mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-03 13:11:25 +00:00
Revert "Add support for mixed precision in contraction scale and bilinear" (#967)
* Revert "Add support for mixed precision in contraction scale and bilinear (#936)"
This reverts commit f07485060e.
* revert commits #957 and #960
This commit is contained in:
Illia Silin
@@ -1,61 +0,0 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <array>
|
||||
|
||||
#include "ck/tensor_operation/gpu/device/device_base.hpp"
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
|
||||
// GEMM:
|
||||
// input : A0[M0, M1, ... K0, K1, ...], ...
|
||||
// input : B0[N0, N1, ... K0, K1, ...], ...
|
||||
// input : D0[M0, M1, ... N0, N1, ...], D1[M0, M1, ... N0, N1, ...], ...
|
||||
// output : E[M0, M1, ... N0, N1, ...]
|
||||
// C = a_op(A) * b_op(B)
|
||||
// E = cde_op(C, D0, D1, ...)
|
||||
// Assume:
|
||||
// D0, D1, ... and E have the same layout
|
||||
template <index_t NumDimM,
|
||||
index_t NumDimN,
|
||||
index_t NumDimK,
|
||||
typename AsDataType,
|
||||
typename BsDataType,
|
||||
typename DsDataType,
|
||||
typename EDataType,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CDEElementwiseOperation>
|
||||
struct DeviceContractionMultipleABD : public BaseOperator
|
||||
{
|
||||
static constexpr index_t NumATensor = AsDataType::Size();
|
||||
static constexpr index_t NumBTensor = BsDataType::Size();
|
||||
static constexpr index_t NumDTensor = DsDataType::Size();
|
||||
|
||||
virtual std::unique_ptr<BaseArgument>
|
||||
MakeArgumentPointer(std::array<const void*, NumATensor> p_as,
|
||||
std::array<const void*, NumBTensor> p_bs,
|
||||
std::array<const void*, NumDTensor> p_ds,
|
||||
void* p_e,
|
||||
const std::array<std::vector<index_t>, NumATensor>& a_ms_ks_lengths,
|
||||
const std::array<std::vector<index_t>, NumATensor>& a_ms_ks_strides,
|
||||
const std::array<std::vector<index_t>, NumBTensor>& b_ns_ks_lengths,
|
||||
const std::array<std::vector<index_t>, NumBTensor>& b_ns_ks_strides,
|
||||
const std::array<std::vector<index_t>, NumDTensor>& d_ms_ns_lengths,
|
||||
const std::array<std::vector<index_t>, NumDTensor>& d_ms_ns_strides,
|
||||
const std::vector<index_t>& e_ms_ns_length,
|
||||
const std::vector<index_t>& e_ms_ns_stride,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op) = 0;
|
||||
|
||||
virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -33,8 +33,7 @@ template <index_t NumDimM,
|
||||
typename EDataType,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CDEElementwiseOperation,
|
||||
typename ComputeDataType = ADataType>
|
||||
typename CDEElementwiseOperation>
|
||||
struct DeviceContractionMultipleD : public BaseOperator
|
||||
{
|
||||
static constexpr index_t NumDTensor = DsDataType::Size();
|
||||
|
||||
@@ -1,846 +0,0 @@
|
||||
// SPDX-License-Identifier: MIT
|
||||
// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <iostream>
|
||||
#include <sstream>
|
||||
|
||||
#include "ck/utility/common_header.hpp"
|
||||
#include "ck/tensor_description/tensor_descriptor.hpp"
|
||||
#include "ck/tensor_description/tensor_descriptor_helper.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_abd.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
|
||||
#include "ck/tensor_operation/gpu/device/matrix_padder.hpp"
|
||||
#include "ck/tensor_operation/gpu/grid/gridwise_gemm_multiple_abd_xdl_cshuffle.hpp"
|
||||
#include "ck/host_utility/device_prop.hpp"
|
||||
#include "ck/host_utility/kernel_launch.hpp"
|
||||
|
||||
namespace ck {
|
||||
|
||||
template <typename GridwiseGemm,
|
||||
typename AsPointer,
|
||||
typename BsPointer,
|
||||
typename DsPointer,
|
||||
typename EDataType,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CDEElementwiseOperation,
|
||||
typename AsGridDesc_AK0_M_AK1,
|
||||
typename BsGridDesc_BK0_N_BK1,
|
||||
typename DsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
typename Block2ETileMap,
|
||||
bool HasMainKBlockLoop>
|
||||
__global__ void
|
||||
#if CK_USE_LAUNCH_BOUNDS
|
||||
__launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
|
||||
#endif
|
||||
kernel_contraction_multiple_abd_xdl_cshuffle(
|
||||
AsPointer p_as_grid,
|
||||
BsPointer p_bs_grid,
|
||||
DsPointer p_ds_grid,
|
||||
EDataType* __restrict__ p_e_grid,
|
||||
const AElementwiseOperation a_element_op,
|
||||
const BElementwiseOperation b_element_op,
|
||||
const CDEElementwiseOperation cde_element_op,
|
||||
const AsGridDesc_AK0_M_AK1 as_grid_desc_ak0_m_ak1,
|
||||
const BsGridDesc_BK0_N_BK1 bs_grid_desc_bk0_n_bk1,
|
||||
const DsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
const EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
const Block2ETileMap block_2_etile_map)
|
||||
{
|
||||
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
|
||||
defined(__gfx940__) || defined(__gfx941__) || defined(__gfx942__))
|
||||
__shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
|
||||
|
||||
GridwiseGemm::template Run<HasMainKBlockLoop>(p_as_grid,
|
||||
p_bs_grid,
|
||||
p_ds_grid,
|
||||
p_e_grid,
|
||||
p_shared,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op,
|
||||
as_grid_desc_ak0_m_ak1,
|
||||
bs_grid_desc_bk0_n_bk1,
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock,
|
||||
block_2_etile_map);
|
||||
#else
|
||||
ignore = p_as_grid;
|
||||
ignore = p_bs_grid;
|
||||
ignore = p_ds_grid;
|
||||
ignore = p_e_grid;
|
||||
ignore = a_element_op;
|
||||
ignore = b_element_op;
|
||||
ignore = cde_element_op;
|
||||
ignore = as_grid_desc_ak0_m_ak1;
|
||||
ignore = bs_grid_desc_bk0_n_bk1;
|
||||
ignore = ds_grid_desc_mblock_mperblock_nblock_nperblock;
|
||||
ignore = e_grid_desc_mblock_mperblock_nblock_nperblock;
|
||||
ignore = block_2_etile_map;
|
||||
#endif
|
||||
}
|
||||
|
||||
} // namespace ck
|
||||
|
||||
namespace ck {
|
||||
namespace tensor_operation {
|
||||
namespace device {
|
||||
|
||||
// GEMM:
|
||||
// input : A[M, K]
|
||||
// input : B[N, K]
|
||||
// input : D0[M, N], D1[M, N], ...
|
||||
// output : E[M, N]
|
||||
// C = a_op(A) * b_op(B)
|
||||
// E = cde_op(C, D0, D1, ...)
|
||||
// Assume:
|
||||
// D0, D1, ... and E have the same layout
|
||||
template <index_t NumDimM,
|
||||
index_t NumDimN,
|
||||
index_t NumDimK,
|
||||
typename AsDataType,
|
||||
typename BsDataType,
|
||||
typename AccDataType,
|
||||
typename CShuffleDataType,
|
||||
typename DsDataType,
|
||||
typename EDataType,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CDEElementwiseOperation,
|
||||
GemmSpecialization GemmSpec,
|
||||
index_t NumGemmKPrefetchStage,
|
||||
index_t BlockSize,
|
||||
index_t MPerBlock,
|
||||
index_t NPerBlock,
|
||||
index_t KPerBlock,
|
||||
index_t AK1,
|
||||
index_t BK1,
|
||||
index_t MPerXDL,
|
||||
index_t NPerXDL,
|
||||
index_t MXdlPerWave,
|
||||
index_t NXdlPerWave,
|
||||
typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
|
||||
typename ABlockTransferThreadClusterArrangeOrder,
|
||||
typename ABlockTransferSrcAccessOrder,
|
||||
index_t ABlockTransferSrcVectorDim,
|
||||
index_t ABlockTransferSrcScalarPerVector,
|
||||
index_t ABlockTransferDstScalarPerVector_AK1,
|
||||
index_t ABlockLdsExtraM,
|
||||
typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
|
||||
typename BBlockTransferThreadClusterArrangeOrder,
|
||||
typename BBlockTransferSrcAccessOrder,
|
||||
index_t BBlockTransferSrcVectorDim,
|
||||
index_t BBlockTransferSrcScalarPerVector,
|
||||
index_t BBlockTransferDstScalarPerVector_BK1,
|
||||
index_t BBlockLdsExtraN,
|
||||
index_t CShuffleMXdlPerWavePerShuffle,
|
||||
index_t CShuffleNXdlPerWavePerShuffle,
|
||||
typename CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
index_t CDEBlockTransferScalarPerVector_NPerBlock,
|
||||
LoopScheduler LoopSched = make_default_loop_scheduler(),
|
||||
PipelineVersion PipelineVer = PipelineVersion::v1>
|
||||
struct DeviceContractionMultipleABD_Xdl_CShuffle
|
||||
: public DeviceContractionMultipleABD<NumDimM,
|
||||
NumDimN,
|
||||
NumDimK,
|
||||
AsDataType,
|
||||
BsDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CDEElementwiseOperation>
|
||||
{
|
||||
using DeviceOp = DeviceContractionMultipleABD_Xdl_CShuffle;
|
||||
|
||||
static constexpr index_t NumATensor = AsDataType::Size();
|
||||
static constexpr index_t NumBTensor = BsDataType::Size();
|
||||
static constexpr index_t NumDTensor = DsDataType::Size();
|
||||
|
||||
static constexpr auto I0 = Number<0>{};
|
||||
static constexpr auto I1 = Number<1>{};
|
||||
static constexpr auto I2 = Number<2>{};
|
||||
static constexpr auto I3 = Number<3>{};
|
||||
|
||||
using ComputeDataType = EDataType;
|
||||
|
||||
// GridwiseGemm
|
||||
using GridwiseGemm = GridwiseGemmMultipleABD_xdl_cshuffle<
|
||||
AsDataType,
|
||||
BsDataType,
|
||||
ComputeDataType,
|
||||
AccDataType,
|
||||
CShuffleDataType,
|
||||
DsDataType,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CDEElementwiseOperation,
|
||||
InMemoryDataOperationEnum::Set,
|
||||
NumGemmKPrefetchStage,
|
||||
BlockSize,
|
||||
MPerBlock,
|
||||
NPerBlock,
|
||||
KPerBlock,
|
||||
AK1,
|
||||
BK1,
|
||||
MPerXDL,
|
||||
NPerXDL,
|
||||
MXdlPerWave,
|
||||
NXdlPerWave,
|
||||
ABlockTransferThreadClusterLengths_AK0_M_AK1,
|
||||
ABlockTransferThreadClusterArrangeOrder,
|
||||
ABlockTransferSrcAccessOrder,
|
||||
ABlockTransferSrcVectorDim,
|
||||
ABlockTransferSrcScalarPerVector,
|
||||
ABlockTransferDstScalarPerVector_AK1,
|
||||
false,
|
||||
ABlockLdsExtraM,
|
||||
BBlockTransferThreadClusterLengths_BK0_N_BK1,
|
||||
BBlockTransferThreadClusterArrangeOrder,
|
||||
BBlockTransferSrcAccessOrder,
|
||||
BBlockTransferSrcVectorDim,
|
||||
BBlockTransferSrcScalarPerVector,
|
||||
BBlockTransferDstScalarPerVector_BK1,
|
||||
false,
|
||||
BBlockLdsExtraN,
|
||||
CShuffleMXdlPerWavePerShuffle,
|
||||
CShuffleNXdlPerWavePerShuffle,
|
||||
CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
CDEBlockTransferScalarPerVector_NPerBlock,
|
||||
LoopSched,
|
||||
PipelineVer>;
|
||||
|
||||
static constexpr auto matrix_padder =
|
||||
ck::tensor_operation::device::MatrixPadder<GemmSpec, index_t, index_t, index_t>{
|
||||
MPerBlock, NPerBlock, KPerBlock};
|
||||
|
||||
static auto MakeAGridDescriptor_M_K(const std::vector<index_t>& a_ms_ks_lengths_,
|
||||
const std::vector<index_t>& a_ms_ks_strides_)
|
||||
{
|
||||
assert(a_ms_ks_lengths_.size() == NumDimM + NumDimK &&
|
||||
a_ms_ks_strides_.size() == NumDimM + NumDimK);
|
||||
|
||||
const auto to_tuple = [&](auto& vec, auto num) {
|
||||
return generate_tuple([&](auto i) { return vec[i]; }, num);
|
||||
};
|
||||
|
||||
const auto a_ms_ks_lengths = to_tuple(a_ms_ks_lengths_, Number<NumDimM + NumDimK>{});
|
||||
const auto a_ms_ks_strides = to_tuple(a_ms_ks_strides_, Number<NumDimM + NumDimK>{});
|
||||
|
||||
// dimension Ids for M0, M1, ...
|
||||
constexpr auto mDimIds = typename arithmetic_sequence_gen<0, NumDimM, 1>::type{};
|
||||
|
||||
// dimension Ids for K0, K1, ...
|
||||
constexpr auto kDimIds =
|
||||
typename arithmetic_sequence_gen<NumDimM, NumDimM + NumDimK, 1>::type{};
|
||||
|
||||
// lengths for M0, M1, ...
|
||||
const auto mLengths = get_container_subset(a_ms_ks_lengths, mDimIds);
|
||||
|
||||
// lengths for K0, K1, ...
|
||||
const auto kLengths = get_container_subset(a_ms_ks_lengths, kDimIds);
|
||||
|
||||
// naive tensor A[M0, M1, M2, ..., K0, K1, K2...]
|
||||
const auto a_grid_desc_ms_ks =
|
||||
make_naive_tensor_descriptor(a_ms_ks_lengths, a_ms_ks_strides);
|
||||
|
||||
// transformed tensor A[MRaw = M0 * M1 * M2 * ... , KRaw = K0 * K1 * K2 * ...]
|
||||
const auto a_grid_desc_mraw_kraw = transform_tensor_descriptor(
|
||||
a_grid_desc_ms_ks,
|
||||
make_tuple(make_merge_transform(mLengths), make_merge_transform(kLengths)),
|
||||
make_tuple(mDimIds, kDimIds),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
|
||||
return matrix_padder.PadADescriptor_M_K(a_grid_desc_mraw_kraw);
|
||||
}
|
||||
|
||||
__host__ __device__ static auto
|
||||
MakeAsGridDescriptor_M_K(const std::array<std::vector<index_t>, NumATensor>& as_ms_ks_lengths,
|
||||
const std::array<std::vector<index_t>, NumATensor>& as_ms_ks_strides)
|
||||
{
|
||||
return generate_tuple(
|
||||
[&](auto i) {
|
||||
return MakeAGridDescriptor_M_K(as_ms_ks_lengths[i], as_ms_ks_strides[i]);
|
||||
},
|
||||
Number<NumATensor>{});
|
||||
}
|
||||
|
||||
// Assume: B[N0, N1, N2, ..., K0, K1, K2, ...]
|
||||
static auto MakeBGridDescriptor_N_K(const std::vector<index_t>& b_ns_ks_lengths_,
|
||||
const std::vector<index_t>& b_ns_ks_strides_)
|
||||
{
|
||||
assert(b_ns_ks_lengths_.size() == NumDimN + NumDimK &&
|
||||
b_ns_ks_strides_.size() == NumDimN + NumDimK);
|
||||
|
||||
const auto to_tuple = [&](auto& vec, auto num) {
|
||||
return generate_tuple([&](auto i) { return vec[i]; }, num);
|
||||
};
|
||||
|
||||
const auto b_ns_ks_lengths = to_tuple(b_ns_ks_lengths_, Number<NumDimN + NumDimK>{});
|
||||
const auto b_ns_ks_strides = to_tuple(b_ns_ks_strides_, Number<NumDimN + NumDimK>{});
|
||||
|
||||
// dimension Ids for N0, N1, ...
|
||||
constexpr auto nDimIds = typename arithmetic_sequence_gen<0, NumDimN, 1>::type{};
|
||||
|
||||
// dimension Ids for K0, K1, ...
|
||||
constexpr auto kDimIds =
|
||||
typename arithmetic_sequence_gen<NumDimN, NumDimN + NumDimK, 1>::type{};
|
||||
|
||||
// lengths for K0, K1, ...
|
||||
const auto kLengths = get_container_subset(b_ns_ks_lengths, kDimIds);
|
||||
|
||||
// lengths for N0, N1, ...
|
||||
const auto nLengths = get_container_subset(b_ns_ks_lengths, nDimIds);
|
||||
|
||||
// naive tensor B[N0, N1, N2, ..., K0, K1, K2, ...]
|
||||
const auto b_grid_desc_ns_ks =
|
||||
make_naive_tensor_descriptor(b_ns_ks_lengths, b_ns_ks_strides);
|
||||
|
||||
// transformed tensor B[NRaw = N0 * N1 * N2 * ..., KRaw = K0 * K1 * K2 * ...]
|
||||
const auto b_grid_desc_nraw_kraw = transform_tensor_descriptor(
|
||||
b_grid_desc_ns_ks,
|
||||
make_tuple(make_merge_transform(nLengths), make_merge_transform(kLengths)),
|
||||
make_tuple(nDimIds, kDimIds),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
|
||||
return matrix_padder.PadBDescriptor_N_K(b_grid_desc_nraw_kraw);
|
||||
}
|
||||
|
||||
__host__ __device__ static auto
|
||||
MakeBsGridDescriptor_N_K(const std::array<std::vector<index_t>, NumBTensor>& bs_ns_ks_lengths,
|
||||
const std::array<std::vector<index_t>, NumBTensor>& bs_ns_ks_strides)
|
||||
{
|
||||
return generate_tuple(
|
||||
[&](auto i) {
|
||||
return MakeBGridDescriptor_N_K(bs_ns_ks_lengths[i], bs_ns_ks_strides[i]);
|
||||
},
|
||||
Number<NumBTensor>{});
|
||||
}
|
||||
|
||||
// assume E[M0, M1, M2, ..., N0, N1, N2...]
|
||||
static auto MakeEGridDescriptor_M_N(const std::vector<index_t>& e_ms_ns_lengths_,
|
||||
const std::vector<index_t>& e_ms_ns_strides_)
|
||||
{
|
||||
assert(e_ms_ns_lengths_.size() == NumDimM + NumDimN &&
|
||||
e_ms_ns_strides_.size() == NumDimM + NumDimN);
|
||||
|
||||
const auto to_tuple = [&](auto& vec, auto num) {
|
||||
return generate_tuple([&](auto i) { return vec[i]; }, num);
|
||||
};
|
||||
|
||||
const auto e_ms_ns_lengths = to_tuple(e_ms_ns_lengths_, Number<NumDimM + NumDimN>{});
|
||||
const auto e_ms_ns_strides = to_tuple(e_ms_ns_strides_, Number<NumDimM + NumDimN>{});
|
||||
|
||||
// dimension Ids for M0, M1, ...
|
||||
constexpr auto mDimIds = typename arithmetic_sequence_gen<0, NumDimM, 1>::type{};
|
||||
|
||||
// dimension Ids for N0, N1, ...
|
||||
constexpr auto nDimIds =
|
||||
typename arithmetic_sequence_gen<NumDimM, NumDimM + NumDimN, 1>::type{};
|
||||
|
||||
// lengths for M0, M1, ...
|
||||
const auto mLengths = get_container_subset(e_ms_ns_lengths, mDimIds);
|
||||
|
||||
// lengths for K0, K1, ...
|
||||
const auto nLengths = get_container_subset(e_ms_ns_lengths, nDimIds);
|
||||
|
||||
// naive tensor E[M0, M1, M2, ..., N0, N1, N2...]
|
||||
const auto e_grid_desc_ms_ns =
|
||||
make_naive_tensor_descriptor(e_ms_ns_lengths, e_ms_ns_strides);
|
||||
|
||||
// transformed tensor E[MRaw = M0 * M1 * M2 * ... , NRaw = N0 * N1 * N2 * ...]
|
||||
const auto e_grid_desc_mraw_nraw = transform_tensor_descriptor(
|
||||
e_grid_desc_ms_ns,
|
||||
make_tuple(make_merge_transform(mLengths), make_merge_transform(nLengths)),
|
||||
make_tuple(mDimIds, nDimIds),
|
||||
make_tuple(Sequence<0>{}, Sequence<1>{}));
|
||||
|
||||
return matrix_padder.PadCDescriptor_M_N(e_grid_desc_mraw_nraw);
|
||||
}
|
||||
|
||||
static auto
|
||||
MakeDsGridDescriptor_M_N(const std::array<std::vector<index_t>, NumDTensor>& ds_ms_ns_lengths,
|
||||
const std::array<std::vector<index_t>, NumDTensor>& ds_ms_ns_strides)
|
||||
{
|
||||
return generate_tuple(
|
||||
[&](auto i) {
|
||||
return MakeEGridDescriptor_M_N(ds_ms_ns_lengths[i], ds_ms_ns_strides[i]);
|
||||
},
|
||||
Number<NumDTensor>{});
|
||||
}
|
||||
|
||||
// desc for problem definition
|
||||
using AsGridDesc_M_K = remove_cvref_t<decltype(MakeAsGridDescriptor_M_K({}, {}))>;
|
||||
using BsGridDesc_N_K = remove_cvref_t<decltype(MakeBsGridDescriptor_N_K({}, {}))>;
|
||||
using DsGridDesc_M_N = remove_cvref_t<decltype(MakeDsGridDescriptor_M_N({}, {}))>;
|
||||
using EGridDesc_M_N = remove_cvref_t<decltype(MakeEGridDescriptor_M_N({}, {}))>;
|
||||
|
||||
// desc for blockwise copy
|
||||
using AsGridDesc_AK0_M_AK1 =
|
||||
remove_cvref_t<decltype(GridwiseGemm::MakeAsGridDescriptor_AK0_M_AK1(AsGridDesc_M_K{}))>;
|
||||
using BsGridDesc_BK0_N_BK1 =
|
||||
remove_cvref_t<decltype(GridwiseGemm::MakeBsGridDescriptor_BK0_N_BK1(BsGridDesc_N_K{}))>;
|
||||
using DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock = remove_cvref_t<
|
||||
decltype(GridwiseGemm::MakeDsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
DsGridDesc_M_N{}))>;
|
||||
using EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock =
|
||||
remove_cvref_t<decltype(GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
EGridDesc_M_N{}))>;
|
||||
|
||||
// block-to-e-tile map
|
||||
using Block2ETileMap =
|
||||
remove_cvref_t<decltype(GridwiseGemm::MakeBlock2ETileMap(EGridDesc_M_N{}))>;
|
||||
|
||||
// Argument
|
||||
struct Argument : public BaseArgument
|
||||
{
|
||||
Argument(std::array<const void*, NumATensor> p_as_grid,
|
||||
std::array<const void*, NumBTensor> p_bs_grid,
|
||||
std::array<const void*, NumDTensor> p_ds_grid,
|
||||
void* p_e_grid,
|
||||
const std::array<std::vector<index_t>, NumATensor>& a_ms_ks_lengths,
|
||||
const std::array<std::vector<index_t>, NumATensor>& a_ms_ks_strides,
|
||||
const std::array<std::vector<index_t>, NumBTensor>& b_ns_ks_lengths,
|
||||
const std::array<std::vector<index_t>, NumBTensor>& b_ns_ks_strides,
|
||||
const std::array<std::vector<index_t>, NumDTensor>& d_ms_ns_lengths,
|
||||
const std::array<std::vector<index_t>, NumDTensor>& d_ms_ns_strides,
|
||||
const std::vector<index_t>& e_ms_ns_length,
|
||||
const std::vector<index_t>& e_ms_ns_stride,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op)
|
||||
: p_as_grid_{},
|
||||
p_bs_grid_{},
|
||||
p_ds_grid_{},
|
||||
p_e_grid_{static_cast<EDataType*>(p_e_grid)},
|
||||
as_grid_desc_m_k_{},
|
||||
bs_grid_desc_n_k_{},
|
||||
ds_grid_desc_m_n_{},
|
||||
e_grid_desc_m_n_{MakeEGridDescriptor_M_N(e_ms_ns_length, e_ms_ns_stride)},
|
||||
as_grid_desc_ak0_m_ak1_{},
|
||||
bs_grid_desc_bk0_n_bk1_{},
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock_{},
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock_{},
|
||||
block_2_etile_map_{GridwiseGemm::MakeBlock2ETileMap(e_grid_desc_m_n_)},
|
||||
a_element_op_{a_element_op},
|
||||
b_element_op_{b_element_op},
|
||||
cde_element_op_{cde_element_op}
|
||||
{
|
||||
// populate pointer, desc for As
|
||||
static_for<0, NumATensor, 1>{}([&](auto i) {
|
||||
// using ALayout = remove_cvref_t<tuple_element_t<i.value, AsLayout>>;
|
||||
using ADataType = remove_cvref_t<tuple_element_t<i.value, AsDataType>>;
|
||||
|
||||
// A pointer
|
||||
p_as_grid_(i) = static_cast<const ADataType*>(p_as_grid[i]);
|
||||
|
||||
// A desc
|
||||
as_grid_desc_m_k_(i) =
|
||||
MakeAGridDescriptor_M_K(a_ms_ks_lengths[i], a_ms_ks_strides[i]);
|
||||
});
|
||||
|
||||
// populate pointer, desc for Bs
|
||||
static_for<0, NumBTensor, 1>{}([&](auto i) {
|
||||
// using BLayout = remove_cvref_t<tuple_element_t<i.value, BsLayout>>;
|
||||
using BDataType = remove_cvref_t<tuple_element_t<i.value, BsDataType>>;
|
||||
|
||||
// B pointer
|
||||
p_bs_grid_(i) = static_cast<const BDataType*>(p_bs_grid[i]);
|
||||
|
||||
// B desc
|
||||
bs_grid_desc_n_k_(i) =
|
||||
MakeBGridDescriptor_N_K(b_ns_ks_lengths[i], b_ns_ks_strides[i]);
|
||||
});
|
||||
|
||||
// populate pointer, desc for Ds
|
||||
static_for<0, NumDTensor, 1>{}([&](auto i) {
|
||||
// using DLayout = remove_cvref_t<tuple_element_t<i.value, DsLayout>>;
|
||||
using DDataType = remove_cvref_t<tuple_element_t<i.value, DsDataType>>;
|
||||
|
||||
// D pointer
|
||||
p_ds_grid_(i) = static_cast<const DDataType*>(p_ds_grid[i]);
|
||||
|
||||
// D desc
|
||||
ds_grid_desc_m_n_(i) =
|
||||
MakeEGridDescriptor_M_N(d_ms_ns_lengths[i], d_ms_ns_strides[i]);
|
||||
});
|
||||
|
||||
// populate desc for Ds/E
|
||||
if(GridwiseGemm::CheckValidity(as_grid_desc_m_k_,
|
||||
bs_grid_desc_n_k_,
|
||||
ds_grid_desc_m_n_,
|
||||
e_grid_desc_m_n_,
|
||||
block_2_etile_map_))
|
||||
{
|
||||
as_grid_desc_ak0_m_ak1_ =
|
||||
GridwiseGemm::MakeAsGridDescriptor_AK0_M_AK1(as_grid_desc_m_k_);
|
||||
|
||||
bs_grid_desc_bk0_n_bk1_ =
|
||||
GridwiseGemm::MakeBsGridDescriptor_BK0_N_BK1(bs_grid_desc_n_k_);
|
||||
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock_ =
|
||||
GridwiseGemm::MakeDsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
ds_grid_desc_m_n_);
|
||||
|
||||
e_grid_desc_mblock_mperblock_nblock_nperblock_ =
|
||||
GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
|
||||
e_grid_desc_m_n_);
|
||||
}
|
||||
|
||||
// for sanity check of vector memory access
|
||||
for(index_t i = 0; i < NumATensor; ++i)
|
||||
{
|
||||
a_mz_stride_[i] = a_ms_ks_strides[i][NumDimM - 1];
|
||||
a_kz_stride_[i] = a_ms_ks_strides[i][NumDimM + NumDimK - 1];
|
||||
}
|
||||
|
||||
for(index_t i = 0; i < NumBTensor; ++i)
|
||||
{
|
||||
b_nz_stride_[i] = b_ns_ks_strides[i][NumDimN - 1];
|
||||
b_kz_stride_[i] = b_ns_ks_strides[i][NumDimN + NumDimK - 1];
|
||||
}
|
||||
|
||||
for(index_t i = 0; i < NumDTensor; ++i)
|
||||
{
|
||||
ds_nz_stride_[i] = d_ms_ns_strides[i][NumDimM + NumDimN - 1];
|
||||
}
|
||||
|
||||
e_nz_stride_ = e_ms_ns_stride[NumDimM + NumDimN - 1];
|
||||
}
|
||||
|
||||
// pointers
|
||||
typename GridwiseGemm::AsGridPointer p_as_grid_;
|
||||
typename GridwiseGemm::BsGridPointer p_bs_grid_;
|
||||
typename GridwiseGemm::DsGridPointer p_ds_grid_;
|
||||
EDataType* p_e_grid_;
|
||||
|
||||
// tensor descriptors for problem definiton
|
||||
AsGridDesc_M_K as_grid_desc_m_k_;
|
||||
BsGridDesc_N_K bs_grid_desc_n_k_;
|
||||
DsGridDesc_M_N ds_grid_desc_m_n_;
|
||||
EGridDesc_M_N e_grid_desc_m_n_;
|
||||
|
||||
// tensor descriptors for block/thread-wise copy
|
||||
AsGridDesc_AK0_M_AK1 as_grid_desc_ak0_m_ak1_;
|
||||
BsGridDesc_BK0_N_BK1 bs_grid_desc_bk0_n_bk1_;
|
||||
DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock
|
||||
ds_grid_desc_mblock_mperblock_nblock_nperblock_;
|
||||
EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock e_grid_desc_mblock_mperblock_nblock_nperblock_;
|
||||
|
||||
// block-to-e-tile map
|
||||
Block2ETileMap block_2_etile_map_;
|
||||
|
||||
// element-wise op
|
||||
AElementwiseOperation a_element_op_;
|
||||
BElementwiseOperation b_element_op_;
|
||||
CDEElementwiseOperation cde_element_op_;
|
||||
|
||||
// Strides for the last M/N/K dimensions of A/B/Ds/E
|
||||
// for sanity check of vector load/store
|
||||
std::array<index_t, NumATensor> a_mz_stride_;
|
||||
std::array<index_t, NumATensor> a_kz_stride_;
|
||||
|
||||
std::array<index_t, NumBTensor> b_nz_stride_;
|
||||
std::array<index_t, NumBTensor> b_kz_stride_;
|
||||
|
||||
std::array<index_t, NumDTensor> ds_nz_stride_;
|
||||
index_t e_nz_stride_;
|
||||
};
|
||||
|
||||
// Invoker
|
||||
struct Invoker : public BaseInvoker
|
||||
{
|
||||
using Argument = DeviceOp::Argument;
|
||||
|
||||
float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
|
||||
{
|
||||
if(!GridwiseGemm::CheckValidity(arg.as_grid_desc_m_k_,
|
||||
arg.bs_grid_desc_n_k_,
|
||||
arg.ds_grid_desc_m_n_,
|
||||
arg.e_grid_desc_m_n_,
|
||||
arg.block_2_etile_map_))
|
||||
{
|
||||
throw std::runtime_error("wrong! GridwiseGemm has invalid setting");
|
||||
}
|
||||
|
||||
const index_t grid_size =
|
||||
arg.block_2_etile_map_.CalculateGridSize(arg.e_grid_desc_m_n_);
|
||||
|
||||
auto launch_kernel = [&](auto has_main_k_block_loop) {
|
||||
constexpr bool has_main_loop = has_main_k_block_loop.value;
|
||||
|
||||
const auto kernel = kernel_contraction_multiple_abd_xdl_cshuffle<
|
||||
GridwiseGemm,
|
||||
typename GridwiseGemm::AsGridPointer,
|
||||
typename GridwiseGemm::BsGridPointer,
|
||||
typename GridwiseGemm::DsGridPointer,
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CDEElementwiseOperation,
|
||||
DeviceOp::AsGridDesc_AK0_M_AK1,
|
||||
DeviceOp::BsGridDesc_BK0_N_BK1,
|
||||
DeviceOp::DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
DeviceOp::EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
|
||||
DeviceOp::Block2ETileMap,
|
||||
has_main_loop>;
|
||||
|
||||
return launch_and_time_kernel(stream_config,
|
||||
kernel,
|
||||
dim3(grid_size),
|
||||
dim3(BlockSize),
|
||||
0,
|
||||
arg.p_as_grid_,
|
||||
arg.p_bs_grid_,
|
||||
arg.p_ds_grid_,
|
||||
arg.p_e_grid_,
|
||||
arg.a_element_op_,
|
||||
arg.b_element_op_,
|
||||
arg.cde_element_op_,
|
||||
arg.as_grid_desc_ak0_m_ak1_,
|
||||
arg.bs_grid_desc_bk0_n_bk1_,
|
||||
arg.ds_grid_desc_mblock_mperblock_nblock_nperblock_,
|
||||
arg.e_grid_desc_mblock_mperblock_nblock_nperblock_,
|
||||
arg.block_2_etile_map_);
|
||||
};
|
||||
|
||||
const auto K = arg.as_grid_desc_m_k_[I0].GetLength(I1);
|
||||
|
||||
if(GridwiseGemm::CalculateHasMainKBlockLoop(K))
|
||||
{
|
||||
return launch_kernel(integral_constant<bool, true>{});
|
||||
}
|
||||
else
|
||||
{
|
||||
return launch_kernel(integral_constant<bool, false>{});
|
||||
}
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
float Run(const BaseArgument* p_arg,
|
||||
const StreamConfig& stream_config = StreamConfig{}) override
|
||||
{
|
||||
return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
|
||||
}
|
||||
};
|
||||
|
||||
static bool IsSupportedArgument(const Argument& arg)
|
||||
{
|
||||
if(!ck::is_xdl_supported())
|
||||
{
|
||||
return false;
|
||||
}
|
||||
|
||||
// check vector load/store
|
||||
{
|
||||
bool all_valid = true;
|
||||
|
||||
static_for<0, NumATensor, 1>{}([&](auto i) {
|
||||
// vector memory access of A: could be on M or AK1 dimension
|
||||
if constexpr(ABlockTransferSrcVectorDim == 1)
|
||||
{
|
||||
if(!(arg.a_mz_stride_[i] == 1 && arg.as_grid_desc_ak0_m_ak1_[i].GetLength(I1) %
|
||||
ABlockTransferSrcScalarPerVector ==
|
||||
0))
|
||||
{
|
||||
all_valid = false;
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
if(!(arg.a_kz_stride_[i] == 1 && arg.as_grid_desc_ak0_m_ak1_[i].GetLength(I2) %
|
||||
ABlockTransferSrcScalarPerVector ==
|
||||
0))
|
||||
{
|
||||
all_valid = false;
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// vector memory access of B: could be on N or BK1 dimension
|
||||
static_for<0, NumBTensor, 1>{}([&](auto i) {
|
||||
if constexpr(BBlockTransferSrcVectorDim == 1)
|
||||
{
|
||||
if(!(arg.b_nz_stride_[i] == 1 && arg.bs_grid_desc_bk0_n_bk1_[i].GetLength(I1) %
|
||||
BBlockTransferSrcScalarPerVector ==
|
||||
0))
|
||||
{
|
||||
all_valid = false;
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
if(!(arg.b_kz_stride_[i] == 1 && arg.bs_grid_desc_bk0_n_bk1_[i].GetLength(I2) %
|
||||
BBlockTransferSrcScalarPerVector ==
|
||||
0))
|
||||
{
|
||||
all_valid = false;
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// check vector load of Ds
|
||||
static_for<0, NumDTensor, 1>{}([&](auto i) {
|
||||
if(!(arg.ds_nz_stride_[i] == 1 &&
|
||||
arg.ds_grid_desc_mblock_mperblock_nblock_nperblock_[i].GetLength(I3) %
|
||||
CDEBlockTransferScalarPerVector_NPerBlock ==
|
||||
0))
|
||||
{
|
||||
all_valid = false;
|
||||
}
|
||||
});
|
||||
|
||||
// vector memory access of E: always on NPerBlock dimension
|
||||
if(!(arg.e_nz_stride_ == 1 &&
|
||||
arg.e_grid_desc_mblock_mperblock_nblock_nperblock_.GetLength(I3) %
|
||||
CDEBlockTransferScalarPerVector_NPerBlock ==
|
||||
0))
|
||||
{
|
||||
all_valid = false;
|
||||
}
|
||||
|
||||
if(!all_valid)
|
||||
{
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
return GridwiseGemm::CheckValidity(arg.as_grid_desc_m_k_,
|
||||
arg.bs_grid_desc_n_k_,
|
||||
arg.ds_grid_desc_m_n_,
|
||||
arg.e_grid_desc_m_n_,
|
||||
arg.block_2_etile_map_);
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
bool IsSupportedArgument(const BaseArgument* p_arg) override
|
||||
{
|
||||
return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
|
||||
}
|
||||
|
||||
static auto MakeArgument(std::array<const void*, NumATensor> p_as,
|
||||
std::array<const void*, NumBTensor> p_bs,
|
||||
std::array<const void*, NumDTensor> p_ds,
|
||||
void* p_e,
|
||||
const std::array<std::vector<index_t>, NumATensor>& a_ms_ks_lengths,
|
||||
const std::array<std::vector<index_t>, NumATensor>& a_ms_ks_strides,
|
||||
const std::array<std::vector<index_t>, NumBTensor>& b_ns_ks_lengths,
|
||||
const std::array<std::vector<index_t>, NumBTensor>& b_ns_ks_strides,
|
||||
const std::array<std::vector<index_t>, NumDTensor>& d_ms_ns_lengths,
|
||||
const std::array<std::vector<index_t>, NumDTensor>& d_ms_ns_strides,
|
||||
const std::vector<index_t>& e_ms_ns_length,
|
||||
const std::vector<index_t>& e_ms_ns_stride,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op)
|
||||
{
|
||||
return Argument{p_as,
|
||||
p_bs,
|
||||
p_ds,
|
||||
p_e,
|
||||
a_ms_ks_lengths,
|
||||
a_ms_ks_strides,
|
||||
b_ns_ks_lengths,
|
||||
b_ns_ks_strides,
|
||||
d_ms_ns_lengths,
|
||||
d_ms_ns_strides,
|
||||
e_ms_ns_length,
|
||||
e_ms_ns_stride,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op};
|
||||
}
|
||||
|
||||
static auto MakeInvoker() { return Invoker{}; }
|
||||
|
||||
// polymorphic
|
||||
std::unique_ptr<BaseArgument>
|
||||
MakeArgumentPointer(std::array<const void*, NumATensor> p_as,
|
||||
std::array<const void*, NumBTensor> p_bs,
|
||||
std::array<const void*, NumDTensor> p_ds,
|
||||
void* p_e,
|
||||
const std::array<std::vector<index_t>, NumATensor>& as_ms_ks_lengths,
|
||||
const std::array<std::vector<index_t>, NumATensor>& as_ms_ks_strides,
|
||||
const std::array<std::vector<index_t>, NumBTensor>& bs_ns_ks_lengths,
|
||||
const std::array<std::vector<index_t>, NumBTensor>& bs_ns_ks_strides,
|
||||
const std::array<std::vector<index_t>, NumDTensor>& ds_ms_ns_lengths,
|
||||
const std::array<std::vector<index_t>, NumDTensor>& ds_ms_ns_strides,
|
||||
const std::vector<index_t>& e_ms_ns_length,
|
||||
const std::vector<index_t>& e_ms_ns_stride,
|
||||
AElementwiseOperation a_element_op,
|
||||
BElementwiseOperation b_element_op,
|
||||
CDEElementwiseOperation cde_element_op) override
|
||||
{
|
||||
return std::make_unique<Argument>(p_as,
|
||||
p_bs,
|
||||
p_ds,
|
||||
p_e,
|
||||
as_ms_ks_lengths,
|
||||
as_ms_ks_strides,
|
||||
bs_ns_ks_lengths,
|
||||
bs_ns_ks_strides,
|
||||
ds_ms_ns_lengths,
|
||||
ds_ms_ns_strides,
|
||||
e_ms_ns_length,
|
||||
e_ms_ns_stride,
|
||||
a_element_op,
|
||||
b_element_op,
|
||||
cde_element_op);
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
|
||||
{
|
||||
return std::make_unique<Invoker>(Invoker{});
|
||||
}
|
||||
|
||||
// polymorphic
|
||||
std::string GetTypeString() const override
|
||||
{
|
||||
auto str = std::stringstream();
|
||||
|
||||
std::map<LoopScheduler, std::string> LoopSchedToString{
|
||||
{LoopScheduler::Default, "Default"}, {LoopScheduler::Interwave, "Interwave"}};
|
||||
|
||||
std::map<PipelineVersion, std::string> PipelineVersionToString{{PipelineVersion::v1, "v1"},
|
||||
{PipelineVersion::v2, "v2"}};
|
||||
|
||||
// clang-format off
|
||||
str << "DeviceContractionMultipleABD_Xdl_CShuffle"
|
||||
<< "<"
|
||||
<< BlockSize << ", "
|
||||
<< MPerBlock << ", "
|
||||
<< NPerBlock << ", "
|
||||
<< KPerBlock << ", "
|
||||
<< AK1 << ", "
|
||||
<< BK1 << ", "
|
||||
<< MPerXDL << ", "
|
||||
<< NPerXDL << ", "
|
||||
<< MXdlPerWave << ", "
|
||||
<< NXdlPerWave << ", "
|
||||
<< ABlockTransferSrcScalarPerVector << ", "
|
||||
<< BBlockTransferSrcScalarPerVector << ", "
|
||||
<< CShuffleMXdlPerWavePerShuffle << ", "
|
||||
<< CShuffleNXdlPerWavePerShuffle << ", "
|
||||
<< getGemmSpecializationString(GemmSpec)
|
||||
<< ">"
|
||||
<< " LoopScheduler: "
|
||||
<< LoopSchedToString[LoopSched] << ", "
|
||||
<< "PipelineVersion: "
|
||||
<< PipelineVersionToString[PipelineVer];
|
||||
// clang-format on
|
||||
|
||||
return str.str();
|
||||
}
|
||||
};
|
||||
|
||||
} // namespace device
|
||||
} // namespace tensor_operation
|
||||
} // namespace ck
|
||||
@@ -112,7 +112,6 @@ template <index_t NumDimM,
|
||||
typename CShuffleDataType,
|
||||
typename DsDataType,
|
||||
typename EDataType,
|
||||
typename ComputeDataType,
|
||||
typename AElementwiseOperation,
|
||||
typename BElementwiseOperation,
|
||||
typename CDEElementwiseOperation,
|
||||
@@ -157,8 +156,7 @@ struct DeviceContractionMultipleD_Xdl_CShuffle
|
||||
EDataType,
|
||||
AElementwiseOperation,
|
||||
BElementwiseOperation,
|
||||
CDEElementwiseOperation,
|
||||
ComputeDataType>
|
||||
CDEElementwiseOperation>
|
||||
{
|
||||
using DeviceOp = DeviceContractionMultipleD_Xdl_CShuffle;
|
||||
|
||||
@@ -312,6 +310,8 @@ struct DeviceContractionMultipleD_Xdl_CShuffle
|
||||
using DsGridDesc_M_N = remove_cvref_t<decltype(MakeDsGridDescriptor_M_N({{}}, {{}}))>;
|
||||
using EGridDesc_M_N = decltype(MakeEGridDescriptor_M_N({}, {}));
|
||||
|
||||
using ComputeDataType = ADataType;
|
||||
|
||||
// GridwiseGemm
|
||||
using GridwiseGemm = GridwiseGemmMultipleD_xdl_cshuffle<
|
||||
ADataType, // TODO: distinguish A/B datatype
|
||||
|
||||
Reference in New Issue
Block a user