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Revert "Implement device grouped gemm fixed nk multi abd for rdna4 (#3619)" (#3705)

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This reverts commit 372a284890dc19cfd3c241c3e9a6076d35e843a5.

[ROCm/composable_kernel commit: 569640dc70]
This commit is contained in:
Illia Silin
2026-02-03 09:52:14 -08:00
committed by GitHub
parent 4add4af76e
commit aef327296e
24 changed files with 120 additions and 3517 deletions
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6
library/src/tensor_operation_instance/gpu/grouped_gemm_fixed_nk_multi_abd/CMakeLists.txt
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@@ -1,17 +1,13 @@
# Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
# SPDX-License-Identifier: MIT
# ONLY XDL_AND_WMMA_KERNELS
# ONLY XDL_KERNELS
set(GROUPED_GEMM_FIXED_NK_MULTI_ABD_INSTANCES)
list(APPEND GROUPED_GEMM_FIXED_NK_MULTI_ABD_INSTANCES
device_grouped_gemm_xdl_fixed_nk_bias_gelu_bf16_i8_bf16_mk_kn_mn_instance.cpp
device_grouped_gemm_xdl_fixed_nk_bias_gelu_bf16_i8_bf16_mk_nk_mn_instance.cpp
device_grouped_gemm_xdl_fixed_nk_bias_gelu_bf16_i8_bf16_km_kn_mn_instance.cpp
device_grouped_gemm_wmma_fixed_nk_bias_gelu_bf16_i8_bf16_mk_kn_mn_instance.cpp
device_grouped_gemm_wmma_fixed_nk_bias_gelu_bf16_i8_bf16_mk_nk_mn_instance.cpp
device_grouped_gemm_wmma_fixed_nk_bias_gelu_bf16_i8_bf16_km_kn_mn_instance.cpp
)
add_instance_library(device_grouped_gemm_fixed_nk_multi_abd_instance ${GROUPED_GEMM_FIXED_NK_MULTI_ABD_INSTANCES})

144
library/src/tensor_operation_instance/gpu/grouped_gemm_fixed_nk_multi_abd/device_grouped_gemm_wmma_fixed_nk_bias_gelu_bf16_i8_bf16_km_kn_mn_instance.cpp
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@@ -1,144 +0,0 @@
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_grouped_gemm_multi_abd.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_grouped_gemm_multi_abd_wmma_fixed_nk.hpp"
#include "ck/tensor_operation/gpu/element/unary_element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
template <index_t... Is>
using S = Sequence<Is...>;
using BF16 = bhalf_t;
using I8 = int8_t;
using F32 = float;
using Row = tensor_layout::gemm::RowMajor;
using Col = tensor_layout::gemm::ColumnMajor;
using Multiply = element_wise::Multiply;
using PassThrough = element_wise::PassThrough;
using AddFastGelu = element_wise::AddFastGelu;
using Add = element_wise::Add;
using FastGelu = element_wise::FastGelu;
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
template <typename DsLayout,
typename DsDataType,
typename CDEElementOp,
GemmSpecialization GemmSpec>
using device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_km_kn_mn_instances = std::tuple<
// clang-format off
//#######################################| AsLayout| BsLayout| DsLayout| ELayout| AsData| BData| AccData| CShuffle| DsData| EData| A| B| CDE| GEMM| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
//#######################################| | | | | Type| Type| Type| DataType| Type| Type| Elementwise| Elementwise| Elementwise| Spacialization| Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MRepeat| NRepeat| _MBlock_MPerBlock_NBlock_NPerBlock| ScalarPerVector|
//#######################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| | _NWaveNPerXdl|
//#######################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGroupedGemm_Wmma_Multi_ABD_Fixed_NK< Tuple<Col>, Tuple<Row, Row>, DsLayout, Row, Tuple<BF16>, Tuple<I8, BF16>, F32, BF16, DsDataType, BF16, PassThrough, Multiply, CDEElementOp, GemmSpec, 256, 256, 256, 32, 8, 8, 16, 16, 8, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, 0, 1, 1, S<1, 32, 1, 8>, 4>,
DeviceGroupedGemm_Wmma_Multi_ABD_Fixed_NK< Tuple<Col>, Tuple<Row, Row>, DsLayout, Row, Tuple<BF16>, Tuple<I8, BF16>, F32, BF16, DsDataType, BF16, PassThrough, Multiply, CDEElementOp, GemmSpec, 256, 128, 256, 32, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, 0, 1, 1, S<1, 32, 1, 8>, 4>,
DeviceGroupedGemm_Wmma_Multi_ABD_Fixed_NK< Tuple<Col>, Tuple<Row, Row>, DsLayout, Row, Tuple<BF16>, Tuple<I8, BF16>, F32, BF16, DsDataType, BF16, PassThrough, Multiply, CDEElementOp, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 2, 4, S<4, 32, 2>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 0, S<4, 32, 2>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, 0, 1, 1, S<1, 32, 1, 8>, 4>
// clang-format on
>;
void add_device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_km_kn_mn_bias_gelu_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmMultiABDFixedNK<Tuple<Col>,
Tuple<Row, Row>,
Tuple<Row>,
Row,
Tuple<BF16>,
Tuple<I8, BF16>,
Tuple<BF16>,
BF16,
PassThrough,
Multiply,
AddFastGelu>>>& instances)
{
add_device_operation_instances(
instances,
device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_km_kn_mn_instances<
Tuple<Row>,
Tuple<BF16>,
AddFastGelu,
GemmMNKPadding>{});
}
void add_device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_km_kn_mn_bias_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmMultiABDFixedNK<Tuple<Col>,
Tuple<Row, Row>,
Tuple<Row>,
Row,
Tuple<BF16>,
Tuple<I8, BF16>,
Tuple<BF16>,
BF16,
PassThrough,
Multiply,
Add>>>& instances)
{
add_device_operation_instances(
instances,
device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_km_kn_mn_instances<
Tuple<Row>,
Tuple<BF16>,
Add,
GemmMNKPadding>{});
}
void add_device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_km_kn_mn_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmMultiABDFixedNK<Tuple<Col>,
Tuple<Row, Row>,
Tuple<>,
Row,
Tuple<BF16>,
Tuple<I8, BF16>,
Tuple<>,
BF16,
PassThrough,
Multiply,
PassThrough>>>& instances)
{
add_device_operation_instances(
instances,
device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_km_kn_mn_instances<
Tuple<>,
Tuple<>,
PassThrough,
GemmMNKPadding>{});
}
void add_device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_km_kn_mn_gelu_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmMultiABDFixedNK<Tuple<Col>,
Tuple<Row, Row>,
Tuple<>,
Row,
Tuple<BF16>,
Tuple<I8, BF16>,
Tuple<>,
BF16,
PassThrough,
Multiply,
FastGelu>>>& instances)
{
add_device_operation_instances(
instances,
device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_km_kn_mn_instances<
Tuple<>,
Tuple<>,
FastGelu,
GemmMNKPadding>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck

144
library/src/tensor_operation_instance/gpu/grouped_gemm_fixed_nk_multi_abd/device_grouped_gemm_wmma_fixed_nk_bias_gelu_bf16_i8_bf16_mk_kn_mn_instance.cpp
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@@ -1,144 +0,0 @@
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_grouped_gemm_multi_abd.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_grouped_gemm_multi_abd_wmma_fixed_nk.hpp"
#include "ck/tensor_operation/gpu/element/unary_element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
template <index_t... Is>
using S = Sequence<Is...>;
using BF16 = bhalf_t;
using I8 = int8_t;
using F32 = float;
using Row = tensor_layout::gemm::RowMajor;
using Col = tensor_layout::gemm::ColumnMajor;
using Multiply = element_wise::Multiply;
using PassThrough = element_wise::PassThrough;
using AddFastGelu = element_wise::AddFastGelu;
using Add = element_wise::Add;
using FastGelu = element_wise::FastGelu;
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
template <typename DsLayout,
typename DsDataType,
typename CDEElementOp,
GemmSpecialization GemmSpec>
using device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_kn_mn_instances = std::tuple<
// clang-format off
//#######################################| AsLayout| BsLayout| DsLayout| ELayout| AsData| BsData| AccData| CShuffle| DsData| EData| A| B| CDE| GEMM| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
//#######################################| | | | | Type| Type| Type| DataType| Type| Type| Elementwise| Elementwise| Elementwise| Spacialization| Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MRepeat| NRepeat| _MBlock_MPerBlock_NBlock_NPerBlock| ScalarPerVector|
//#######################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| | |
//#######################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGroupedGemm_Wmma_Multi_ABD_Fixed_NK< Tuple<Row>, Tuple<Row, Row>, DsLayout, Row, Tuple<BF16>, Tuple<I8, BF16>, F32, BF16, DsDataType, BF16, PassThrough, Multiply, CDEElementOp, GemmSpec, 256, 256, 256, 32, 8, 8, 16, 16, 8, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, 0, 1, 1, S<1, 32, 1, 8>, 4>,
DeviceGroupedGemm_Wmma_Multi_ABD_Fixed_NK< Tuple<Row>, Tuple<Row, Row>, DsLayout, Row, Tuple<BF16>, Tuple<I8, BF16>, F32, BF16, DsDataType, BF16, PassThrough, Multiply, CDEElementOp, GemmSpec, 256, 128, 256, 32, 8, 8, 16, 16, 4, 4, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 0, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 4, 0, 1, 1, S<1, 32, 1, 8>, 4>,
DeviceGroupedGemm_Wmma_Multi_ABD_Fixed_NK< Tuple<Row>, Tuple<Row, Row>, DsLayout, Row, Tuple<BF16>, Tuple<I8, BF16>, F32, BF16, DsDataType, BF16, PassThrough, Multiply, CDEElementOp, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 2>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 32, 1, 8>, 4>
// clang-format on
>;
void add_device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_kn_mn_bias_gelu_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmMultiABDFixedNK<Tuple<Row>,
Tuple<Row, Row>,
Tuple<Row>,
Row,
Tuple<BF16>,
Tuple<I8, BF16>,
Tuple<BF16>,
BF16,
PassThrough,
Multiply,
AddFastGelu>>>& instances)
{
add_device_operation_instances(
instances,
device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_kn_mn_instances<
Tuple<Row>,
Tuple<BF16>,
AddFastGelu,
GemmMNKPadding>{});
}
void add_device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_kn_mn_bias_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmMultiABDFixedNK<Tuple<Row>,
Tuple<Row, Row>,
Tuple<Row>,
Row,
Tuple<BF16>,
Tuple<I8, BF16>,
Tuple<BF16>,
BF16,
PassThrough,
Multiply,
Add>>>& instances)
{
add_device_operation_instances(
instances,
device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_kn_mn_instances<
Tuple<Row>,
Tuple<BF16>,
Add,
GemmMNKPadding>{});
}
void add_device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_kn_mn_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmMultiABDFixedNK<Tuple<Row>,
Tuple<Row, Row>,
Tuple<>,
Row,
Tuple<BF16>,
Tuple<I8, BF16>,
Tuple<>,
BF16,
PassThrough,
Multiply,
PassThrough>>>& instances)
{
add_device_operation_instances(
instances,
device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_kn_mn_instances<
Tuple<>,
Tuple<>,
PassThrough,
GemmMNKPadding>{});
}
void add_device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_kn_mn_gelu_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmMultiABDFixedNK<Tuple<Row>,
Tuple<Row, Row>,
Tuple<>,
Row,
Tuple<BF16>,
Tuple<I8, BF16>,
Tuple<>,
BF16,
PassThrough,
Multiply,
FastGelu>>>& instances)
{
add_device_operation_instances(
instances,
device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_kn_mn_instances<
Tuple<>,
Tuple<>,
FastGelu,
GemmMNKPadding>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck

144
library/src/tensor_operation_instance/gpu/grouped_gemm_fixed_nk_multi_abd/device_grouped_gemm_wmma_fixed_nk_bias_gelu_bf16_i8_bf16_mk_nk_mn_instance.cpp
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@@ -1,144 +0,0 @@
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
// SPDX-License-Identifier: MIT
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
#include "ck/tensor_operation/gpu/device/device_grouped_gemm_multi_abd.hpp"
#include "ck/tensor_operation/gpu/device/impl/device_grouped_gemm_multi_abd_wmma_fixed_nk.hpp"
#include "ck/tensor_operation/gpu/element/unary_element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
template <index_t... Is>
using S = Sequence<Is...>;
using BF16 = bhalf_t;
using I8 = int8_t;
using F32 = float;
using Row = tensor_layout::gemm::RowMajor;
using Col = tensor_layout::gemm::ColumnMajor;
using Multiply = element_wise::Multiply;
using PassThrough = element_wise::PassThrough;
using AddFastGelu = element_wise::AddFastGelu;
using Add = element_wise::Add;
using FastGelu = element_wise::FastGelu;
static constexpr auto GemmMNKPadding = GemmSpecialization::MNKPadding;
template <typename DsLayout,
typename DsDataType,
typename CDEElementOp,
GemmSpecialization GemmSpec>
using device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_nk_mn_instances = std::tuple<
// clang-format off
//######################################| AsLayout| BsLayout| DsLayout| ELayout| AsData| BsData| AccData| CShuffle| DsData| EData| A| B| CDE| GEMM| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MRepeat| NRepeat| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer|
//######################################| | | | | Type| Type| Type| DataType| Type| Type| Elementwise| Elementwise| Elementwise|Spacialization| Size| Block| Block| Block| | | Wmma| Wmma| | | ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MRepeat| NRepeat| _MBlock_MPerBlock_NBlock_NPerBlock| ScalarPerVector|
//######################################| | | | | | | | | | | Operation| Operation| Operation| | | | | | | | | | | | Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| | |
//######################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGroupedGemm_Wmma_Multi_ABD_Fixed_NK< Tuple<Row>, Tuple<Col, Col>, DsLayout, Row, Tuple<BF16>, Tuple<I8, BF16>, F32, BF16, DsDataType, BF16, PassThrough, Multiply, CDEElementOp, GemmSpec, 256, 128, 128, 64, 8, 8, 16, 16, 2, 4, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, 8>,
DeviceGroupedGemm_Wmma_Multi_ABD_Fixed_NK< Tuple<Row>, Tuple<Col, Col>, DsLayout, Row, Tuple<BF16>, Tuple<I8, BF16>, F32, BF16, DsDataType, BF16, PassThrough, Multiply, CDEElementOp, GemmSpec, 256, 128, 128, 64, 2, 2, 16, 16, 2, 4, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 2, 2, 1, S<8, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 2, 2, 1, 1, 1, S<1, 64, 1, 4>, 8>,
DeviceGroupedGemm_Wmma_Multi_ABD_Fixed_NK< Tuple<Row>, Tuple<Col, Col>, DsLayout, Row, Tuple<BF16>, Tuple<I8, BF16>, F32, BF16, DsDataType, BF16, PassThrough, Multiply, CDEElementOp, GemmSpec, 256, 128, 128, 32, 8, 8, 16, 16, 2, 4, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, 1, 1, S<1, 64, 1, 4>, 8>
// clang-format on
>;
void add_device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_nk_mn_bias_gelu_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmMultiABDFixedNK<Tuple<Row>,
Tuple<Col, Col>,
Tuple<Row>,
Row,
Tuple<BF16>,
Tuple<I8, BF16>,
Tuple<BF16>,
BF16,
PassThrough,
Multiply,
AddFastGelu>>>& instances)
{
add_device_operation_instances(
instances,
device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_nk_mn_instances<
Tuple<Row>,
Tuple<BF16>,
AddFastGelu,
GemmMNKPadding>{});
}
void add_device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_nk_mn_bias_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmMultiABDFixedNK<Tuple<Row>,
Tuple<Col, Col>,
Tuple<Row>,
Row,
Tuple<BF16>,
Tuple<I8, BF16>,
Tuple<BF16>,
BF16,
PassThrough,
Multiply,
Add>>>& instances)
{
add_device_operation_instances(
instances,
device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_nk_mn_instances<
Tuple<Row>,
Tuple<BF16>,
Add,
GemmMNKPadding>{});
}
void add_device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_nk_mn_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmMultiABDFixedNK<Tuple<Row>,
Tuple<Col, Col>,
Tuple<>,
Row,
Tuple<BF16>,
Tuple<I8, BF16>,
Tuple<>,
BF16,
PassThrough,
Multiply,
PassThrough>>>& instances)
{
add_device_operation_instances(
instances,
device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_nk_mn_instances<
Tuple<>,
Tuple<>,
PassThrough,
GemmMNKPadding>{});
}
void add_device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_nk_mn_gelu_instances(
std::vector<std::unique_ptr<DeviceGroupedGemmMultiABDFixedNK<Tuple<Row>,
Tuple<Col, Col>,
Tuple<>,
Row,
Tuple<BF16>,
Tuple<I8, BF16>,
Tuple<>,
BF16,
PassThrough,
Multiply,
FastGelu>>>& instances)
{
add_device_operation_instances(
instances,
device_grouped_gemm_wmma_fixed_nk_multi_abd_bf16_i8_bf16_mk_nk_mn_instances<
Tuple<>,
Tuple<>,
FastGelu,
GemmMNKPadding>{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck

10
library/src/tensor_operation_instance/gpu/grouped_gemm_fixed_nk_multi_abd/device_grouped_gemm_xdl_fixed_nk_bf16_i8_bf16_km_kn_mn_common.hpp
View File

@@ -61,8 +61,6 @@ static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecial
static constexpr auto GemmMNPadding = ck::tensor_operation::device::GemmSpecialization::MNPadding;
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
// NOTE: After adding unit tests for DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK it tuned out that
// portion of the instances are failing. As a workaround these have been commented out.
template <typename DsLayout,
typename DsDataType,
typename CDEElementOp,
@@ -74,14 +72,14 @@ using device_grouped_gemm_xdl_fixed_nk_multi_abd_bf16_i8_bf16_km_kn_mn_instances
//######################################| | | | | | | | | | | Operation| Operation| Operation| | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
//######################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 256, 128, 32, 8, 8, 32, 32, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
// DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 128, 128, 32, 8, 8, 32, 32, 2, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 128, 128, 32, 8, 8, 32, 32, 2, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 128, 64, 32, 8, 2, 32, 32, 2, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<16,16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 128, 64, 32, 8, 8, 32, 32, 2, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
// DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 64, 128, 32, 8, 2, 32, 32, 1, 2, S<4, 32, 2>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 64, 128, 32, 8, 2, 32, 32, 1, 2, S<4, 32, 2>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 64, 128, 32, 8, 8, 32, 32, 1, 2, S<4, 32, 2>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 4, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
// DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 128, 128, 64, 32, 8, 2, 32, 32, 2, 2, S<4, 32, 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, 4, 2, 0, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 128, 128, 64, 32, 8, 2, 32, 32, 2, 2, S<4, 32, 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, 4, 2, 0, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 128, 128, 64, 32, 8, 8, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
// DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 128, 64, 128, 32, 8, 2, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 128, 64, 128, 32, 8, 2, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 128, 64, 128, 32, 8, 8, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>
// clang-format on
>;

10
library/src/tensor_operation_instance/gpu/grouped_gemm_fixed_nk_multi_abd/device_grouped_gemm_xdl_fixed_nk_bf16_i8_bf16_mk_kn_mn_common.hpp
View File

@@ -61,8 +61,6 @@ static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecial
static constexpr auto GemmMNPadding = ck::tensor_operation::device::GemmSpecialization::MNPadding;
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
// NOTE: After adding unit tests for DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK it tuned out that
// portion of the instances are failing. As a workaround these have been commented out.
template <typename DsLayout,
typename DsDataType,
typename CDEElementOp,
@@ -74,14 +72,14 @@ using device_grouped_gemm_xdl_fixed_nk_multi_abd_bf16_i8_bf16_mk_kn_mn_instances
//######################################| | | | | | | | | | | Operation| Operation| Operation| | Stage| | | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | PerShuffle| PerShuffle| _NBlock_NWaveNPerXdl| _NWaveNPerXdl|
//######################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 256, 128, 32, 8, 8, 32, 32, 4, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
// DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 128, 128, 32, 8, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 128, 128, 32, 8, 8, 32, 32, 2, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 128, 64, 32, 8, 2, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<16,16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 128, 64, 32, 8, 8, 32, 32, 2, 1, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
// DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 64, 128, 32, 8, 2, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 64, 128, 32, 8, 2, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 32, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 256, 64, 128, 32, 8, 8, 32, 32, 1, 2, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 1, S<1, 32, 1, 8>, 8>,
// DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 128, 128, 64, 32, 8, 2, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 128, 128, 64, 32, 8, 2, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 32, 1, 4>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 128, 128, 64, 32, 8, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, 1, 1, 1, S<1, 32, 1, 4>, 8>,
// DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 128, 64, 128, 32, 8, 2, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 128, 64, 128, 32, 8, 2, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, 0, 1, 1, S<1, 16, 1, 8>, 8>,
DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK< AsLayout, BsLayout, DsLayout, ELayout, AsDataType, BsDataType, AccDataType, CShuffleDataType, DsDataType, EDataType, AElementOp, BElementOp, CDEElementOp, GemmSpec, 1, 128, 64, 128, 32, 8, 8, 32, 32, 2, 2, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, 1, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, 1, 1, 1, S<1, 16, 1, 8>, 8>
// clang-format on
>;

2
library/src/tensor_operation_instance/gpu/grouped_gemm_fixed_nk_multi_abd/device_grouped_gemm_xdl_fixed_nk_bf16_i8_bf16_mk_nk_mn_common.hpp
View File

@@ -61,8 +61,6 @@ static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecial
static constexpr auto GemmMNPadding = ck::tensor_operation::device::GemmSpecialization::MNPadding;
static constexpr auto GemmMNKPadding = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
// NOTE: After adding unit tests for DeviceGroupedGemm_Xdl_Multi_ABD_Fixed_NK it tuned out that
// portion of the instances are failing. As a workaround these have been commented out.
template <typename DsLayout,
typename DsDataType,
typename CDEElementOp,