC,
NDHWGK,
F16,
F16,
F16,
PassThrough,
PassThrough,
PassThrough>>>& instances);
#endif #endif
#ifdef CK_ENABLE_FP32 #ifdef CK_ENABLE_FP32
void add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f32_instances( void add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f32_instances(
...@@ -231,6 +304,31 @@ void add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f16_comp_bf8_ ...@@ -231,6 +304,31 @@ void add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f16_comp_bf8_
BF8, BF8,
F8>>>& instances); F8>>>& instances);
#endif #endif
#ifdef CK_ENABLE_INT8
void add_device_grouped_conv3d_bwd_weight_wmma_ndhwgc_gkzyxc_ndhwgk_i8_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<3,
NDHWGC,
GKZYXC,
NDHWGK,
int8_t,
int8_t,
int8_t,
PassThrough,
PassThrough,
PassThrough>>>& instances);
void add_device_grouped_conv3d_bwd_weight_wmma_ndhwgc_gkzyxc_ndhwgk_i8_1x1s1p0_instances(
std::vector<std::unique_ptr<DeviceGroupedConvBwdWeight<3,
NDHWGC,
GKZYXC,
NDHWGK,
int8_t,
int8_t,
int8_t,
PassThrough,
PassThrough,
PassThrough>>>& instances);
#endif
#ifdef DL_KERNELS #ifdef DL_KERNELS
// dl // dl
...@@ -529,8 +627,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -529,8 +627,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_f16_instances(op_ptrs); add_device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_f16_instances(op_ptrs);
...@@ -539,9 +637,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -539,9 +637,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> && is_same_v<WeiDataType, float> &&
is_same_v<WeiDataType, float> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_bf16_f32_bf16_instances( add_device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_bf16_f32_bf16_instances(
...@@ -552,8 +649,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -552,8 +649,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
} }
else if constexpr(is_same_v<InLayout, NWGC> && is_same_v<WeiLayout, GKXC> && if constexpr(is_same_v<InLayout, NWGC> && is_same_v<WeiLayout, GKXC> &&
is_same_v<OutLayout, NWGK>) is_same_v<OutLayout, NWGK>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
#ifdef CK_ENABLE_FP32 #ifdef CK_ENABLE_FP32
...@@ -564,16 +661,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -564,16 +661,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
{ {
add_device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_f16_instances(op_ptrs); add_device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_f16_instances(op_ptrs);
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> && is_same_v<WeiDataType, float> &&
is_same_v<WeiDataType, float> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
add_device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_bf16_f32_bf16_instances( add_device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_bf16_f32_bf16_instances(
op_ptrs); op_ptrs);
...@@ -582,7 +678,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -582,7 +678,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
#endif #endif
} }
} }
else if constexpr(NumDimSpatial == 2) if constexpr(NumDimSpatial == 2)
{ {
if constexpr(is_same_v<InLayout, GNHWC> && is_same_v<WeiLayout, GKYXC> && if constexpr(is_same_v<InLayout, GNHWC> && is_same_v<WeiLayout, GKYXC> &&
is_same_v<OutLayout, GNHWK>) is_same_v<OutLayout, GNHWK>)
...@@ -600,8 +696,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -600,8 +696,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_f16_instances( add_device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_f16_instances(
...@@ -612,9 +708,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -612,9 +708,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> && is_same_v<WeiDataType, float> &&
is_same_v<WeiDataType, float> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_bf16_f32_bf16_instances( add_device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_bf16_f32_bf16_instances(
...@@ -625,8 +720,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -625,8 +720,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
} }
else if constexpr(is_same_v<InLayout, NHWGC> && is_same_v<WeiLayout, GKYXC> && if constexpr(is_same_v<InLayout, NHWGC> && is_same_v<WeiLayout, GKYXC> &&
is_same_v<OutLayout, NHWGK>) is_same_v<OutLayout, NHWGK>)
{ {
#ifdef CK_ENABLE_FP32 #ifdef CK_ENABLE_FP32
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> && if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
...@@ -641,8 +736,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -641,8 +736,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_f16_instances( add_device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_f16_instances(
...@@ -653,9 +748,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -653,9 +748,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> && is_same_v<WeiDataType, float> &&
is_same_v<WeiDataType, float> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_bf16_f32_bf16_instances( add_device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_bf16_f32_bf16_instances(
...@@ -667,7 +761,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -667,7 +761,7 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
#endif #endif
} }
} }
else if constexpr(NumDimSpatial == 3) if constexpr(NumDimSpatial == 3)
{ {
if constexpr(is_same_v<InLayout, GNDHWC> && is_same_v<WeiLayout, GKZYXC> && if constexpr(is_same_v<InLayout, GNDHWC> && is_same_v<WeiLayout, GKZYXC> &&
is_same_v<OutLayout, GNDHWK>) is_same_v<OutLayout, GNDHWK>)
...@@ -685,8 +779,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -685,8 +779,8 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t>) is_same_v<OutDataType, half_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv3d_bwd_weight_dl_gndhwc_gkzyxc_gndhwk_f16_instances( add_device_grouped_conv3d_bwd_weight_dl_gndhwc_gkzyxc_gndhwk_f16_instances(
...@@ -694,12 +788,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -694,12 +788,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
#endif #endif
add_device_grouped_conv3d_bwd_weight_xdl_gndhwc_gkzyxc_gndhwk_f16_instances( add_device_grouped_conv3d_bwd_weight_xdl_gndhwc_gkzyxc_gndhwk_f16_instances(
op_ptrs); op_ptrs);
add_device_grouped_conv3d_bwd_weight_wmma_gndhwc_gkzyxc_gndhwk_f16_instances(
op_ptrs);
add_device_grouped_conv3d_bwd_weight_wmma_gndhwc_gkzyxc_gndhwk_f16_1x1s1p0_instances(
op_ptrs);
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> && is_same_v<WeiDataType, float> &&
is_same_v<WeiDataType, float> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv3d_bwd_weight_dl_gndhwc_gkzyxc_gndhwk_bf16_f32_bf16_instances( add_device_grouped_conv3d_bwd_weight_dl_gndhwc_gkzyxc_gndhwk_bf16_f32_bf16_instances(
...@@ -708,10 +805,20 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -708,10 +805,20 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
add_device_grouped_conv3d_bwd_weight_xdl_gndhwc_gkzyxc_gndhwk_bf16_f32_bf16_instances( add_device_grouped_conv3d_bwd_weight_xdl_gndhwc_gkzyxc_gndhwk_bf16_f32_bf16_instances(
op_ptrs); op_ptrs);
} }
#endif
#ifdef CK_ENABLE_INT8
else if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<OutDataType, int8_t>)
{
add_device_grouped_conv3d_bwd_weight_wmma_gndhwc_gkzyxc_gndhwk_i8_instances(
op_ptrs);
add_device_grouped_conv3d_bwd_weight_wmma_gndhwc_gkzyxc_gndhwk_i8_1x1s1p0_instances(
op_ptrs);
}
#endif #endif
} }
else if constexpr(is_same_v<InLayout, NDHWGC> && is_same_v<WeiLayout, GKZYXC> && if constexpr(is_same_v<InLayout, NDHWGC> && is_same_v<WeiLayout, GKZYXC> &&
is_same_v<OutLayout, NDHWGK>) is_same_v<OutLayout, NDHWGK>)
{ {
#ifdef CK_ENABLE_FP32 #ifdef CK_ENABLE_FP32
if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> && if constexpr(is_same_v<InDataType, float> && is_same_v<WeiDataType, float> &&
...@@ -726,10 +833,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -726,10 +833,9 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
} }
#endif #endif
#ifdef CK_ENABLE_FP16 #ifdef CK_ENABLE_FP16
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t> && is_same_v<OutDataType, half_t> && is_same_v<ComputeTypeA, half_t> &&
is_same_v<ComputeTypeA, half_t> && is_same_v<ComputeTypeB, half_t>)
is_same_v<ComputeTypeB, half_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv3d_bwd_weight_dl_ndhwgc_gkzyxc_ndhwgk_f16_instances( add_device_grouped_conv3d_bwd_weight_dl_ndhwgc_gkzyxc_ndhwgk_f16_instances(
...@@ -737,12 +843,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -737,12 +843,15 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
#endif #endif
add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f16_instances( add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f16_instances(
op_ptrs); op_ptrs);
add_device_grouped_conv3d_bwd_weight_wmma_ndhwgc_gkzyxc_ndhwgk_f16_instances(
op_ptrs);
add_device_grouped_conv3d_bwd_weight_wmma_ndhwgc_gkzyxc_ndhwgk_f16_1x1s1p0_instances(
op_ptrs);
} }
#endif #endif
#ifdef CK_ENABLE_BF16 #ifdef CK_ENABLE_BF16
else if constexpr(is_same_v<InDataType, ck::bhalf_t> && if constexpr(is_same_v<InDataType, ck::bhalf_t> && is_same_v<WeiDataType, float> &&
is_same_v<WeiDataType, float> && is_same_v<OutDataType, ck::bhalf_t>)
is_same_v<OutDataType, ck::bhalf_t>)
{ {
#ifdef DL_KERNELS #ifdef DL_KERNELS
add_device_grouped_conv3d_bwd_weight_dl_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instances( add_device_grouped_conv3d_bwd_weight_dl_ndhwgc_gkzyxc_ndhwgk_bf16_f32_bf16_instances(
...@@ -752,10 +861,20 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe ...@@ -752,10 +861,20 @@ struct DeviceOperationInstanceFactory<ck::tensor_operation::device::DeviceGroupe
op_ptrs); op_ptrs);
} }
#endif #endif
#ifdef CK_ENABLE_INT8
else if constexpr(is_same_v<InDataType, int8_t> && is_same_v<WeiDataType, int8_t> &&
is_same_v<OutDataType, int8_t>)
{
add_device_grouped_conv3d_bwd_weight_wmma_ndhwgc_gkzyxc_ndhwgk_i8_instances(
op_ptrs);
add_device_grouped_conv3d_bwd_weight_wmma_ndhwgc_gkzyxc_ndhwgk_i8_1x1s1p0_instances(
op_ptrs);
}
#endif
#if defined CK_ENABLE_FP16 && defined CK_ENABLE_FP8 && defined CK_ENABLE_BF8 #if defined CK_ENABLE_FP16 && defined CK_ENABLE_FP8 && defined CK_ENABLE_BF8
else if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> && if constexpr(is_same_v<InDataType, half_t> && is_same_v<WeiDataType, half_t> &&
is_same_v<OutDataType, half_t> && is_same_v<OutDataType, half_t> && is_same_v<ComputeTypeA, bf8_t> &&
is_same_v<ComputeTypeA, bf8_t> && is_same_v<ComputeTypeB, f8_t>) is_same_v<ComputeTypeB, f8_t>)
{ {
add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f16_comp_bf8_f8_instances( add_device_grouped_conv3d_bwd_weight_xdl_ndhwgc_gkzyxc_ndhwgk_f16_comp_bf8_f8_instances(
op_ptrs); op_ptrs);
......
library/include/ck/library/utility/check_err.hpp
View file @ f0298581
...@@ -230,7 +230,6 @@ check_err(const Range& out, ...@@ -230,7 +230,6 @@ check_err(const Range& out,
return res; return res;
} }
#if defined CK_ENABLE_FP8
template <typename Range, typename RefRange> template <typename Range, typename RefRange>
std::enable_if_t<(std::is_same_v<ranges::range_value_t<Range>, ranges::range_value_t<RefRange>> && std::enable_if_t<(std::is_same_v<ranges::range_value_t<Range>, ranges::range_value_t<RefRange>> &&
std::is_same_v<ranges::range_value_t<Range>, f8_t>), std::is_same_v<ranges::range_value_t<Range>, f8_t>),
...@@ -275,9 +274,7 @@ check_err(const Range& out, ...@@ -275,9 +274,7 @@ check_err(const Range& out,
} }
return res; return res;
} }
#endif
#if defined CK_ENABLE_BF8
template <typename Range, typename RefRange> template <typename Range, typename RefRange>
std::enable_if_t<(std::is_same_v<ranges::range_value_t<Range>, ranges::range_value_t<RefRange>> && std::enable_if_t<(std::is_same_v<ranges::range_value_t<Range>, ranges::range_value_t<RefRange>> &&
std::is_same_v<ranges::range_value_t<Range>, bf8_t>), std::is_same_v<ranges::range_value_t<Range>, bf8_t>),
...@@ -322,7 +319,6 @@ check_err(const Range& out, ...@@ -322,7 +319,6 @@ check_err(const Range& out,
} }
return res; return res;
} }
#endif
} // namespace utils } // namespace utils
} // namespace ck } // namespace ck
library/src/tensor_operation_instance/gpu/CMakeLists.txt
View file @ f0298581
...@@ -2,44 +2,44 @@ function(add_instance_library INSTANCE_NAME) ...@@ -2,44 +2,44 @@ function(add_instance_library INSTANCE_NAME)
message("adding instance ${INSTANCE_NAME}") message("adding instance ${INSTANCE_NAME}")
set(result 1) set(result 1)
if(DEFINED DTYPES) if(DEFINED DTYPES)
foreach(source IN LISTS ARGN) foreach(source IN LISTS ARGN)
set(test 0) set(test 0)
foreach(type IN LISTS DTYPES) foreach(type IN LISTS DTYPES)
if(type MATCHES "fp16") if(type MATCHES "fp16")
set(type1 "_f16") set(type1 "_f16")
elseif(type MATCHES "fp32") elseif(type MATCHES "fp32")
set(type1 "_f32") set(type1 "_f32")
elseif(type MATCHES "fp8") elseif(type MATCHES "fp8")
set(type1 "_f8") set(type1 "_f8")
elseif(type MATCHES "bf16") elseif(type MATCHES "bf16")
set(type1 "_b16") set(type1 "_b16")
elseif(type MATCHES "fp64") elseif(type MATCHES "fp64")
set(type1 "_f64") set(type1 "_f64")
elseif(type MATCHES "int8") elseif(type MATCHES "int8")
set(type1 "_i8") set(type1 "_i8")
endif() endif()
#make an exception for reduction kernels #make an exception for reduction kernels
if("${source}" MATCHES "${type}" OR "${source}" MATCHES "${type1}" OR "${source}" MATCHES "device_reduce_instance") if("${source}" MATCHES "${type}" OR "${source}" MATCHES "${type1}" OR "${source}" MATCHES "device_reduce_instance" OR ${source} MATCHES "device_image_to_column")
#if filename matches any selected type, exit type loop and do no exclude the file from the list #if filename matches any selected type, exit type loop and do no exclude the file from the list
set(test 0) set(test 0)
break() break()
elseif((source MATCHES "fp8" OR source MATCHES "fp32" OR source MATCHES "fp64" OR source MATCHES "bf16" OR source MATCHES "int8" OR source MATCHES "fp16" OR elseif((source MATCHES "fp8" OR source MATCHES "fp32" OR source MATCHES "fp64" OR source MATCHES "bf16" OR source MATCHES "int8" OR source MATCHES "fp16" OR
source MATCHES "_f8" OR source MATCHES "_f32" OR source MATCHES "_f64" OR source MATCHES "_i8" OR source MATCHES "_f16" OR source MATCHES "_b16") AND source MATCHES "_f8" OR source MATCHES "_f32" OR source MATCHES "_f64" OR source MATCHES "_i8" OR source MATCHES "_f16" OR source MATCHES "_b16") AND
NOT(source MATCHES type OR source MATCHES type1)) NOT(source MATCHES type OR source MATCHES type1))
#if filename contains a type which doesn't match any selected type, mark it for removal #if filename contains a type which doesn't match any selected type, mark it for removal
set(test 1) set(test 1)
endif() endif()
endforeach() endforeach()
if(test EQUAL 1) if(test EQUAL 1)
message("removing instance ${source} ") message("removing instance ${source} ")
list(REMOVE_ITEM ARGN "${source}") list(REMOVE_ITEM ARGN "${source}")
endif() endif()
endforeach() endforeach()
endif() endif()
foreach(source IN LISTS ARGN) foreach(source IN LISTS ARGN)
if(NOT DEFINED DL_KERNELS AND source MATCHES "_dl") if(NOT DEFINED DL_KERNELS AND source MATCHES "_dl")
message("removing dl instance ${source} ") message("removing dl instance ${source} ")
list(REMOVE_ITEM ARGN "${source}") list(REMOVE_ITEM ARGN "${source}")
endif() endif()
endforeach() endforeach()
#only continue if there are some source files left on the list #only continue if there are some source files left on the list
...@@ -49,8 +49,10 @@ function(add_instance_library INSTANCE_NAME) ...@@ -49,8 +49,10 @@ function(add_instance_library INSTANCE_NAME)
set_target_properties(${INSTANCE_NAME} PROPERTIES POSITION_INDEPENDENT_CODE ON) set_target_properties(${INSTANCE_NAME} PROPERTIES POSITION_INDEPENDENT_CODE ON)
clang_tidy_check(${INSTANCE_NAME}) clang_tidy_check(${INSTANCE_NAME})
set(result 0) set(result 0)
message("add_instance_library ${INSTANCE_NAME}")
else()
message("skip_instance_libary ${INSTANCE_NAME}")
endif() endif()
#message("add_instance_library returns ${result}")
set(result ${result} PARENT_SCOPE) set(result ${result} PARENT_SCOPE)
endfunction(add_instance_library INSTANCE_NAME) endfunction(add_instance_library INSTANCE_NAME)
...@@ -58,65 +60,70 @@ endfunction(add_instance_library INSTANCE_NAME) ...@@ -58,65 +60,70 @@ endfunction(add_instance_library INSTANCE_NAME)
file(GLOB dir_list LIST_DIRECTORIES true *) file(GLOB dir_list LIST_DIRECTORIES true *)
set(CK_DEVICE_INSTANCES) set(CK_DEVICE_INSTANCES)
FOREACH(subdir_path ${dir_list}) FOREACH(subdir_path ${dir_list})
set(target_dir) set(target_dir)
IF(IS_DIRECTORY "${subdir_path}") IF(IS_DIRECTORY "${subdir_path}")
set(cmake_instance) set(cmake_instance)
file(READ "${subdir_path}/CMakeLists.txt" cmake_instance) file(READ "${subdir_path}/CMakeLists.txt" cmake_instance)
set(add_inst 0) set(add_inst 0)
if(("${cmake_instance}" MATCHES "_fp8" OR "${cmake_instance}" MATCHES "_f8") AND DTYPES MATCHES "fp8") if(("${cmake_instance}" MATCHES "_fp8" OR "${cmake_instance}" MATCHES "_f8") AND DTYPES MATCHES "fp8")
message("fp8 instance found!") message("fp8 instance found!")
set(add_inst 1) set(add_inst 1)
endif() endif()
if(("${cmake_instance}" MATCHES "_fp16" OR "${cmake_instance}" MATCHES "_f16") AND DTYPES MATCHES "fp16") if(("${cmake_instance}" MATCHES "_fp16" OR "${cmake_instance}" MATCHES "_f16") AND DTYPES MATCHES "fp16")
message("fp16 instance found!") message("fp16 instance found!")
set(add_inst 1) set(add_inst 1)
endif() endif()
if(("${cmake_instance}" MATCHES "_fp32" OR "${cmake_instance}" MATCHES "_f32") AND DTYPES MATCHES "fp32") if(("${cmake_instance}" MATCHES "_fp32" OR "${cmake_instance}" MATCHES "_f32") AND DTYPES MATCHES "fp32")
message("fp32 instance found!") message("fp32 instance found!")
set(add_inst 1) set(add_inst 1)
endif() endif()
if(("${cmake_instance}" MATCHES "_fp64" OR "${cmake_instance}" MATCHES "_f64") AND DTYPES MATCHES "fp64") if(("${cmake_instance}" MATCHES "_fp64" OR "${cmake_instance}" MATCHES "_f64") AND DTYPES MATCHES "fp64")
message("fp64 instance found!") message("fp64 instance found!")
set(add_inst 1) set(add_inst 1)
endif() endif()
if("${cmake_instance}" MATCHES "_bf16" AND DTYPES MATCHES "bf16") if("${cmake_instance}" MATCHES "_bf16" AND DTYPES MATCHES "bf16")
message("bf16 instance found!") message("bf16 instance found!")
set(add_inst 1) set(add_inst 1)
endif() endif()
if(("${cmake_instance}" MATCHES "_int8" OR "${cmake_instance}" MATCHES "_i8") AND DTYPES MATCHES "int8") if(("${cmake_instance}" MATCHES "_int8" OR "${cmake_instance}" MATCHES "_i8") AND DTYPES MATCHES "int8")
message("int8 instance found!") message("int8 instance found!")
set(add_inst 1) set(add_inst 1)
endif() endif()
if(NOT "${cmake_instance}" MATCHES "_fp8" OR if(NOT ("${cmake_instance}" MATCHES "_fp8" OR
NOT "${cmake_instance}" MATCHES "_f8" OR "${cmake_instance}" MATCHES "_f8" OR
NOT "${cmake_instance}" MATCHES "_fp16" OR "${cmake_instance}" MATCHES "_fp16" OR
NOT "${cmake_instance}" MATCHES "_f16" OR "${cmake_instance}" MATCHES "_f16" OR
NOT "${cmake_instance}" MATCHES "_fp32" OR "${cmake_instance}" MATCHES "_fp32" OR
NOT "${cmake_instance}" MATCHES "_f32" OR "${cmake_instance}" MATCHES "_f32" OR
NOT "${cmake_instance}" MATCHES "_fp64" OR "${cmake_instance}" MATCHES "_fp64" OR
NOT "${cmake_instance}" MATCHES "_f64" OR "${cmake_instance}" MATCHES "_f64" OR
NOT "${cmake_instance}" MATCHES "_bf16" OR "${cmake_instance}" MATCHES "_bf16" OR
NOT "${cmake_instance}" MATCHES "_int8" OR "${cmake_instance}" MATCHES "_int8" OR
NOT "${cmake_instance}" MATCHES "_i8" OR "${cmake_instance}" MATCHES "_i8" OR
NOT "${cmake_instance}" MATCHES "_int4" OR "${cmake_instance}" MATCHES "_int4"))
NOT DEFINED DTYPES) message("instance should be built for all types!")
message("instance should be built for all types!") set(add_inst 1)
set(add_inst 1) endif()
endif() if(NOT DEFINED DTYPES)
if("${cmake_instance}" MATCHES "quantization" AND DEFINED DTYPES AND NOT DTYPES MATCHES "int8") set(add_inst 1)
message("quantization instances will not be built!") endif()
set(add_inst 0) if(("${cmake_instance}" MATCHES "quantization") AND (DEFINED DTYPES) AND (NOT DTYPES MATCHES "int8"))
endif() message("quantization instances will not be built!")
if("${cmake_instance}" MATCHES "ONLY DL_KERNELS" AND NOT DEFINED DL_KERNELS)
message("Found only dl instances, but DL_KERNELS is not set. Skipping.")
set(add_inst 0) set(add_inst 0)
endif() endif()
if(add_inst EQUAL 1) if(("${cmake_instance}" MATCHES "ONLY DL_KERNELS") AND (NOT DEFINED DL_KERNELS))
get_filename_component(target_dir ${subdir_path} NAME) message("Found only dl instances, but DL_KERNELS is not set. Skipping.")
add_subdirectory(${target_dir}) set(add_inst 0)
list(APPEND CK_DEVICE_INSTANCES $<TARGET_OBJECTS:device_${target_dir}_instance>) endif()
endif() if((add_inst EQUAL 1))
ENDIF() get_filename_component(target_dir ${subdir_path} NAME)
add_subdirectory(${target_dir})
list(APPEND CK_DEVICE_INSTANCES $<TARGET_OBJECTS:device_${target_dir}_instance>)
message("add_instance_directory ${subdir_path}")
else()
message("skip_instance_directory ${subdir_path}")
endif()
ENDIF()
ENDFOREACH() ENDFOREACH()
add_library(device_operations STATIC ${CK_DEVICE_INSTANCES}) add_library(device_operations STATIC ${CK_DEVICE_INSTANCES})
...@@ -158,11 +165,11 @@ target_compile_options(device_operations PRIVATE ...@@ -158,11 +165,11 @@ target_compile_options(device_operations PRIVATE
# install(TARGETS device_operations LIBRARY DESTINATION lib) # install(TARGETS device_operations LIBRARY DESTINATION lib)
rocm_install(TARGETS device_operations rocm_install(TARGETS device_operations
EXPORT device_operationsTargets) EXPORT device_operationsTargets)
rocm_install(DIRECTORY ${DEV_OPS_INC_DIRS} DESTINATION ${CMAKE_INSTALL_INCLUDEDIR}/ck) rocm_install(DIRECTORY ${DEV_OPS_INC_DIRS} DESTINATION ${CMAKE_INSTALL_INCLUDEDIR}/ck)
rocm_install(EXPORT device_operationsTargets rocm_install(EXPORT device_operationsTargets
FILE composable_kerneldevice_operationsTargets.cmake FILE composable_kerneldevice_operationsTargets.cmake
NAMESPACE composable_kernel:: NAMESPACE composable_kernel::
DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/composable_kernel DESTINATION ${CMAKE_INSTALL_LIBDIR}/cmake/composable_kernel
) )
library/src/tensor_operation_instance/gpu/gemm_splitk/CMakeLists.txt
View file @ f0298581
...@@ -15,6 +15,10 @@ list(APPEND GEMM_SPLITK_INSTANCES device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_in ...@@ -15,6 +15,10 @@ list(APPEND GEMM_SPLITK_INSTANCES device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_in
device_gemm_xdl_splitk_f16_fp8_f16_mk_kn_mn_instance.cpp device_gemm_xdl_splitk_f16_fp8_f16_mk_kn_mn_instance.cpp
device_gemm_xdl_splitk_f16_fp8_f16_mk_nk_mn_instance.cpp device_gemm_xdl_splitk_f16_fp8_f16_mk_nk_mn_instance.cpp
device_gemm_xdl_splitk_f16_fp8_f16_km_kn_mn_instance.cpp device_gemm_xdl_splitk_f16_fp8_f16_km_kn_mn_instance.cpp
device_gemm_xdl_splitk_f16_fp8_f16_km_nk_mn_instance.cpp) device_gemm_xdl_splitk_f16_fp8_f16_km_nk_mn_instance.cpp
device_gemm_xdl_splitk_f16_f16_f16_comp_fp8_mk_kn_mn_instance.cpp
device_gemm_xdl_splitk_f16_f16_f16_comp_fp8_mk_nk_mn_instance.cpp
device_gemm_xdl_splitk_f16_f16_f16_comp_fp8_km_kn_mn_instance.cpp
device_gemm_xdl_splitk_f16_f16_f16_comp_fp8_km_nk_mn_instance.cpp)
add_instance_library(device_gemm_splitk_instance ${GEMM_SPLITK_INSTANCES}) add_instance_library(device_gemm_splitk_instance ${GEMM_SPLITK_INSTANCES})
library/src/tensor_operation_instance/gpu/gemm_splitk/device_gemm_xdl_splitk_f16_f16_f16_comp_fp8_km_kn_mn_instance.cpp 0 → 100755
View file @ f0298581
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, 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/impl/device_gemm_xdl_splitk_c_shuffle.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using F8 = ck::f8_t;
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;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_splitk_f16_f16_f16_comp_f8_km_kn_mn_instances = std::tuple<
// clang-format off
//#########################|AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| GEMM| 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| Compute|
//#########################| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise|Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector| Type|
//#########################| | | | | | | | 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| |
//#########################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 4>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, 1, 1, S<1, 16, 1, 4>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>
// clang-format on
>;
void add_device_gemm_xdl_splitk_f16_f16_f16_comp_f8_km_kn_mn_instances(
std::vector<std::unique_ptr<
DeviceGemmSplitK<Col, Row, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough, F8>>>&
instances)
{
add_device_operation_instances(instances,
device_gemm_xdl_splitk_f16_f16_f16_comp_f8_km_kn_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_splitk/device_gemm_xdl_splitk_f16_f16_f16_comp_fp8_km_nk_mn_instance.cpp 0 → 100755
View file @ f0298581
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, 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/impl/device_gemm_xdl_splitk_c_shuffle.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using F8 = ck::f8_t;
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;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_splitk_f16_f16_f16_comp_f8_km_nk_mn_instances = std::tuple<
// clang-format off
//#########################|AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| GEMM| 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| Compute|
//#########################| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise|Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector| Type|
//#########################| | | | | | | | 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| |
//#########################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, 1, 1, S<1, 32, 1, 4>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, 1, 1, S<1, 16, 1, 4>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, GemmDefault, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>
// clang-format on
>;
void add_device_gemm_xdl_splitk_f16_f16_f16_comp_f8_km_nk_mn_instances(
std::vector<std::unique_ptr<
DeviceGemmSplitK<Col, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough, F8>>>&
instances)
{
add_device_operation_instances(instances,
device_gemm_xdl_splitk_f16_f16_f16_comp_f8_km_nk_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_splitk/device_gemm_xdl_splitk_f16_f16_f16_comp_fp8_mk_kn_mn_instance.cpp 0 → 100755
View file @ f0298581
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, 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/impl/device_gemm_xdl_splitk_c_shuffle.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using F8 = ck::f8_t;
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;
// static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
static constexpr auto GemmMNPadding = ck::tensor_operation::device::GemmSpecialization::MNPadding;
using device_gemm_xdl_splitk_f16_f16_f16_comp_f8_mk_kn_mn_generic_instances = std::tuple<
// clang-format off
//#########################|AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| GEMM| 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| Compute|
//#########################| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise|Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector| Type|
//#########################| | | | | | | | 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| |
//#########################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 32, 64, 4, 8, 32, 32, 1, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 1, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, 1, 1, S<1, 16, 1, 8>, 2, F8>
// clang-format on
>;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_splitk_f16_f16_f16_comp_f8_mk_kn_mn_instances = std::tuple<
// clang-format off
//#########################|AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| GEMM| 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| Compute|
//#########################| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise|Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector| Type|
//#########################| | | | | | | | 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| |
//#########################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 64, 192, 4, 8, 32, 32, 1, 3, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 48, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 192, 64, 4, 8, 32, 32, 3, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 4>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, 1, 1, S<1, 16, 1, 4>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 32, 192, 4, 8, 32, 32, 1, 3, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 24, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 8, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 192, 32, 4, 8, 32, 32, 3, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, 1, 1, S<1, 32, 1, 4>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 32, 64, 4, 8, 32, 32, 1, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 64, 32, 4, 8, 32, 32, 1, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, 1, 1, S<1, 32, 1, 4>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, GemmMNPadding, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 8, true, 1, 1, S<1, 32, 1, 4>, 8, F8>
// clang-format on
>;
void add_device_gemm_xdl_splitk_f16_f16_f16_comp_f8_mk_kn_mn_instances(
std::vector<std::unique_ptr<
DeviceGemmSplitK<Row, Row, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough, F8>>>&
instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_splitk_f16_f16_f16_comp_f8_mk_kn_mn_generic_instances{});
add_device_operation_instances(instances,
device_gemm_xdl_splitk_f16_f16_f16_comp_f8_mk_kn_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_splitk/device_gemm_xdl_splitk_f16_f16_f16_comp_fp8_mk_nk_mn_instance.cpp 0 → 100755
View file @ f0298581
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, 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/impl/device_gemm_xdl_splitk_c_shuffle.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
using F8 = ck::f8_t;
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;
static constexpr auto MNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
using device_gemm_xdl_splitk_f16_f16_f16_comp_f8_mk_nk_mn_generic_instances = std::tuple<
// clang-format off
//#########################|AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| GEMM| 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| Compute|
//#########################| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise|Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector| Type|
//#########################| | | | | | | | 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| |
//#########################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 1, 8, true, S<1, 4, 16, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 1, 8, true, 1, 1, S<1, 16, 1, 4>, 2, F8>
// clang-format on
>;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_splitk_f16_f16_f16_comp_f8_mk_nk_mn_instances = std::tuple<
// clang-format off
//#########################|AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| GEMM| 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| Compute|
//#########################| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise|Specialization| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MXdlPerWave_MWaveMPerXdl| ScalarPerVector| Type|
//#########################| | | | | | | | 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| |
//#########################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 256, 256, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 256, 128, 256, 4, 8, 32, 32, 2, 4, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 128, 128, 128, 4, 8, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 256, 128, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 128, 128, 64, 4, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 32, 1, 4>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 128, 64, 128, 4, 8, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 64, 64, 64, 4, 8, 32, 32, 2, 2, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 16, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 16, 1, 4>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 256, 128, 64, 4, 8, 32, 32, 2, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 256, 64, 128, 4, 8, 32, 32, 1, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 128, 128, 32, 4, 8, 32, 32, 2, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 32, 1, 4>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 128, 32, 128, 4, 8, 32, 32, 1, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 16, 1, 8>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 64, 64, 32, 4, 8, 32, 32, 2, 1, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 16, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 16, 1, 4>, 8, F8>,
DeviceGemmXdlSplitKCShuffle< F16, F16, F16, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, MNKPadding, 64, 32, 64, 4, 8, 32, 32, 1, 2, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 8, 8, true, S<1, 4, 16, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 3, 8, 8, true, 1, 1, S<1, 16, 1, 4>, 8, F8>
// clang-format on
>;
void add_device_gemm_xdl_splitk_f16_f16_f16_comp_f8_mk_nk_mn_instances(
std::vector<std::unique_ptr<
DeviceGemmSplitK<Row, Col, Row, F16, F16, F16, PassThrough, PassThrough, PassThrough, F8>>>&
instances)
{
add_device_operation_instances(
instances, device_gemm_xdl_splitk_f16_f16_f16_comp_f8_mk_nk_mn_generic_instances{});
add_device_operation_instances(instances,
device_gemm_xdl_splitk_f16_f16_f16_comp_f8_mk_nk_mn_instances{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/grouped_conv1d_bwd_weight/CMakeLists.txt
View file @ f0298581
set(GROUPED_CONV1D_BWD_WEIGHT set(GROUPED_CONV1D_BWD_WEIGHT
device_grouped_conv1d_bwd_weight_xdl_gnwc_gkxc_gnwk_f16_instance.cpp xdl/device_grouped_conv1d_bwd_weight_xdl_gnwc_gkxc_gnwk_f16_instance.cpp
device_grouped_conv1d_bwd_weight_xdl_gnwc_gkxc_gnwk_f32_instance.cpp xdl/device_grouped_conv1d_bwd_weight_xdl_gnwc_gkxc_gnwk_f32_instance.cpp
device_grouped_conv1d_bwd_weight_xdl_gnwc_gkxc_gnwk_bf16_instance.cpp) xdl/device_grouped_conv1d_bwd_weight_xdl_gnwc_gkxc_gnwk_bf16_instance.cpp)
if(DL_KERNELS) if(DL_KERNELS)
list(APPEND GROUPED_CONV1D_BWD_WEIGHT list(APPEND GROUPED_CONV1D_BWD_WEIGHT
device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_f16_instance.cpp dl/device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_f16_instance.cpp
device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_f32_instance.cpp dl/device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_f32_instance.cpp
device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_bf16_instance.cpp dl/device_grouped_conv1d_bwd_weight_dl_gnwc_gkxc_gnwk_bf16_instance.cpp
device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_f16_instance.cpp dl/device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_f16_instance.cpp
device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_f32_instance.cpp dl/device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_f32_instance.cpp
device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_bf16_instance.cpp) dl/device_grouped_conv1d_bwd_weight_dl_nwgc_gkxc_nwgk_bf16_instance.cpp)
endif() endif()
add_instance_library(device_grouped_conv1d_bwd_weight_instance ${GROUPED_CONV1D_BWD_WEIGHT}) add_instance_library(device_grouped_conv1d_bwd_weight_instance ${GROUPED_CONV1D_BWD_WEIGHT})
library/src/tensor_operation_instance/gpu/grouped_conv2d_bwd_weight/CMakeLists.txt
View file @ f0298581
set(GROUPED_CONV2D_BWD_WEIGHT set(GROUPED_CONV2D_BWD_WEIGHT
device_grouped_conv2d_bwd_weight_xdl_gnhwc_gkyxc_gnhwk_f16_instance.cpp xdl/device_grouped_conv2d_bwd_weight_xdl_gnhwc_gkyxc_gnhwk_f16_instance.cpp
device_grouped_conv2d_bwd_weight_xdl_gnhwc_gkyxc_gnhwk_f32_instance.cpp xdl/device_grouped_conv2d_bwd_weight_xdl_gnhwc_gkyxc_gnhwk_f32_instance.cpp
device_grouped_conv2d_bwd_weight_xdl_gnhwc_gkyxc_gnhwk_bf16_instance.cpp xdl/device_grouped_conv2d_bwd_weight_xdl_gnhwc_gkyxc_gnhwk_bf16_instance.cpp
device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_f16_instance.cpp xdl/device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_f16_instance.cpp
device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_f32_instance.cpp xdl/device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_f32_instance.cpp
device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_bf16_instance.cpp) xdl/device_grouped_conv2d_bwd_weight_xdl_nhwgc_gkyxc_nhwgk_bf16_instance.cpp)
if(DL_KERNELS) if(DL_KERNELS)
list(APPEND GROUPED_CONV2D_BWD_WEIGHT list(APPEND GROUPED_CONV2D_BWD_WEIGHT
device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_f16_instance.cpp dl/device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_f16_instance.cpp
device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_f32_instance.cpp dl/device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_f32_instance.cpp
device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_bf16_instance.cpp dl/device_grouped_conv2d_bwd_weight_dl_gnhwc_gkyxc_gnhwk_bf16_instance.cpp
device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_f16_instance.cpp dl/device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_f16_instance.cpp
device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_f32_instance.cpp dl/device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_f32_instance.cpp
device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_bf16_instance.cpp) dl/device_grouped_conv2d_bwd_weight_dl_nhwgc_gkyxc_nhwgk_bf16_instance.cpp)
endif() endif()
add_instance_library(device_grouped_conv2d_bwd_weight_instance ${GROUPED_CONV2D_BWD_WEIGHT}) add_instance_library(device_grouped_conv2d_bwd_weight_instance ${GROUPED_CONV2D_BWD_WEIGHT})
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment