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Unverified Commit 12235112 authored by rocking5566's avatar rocking5566 Committed by GitHub
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external api for gemm + layernorm (#285) 

* Extract base class for elementwise

* Refactor interface of DeviceGemmReduce. Do not use tuple in interface

* [What] Rename d into reduce in gemm + reduction related code
[Why] Prepare to add d term for add

* Unify base class of gemm + reduce and gemm + bias + add + reduce

* 1. Rename gemm_bias_add_reduce for external api
 2. Refine cmake

* Add normalize device operation

* [What] Reorder the argument
[Why] Because d0 is also the input of c.

* Add type string

* Add example of gemm_bias_add_layernorm  via external api

* Refactor example code

* clang-format

* Fix compile error

* clang-format

* Add external api for gemm_add_add_layernorm and normalize

* Add client example

* clang-format
parent aebd211c
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Showing with 852 additions and 607 deletions
include/ck/tensor_operation/gpu/grid/gridwise_gemm_reduce_xdl_cshuffle_v1.hpp
View file @ 12235112
......@@ -21,16 +21,16 @@ namespace ck {
template <typename GridwiseGemm,
typename FloatAB,
typename FloatC,
typename DPtrsGlobal,
typename ReducePtrsGlobal,
typename AElementwiseOperation,
typename BElementwiseOperation,
typename CElementwiseOperation,
typename DxsInElementwiseOperation,
typename DxsReduceAccElementwiseOperation,
typename ReduceInElementwiseOperations,
typename ReduceAccElementwiseOperations,
typename AGridDesc_AK0_M_AK1,
typename BGridDesc_BK0_N_BK1,
typename CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
typename DGridDescriptor_MBlock_MPerBlock,
typename ReduceGridDescriptor_MBlock_MPerBlock,
typename Block2CTileMap,
bool HasMainKBlockLoop>
__global__ void
......@@ -41,17 +41,17 @@ __global__ void
const FloatAB* __restrict__ p_a_grid,
const FloatAB* __restrict__ p_b_grid,
FloatC* __restrict__ p_c_grid,
DPtrsGlobal p_ds_grid,
ReducePtrsGlobal p_reduces_grid,
const AElementwiseOperation a_element_op,
const BElementwiseOperation b_element_op,
const CElementwiseOperation c_element_op,
const DxsInElementwiseOperation dxs_in_element_op,
const DxsReduceAccElementwiseOperation dxs_out_element_op,
const ReduceInElementwiseOperations reduce_in_element_ops,
const ReduceAccElementwiseOperations reduce_out_element_ops,
const AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1,
const BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1,
const CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
c_grid_desc_mblock_mperblock_nblock_nperblock,
const DGridDescriptor_MBlock_MPerBlock d_grid_desc_mblock_mperblock,
const ReduceGridDescriptor_MBlock_MPerBlock reduce_grid_desc_mblock_mperblock,
const Block2CTileMap block_2_ctile_map)
{
#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__))
......@@ -60,32 +60,32 @@ __global__ void
GridwiseGemm::template Run<HasMainKBlockLoop>(p_a_grid,
p_b_grid,
p_c_grid,
p_ds_grid,
p_reduces_grid,
p_shared,
a_element_op,
b_element_op,
c_element_op,
dxs_in_element_op,
dxs_out_element_op,
reduce_in_element_ops,
reduce_out_element_ops,
a_grid_desc_ak0_m_ak1,
b_grid_desc_bk0_n_bk1,
c_grid_desc_mblock_mperblock_nblock_nperblock,
d_grid_desc_mblock_mperblock,
reduce_grid_desc_mblock_mperblock,
block_2_ctile_map);
#else
ignore = p_a_grid;
ignore = p_b_grid;
ignore = p_c_grid;
ignore = p_ds_grid;
ignore = p_reduces_grid;
ignore = a_element_op;
ignore = b_element_op;
ignore = c_element_op;
ignore = dxs_in_element_op;
ignore = dxs_out_element_op;
ignore = reduce_in_element_ops;
ignore = reduce_out_element_ops;
ignore = a_grid_desc_ak0_m_ak1;
ignore = b_grid_desc_bk0_n_bk1;
ignore = c_grid_desc_mblock_mperblock_nblock_nperblock;
ignore = d_grid_desc_mblock_mperblock;
ignore = reduce_grid_desc_mblock_mperblock;
ignore = block_2_ctile_map;
#endif // end of if (defined(__gfx908__) || defined(__gfx90a__))
}
......@@ -95,19 +95,19 @@ template <typename FloatAB,
typename FloatCShuffle,
typename FloatC,
typename FloatReduceAcc,
typename DPtrsGlobal,
typename ReducePtrsGlobal,
typename AElementwiseOperation,
typename BElementwiseOperation,
typename CElementwiseOperation,
typename DxsReduceOperation,
typename DxsInElementwiseOperation,
typename DxsReduceAccElementwiseOperation,
typename ReduceOperations,
typename ReduceInElementwiseOperations,
typename ReduceAccElementwiseOperations,
InMemoryDataOperationEnum CGlobalMemoryDataOperation,
typename DGlobalMemoryDataOperation,
typename ReduceGlobalMemoryDataOperation,
typename AGridDesc_AK0_M_AK1,
typename BGridDesc_BK0_N_BK1,
typename CGridDesc_M_N,
typename DGridDesc_M,
typename ReduceGridDesc_M,
index_t NumGemmKPrefetchStage,
index_t BlockSize,
index_t MPerBlock,
......@@ -293,18 +293,18 @@ struct GridwiseGemmReduce_k0mk1_k0nk1_mn_xdl_cshuffle_v1
}
__host__ __device__ static constexpr auto
MakeDGridDescriptor_MBlock_MPerBlock(const DGridDesc_M& d_grid_desc_m)
MakeReduceGridDescriptor_MBlock_MPerBlock(const ReduceGridDesc_M& d_grid_desc_m)
{
const auto M = d_grid_desc_m.GetLength(I0);
const auto MBlock = M / MPerBlock;
const auto d_grid_desc_mblock_mperblock = transform_tensor_descriptor(
const auto reduce_grid_desc_mblock_mperblock = transform_tensor_descriptor(
d_grid_desc_m,
make_tuple(make_unmerge_transform(make_tuple(MBlock, Number<MPerBlock>{}))),
make_tuple(Sequence<0>{}),
make_tuple(Sequence<0, 1>{}));
return d_grid_desc_mblock_mperblock;
return reduce_grid_desc_mblock_mperblock;
}
// return block_id to C matrix tile idx (m0, n0) mapping
......@@ -318,29 +318,30 @@ struct GridwiseGemmReduce_k0mk1_k0nk1_mn_xdl_cshuffle_v1
using CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock = remove_cvref_t<decltype(
MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(CGridDesc_M_N{}))>;
using DGridDescriptor_MBlock_MPerBlock =
remove_cvref_t<decltype(MakeDGridDescriptor_MBlock_MPerBlock(DGridDesc_M{}))>;
using ReduceGridDescriptor_MBlock_MPerBlock =
remove_cvref_t<decltype(MakeReduceGridDescriptor_MBlock_MPerBlock(ReduceGridDesc_M{}))>;
using DefaultBlock2CTileMap =
remove_cvref_t<decltype(MakeDefaultBlock2CTileMap(CGridDesc_M_N{}))>;
template <bool HasMainKBlockLoop, typename Block2CTileMap>
__device__ static void Run(const FloatAB* __restrict__ p_a_grid,
const FloatAB* __restrict__ p_b_grid,
FloatC* __restrict__ p_c_grid,
DPtrsGlobal p_ds_grid,
void* __restrict__ p_shared,
const AElementwiseOperation& a_element_op,
const BElementwiseOperation& b_element_op,
const CElementwiseOperation& c_element_op,
const DxsInElementwiseOperation& dxs_in_element_op,
const DxsReduceAccElementwiseOperation& dxs_out_element_op,
const AGridDesc_AK0_M_AK1& a_grid_desc_ak0_m_ak1,
const BGridDesc_BK0_N_BK1& b_grid_desc_bk0_n_bk1,
const CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock&
c_grid_desc_mblock_mperblock_nblock_nperblock,
const DGridDescriptor_MBlock_MPerBlock& d_grid_desc_mblock_mperblock,
const Block2CTileMap& block_2_ctile_map)
__device__ static void
Run(const FloatAB* __restrict__ p_a_grid,
const FloatAB* __restrict__ p_b_grid,
FloatC* __restrict__ p_c_grid,
ReducePtrsGlobal p_reduces_grid,
void* __restrict__ p_shared,
const AElementwiseOperation& a_element_op,
const BElementwiseOperation& b_element_op,
const CElementwiseOperation& c_element_op,
const ReduceInElementwiseOperations& reduce_in_element_ops,
const ReduceAccElementwiseOperations& reduce_out_element_ops,
const AGridDesc_AK0_M_AK1& a_grid_desc_ak0_m_ak1,
const BGridDesc_BK0_N_BK1& b_grid_desc_bk0_n_bk1,
const CGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock&
c_grid_desc_mblock_mperblock_nblock_nperblock,
const ReduceGridDescriptor_MBlock_MPerBlock& reduce_grid_desc_mblock_mperblock,
const Block2CTileMap& block_2_ctile_map)
{
const auto a_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
p_a_grid, a_grid_desc_ak0_m_ak1.GetElementSpaceSize());
......@@ -706,12 +707,12 @@ struct GridwiseGemmReduce_k0mk1_k0nk1_mn_xdl_cshuffle_v1
make_naive_tensor_descriptor_packed(
make_tuple(Number<mreduce_per_thread>{}, Number<nreduce_per_thread>{}));
// VGPR d_reduce_thread_desc_mperblock
constexpr auto d_reduce_thread_desc_mperblock =
// VGPR reduce_thread_desc_mperblock
constexpr auto reduce_thread_desc_mperblock =
make_naive_tensor_descriptor_packed(make_tuple(Number<mreduce_per_thread>{}));
// VGPR d_reduce_thread_desc_mblock_mperblock
constexpr auto d_reduce_thread_desc_mblock_mperblock =
// VGPR reduce_thread_desc_mblock_mperblock
constexpr auto reduce_thread_desc_mblock_mperblock =
make_naive_tensor_descriptor_packed(make_tuple(I1, Number<mreduce_per_thread>{}));
auto c_reduce_thread_buf = make_static_buffer<AddressSpaceEnum::Vgpr, FloatReduceAcc>(
......@@ -740,29 +741,29 @@ struct GridwiseGemmReduce_k0mk1_k0nk1_mn_xdl_cshuffle_v1
1,
true>{c_reduce_block_desc_mperblock_nperblock, c_reduce_thread_data_idx_begin};
auto dxs_reduce_thread_copy_vgpr_to_global = generate_tuple(
auto reduce_tuple_thread_copy_vgpr_to_global = generate_tuple(
[&](auto I) {
auto p_d_grid = p_ds_grid[I];
auto d_out_element_op = dxs_out_element_op[I];
auto p_reduce_grid = p_reduces_grid[I];
auto reduce_acc_element_op = reduce_out_element_ops[I];
return ThreadwiseTensorSliceTransfer_v1r3<
FloatReduceAcc,
remove_pointer_t<decltype(p_d_grid)>,
decltype(d_reduce_thread_desc_mblock_mperblock),
decltype(d_grid_desc_mblock_mperblock),
decltype(d_out_element_op),
remove_pointer_t<decltype(p_reduce_grid)>,
decltype(reduce_thread_desc_mblock_mperblock),
decltype(reduce_grid_desc_mblock_mperblock),
decltype(reduce_acc_element_op),
Sequence<1, mreduce_per_thread>,
Sequence<0, 1>,
1,
CReduceThreadVgpr2GlobalCopySrcDstScalarPerVector_MPerBlock,
DGlobalMemoryDataOperation::At(I),
ReduceGlobalMemoryDataOperation::At(I),
1,
false>{d_grid_desc_mblock_mperblock,
false>{reduce_grid_desc_mblock_mperblock,
make_multi_index(block_work_idx[I0], // mblock
c_reduce_thread_data_idx_begin[I0]), // mperblock
d_out_element_op};
reduce_acc_element_op};
},
Number<p_ds_grid.Size()>{});
Number<p_reduces_grid.Size()>{});
constexpr index_t num_access = sfc_c_vgpr.GetNumOfAccess();
......@@ -797,35 +798,35 @@ struct GridwiseGemmReduce_k0mk1_k0nk1_mn_xdl_cshuffle_v1
make_tuple(I0, I0),
c_reduce_thread_buf);
static_for<0, p_ds_grid.Size(), 1>{}([&](auto In) {
auto& p_d_grid = p_ds_grid[In];
static_for<0, p_reduces_grid.Size(), 1>{}([&](auto In) {
auto& p_reduce_grid = p_reduces_grid[In];
auto d_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
p_d_grid, d_grid_desc_mblock_mperblock.GetElementSpaceSize());
auto reduce_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
p_reduce_grid, reduce_grid_desc_mblock_mperblock.GetElementSpaceSize());
auto d_thread_buf =
auto reduce_thread_buf =
make_static_buffer<AddressSpaceEnum::Vgpr, FloatReduceAcc>(
d_reduce_thread_desc_mperblock.GetElementSpaceSize());
reduce_thread_desc_mperblock.GetElementSpaceSize());
auto& d_in_element_op = dxs_in_element_op[In];
auto& reduce_in_element_op = reduce_in_element_ops[In];
auto& d_reduce_thread_copy_vgpr_to_global =
dxs_reduce_thread_copy_vgpr_to_global(In);
auto& reduce_thread_copy_vgpr_to_global =
reduce_tuple_thread_copy_vgpr_to_global(In);
using DReduceOperation = remove_cvref_t<decltype(DxsReduceOperation{}[In])>;
using ReduceOperation = remove_cvref_t<decltype(ReduceOperations{}[In])>;
using ThreadwiseReduce =
ThreadwiseReduction<FloatReduceAcc,
decltype(c_reduce_thread_desc_mperblock_nperblock),
decltype(d_reduce_thread_desc_mperblock),
DReduceOperation,
decltype(reduce_thread_desc_mperblock),
ReduceOperation,
false>;
// Global write Gemm shuffle + reduction
const auto d_identityVal =
DReduceOperation::template GetIdentityValue<FloatReduceAcc>();
const auto reduce_identityVal =
ReduceOperation::template GetIdentityValue<FloatReduceAcc>();
static_for<0, mreduce_per_thread, 1>{}(
[&](auto I) { d_thread_buf(I) = d_identityVal; });
[&](auto I) { reduce_thread_buf(I) = reduce_identityVal; });
// reduce in VGPR
static_for<0, mreduce_per_thread, 1>{}([&](auto im) {
......@@ -834,26 +835,25 @@ struct GridwiseGemmReduce_k0mk1_k0nk1_mn_xdl_cshuffle_v1
Number<c_reduce_thread_desc_mperblock_nperblock.CalculateOffset(
make_tuple(im, in))>{};
d_in_element_op(c_reduce_thread_buf(offset),
c_reduce_thread_buf(offset));
reduce_in_element_op(c_reduce_thread_buf(offset),
c_reduce_thread_buf(offset));
});
});
ThreadwiseReduce::Reduce(c_reduce_thread_buf, d_thread_buf);
ThreadwiseReduce::Reduce(c_reduce_thread_buf, reduce_thread_buf);
// copy from VGPR to Global
d_reduce_thread_copy_vgpr_to_global.Run(
d_reduce_thread_desc_mblock_mperblock,
make_tuple(I0, I0),
d_thread_buf,
d_grid_desc_mblock_mperblock,
d_grid_buf);
reduce_thread_copy_vgpr_to_global.Run(reduce_thread_desc_mblock_mperblock,
make_tuple(I0, I0),
reduce_thread_buf,
reduce_grid_desc_mblock_mperblock,
reduce_grid_buf);
if constexpr(access_id < num_access - 1)
{
constexpr auto c_global_step = sfc_c_global.GetForwardStep(access_id);
d_reduce_thread_copy_vgpr_to_global.MoveDstSliceWindow(
d_grid_desc_mblock_mperblock,
reduce_thread_copy_vgpr_to_global.MoveDstSliceWindow(
reduce_grid_desc_mblock_mperblock,
make_tuple(c_global_step[I0], c_global_step[I1]));
}
});
......
library/include/ck/library/tensor_operation_instance/gpu/device_elementwise_instance.hpp 0 → 100644
View file @ 12235112
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_elementwise.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
using Normalize = ck::tensor_operation::element_wise::Normalize;
using DeviceNormalizeFromMeanMeanSquarePtr =
ck::tensor_operation::device::DeviceElementwisePtr<5, 1, 2, Normalize>;
void add_device_normalize_from_mean_squaremean_f16_f32_f32_f16_f16_instances(
std::vector<DeviceNormalizeFromMeanMeanSquarePtr>& instances);
template <typename InputType,
typename MeanType,
typename MeanSquareType,
typename GammaDataType,
typename BetaDataType,
typename OutputType>
auto get_device_normalize_from_mean_meansquare_instances()
{
std::vector<DeviceNormalizeFromMeanMeanSquarePtr> op_ptrs;
if constexpr(is_same<InputType, half_t>::value && is_same<MeanType, float>::value &&
is_same<MeanSquareType, float>::value && is_same<GammaDataType, half_t>::value &&
is_same<BetaDataType, half_t>::value && is_same<OutputType, half_t>::value)
{
ck::tensor_operation::device::
add_device_normalize_from_mean_squaremean_f16_f32_f32_f16_f16_instances(op_ptrs);
}
return op_ptrs;
}
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/include/ck/library/tensor_operation_instance/gpu/device_gemm_mean_squaremean_instance.hpp 0 → 100644
View file @ 12235112
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_gemm_reduce.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_gemm_instance {
using DeviceGemmAddAddMeanSquareMeanPtr = ck::tensor_operation::device::DeviceGemmReducePtr<1, 2>;
void add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_mk_kn_mn_instances(
std::vector<DeviceGemmAddAddMeanSquareMeanPtr>&);
void add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_mk_nk_mn_instances(
std::vector<DeviceGemmAddAddMeanSquareMeanPtr>&);
void add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_km_kn_mn_instances(
std::vector<DeviceGemmAddAddMeanSquareMeanPtr>&);
void add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_km_nk_mn_instances(
std::vector<DeviceGemmAddAddMeanSquareMeanPtr>&);
template <typename ADataType,
typename BDataType,
typename CDataType,
typename ALayout,
typename BLayout,
typename CLayout>
auto get_device_gemm_add_add_mean_squaremean_instances()
{
std::vector<DeviceGemmAddAddMeanSquareMeanPtr> op_ptrs;
if constexpr(is_same<ADataType, half_t>::value && is_same<BDataType, half_t>::value &&
is_same<CDataType, half_t>::value)
{
if constexpr(is_same<ALayout, tensor_layout::gemm::RowMajor>::value &&
is_same<BLayout, tensor_layout::gemm::RowMajor>::value &&
is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
{
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_mk_kn_mn_instances(
op_ptrs);
}
else if constexpr(is_same<ALayout, tensor_layout::gemm::RowMajor>::value &&
is_same<BLayout, tensor_layout::gemm::ColumnMajor>::value &&
is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
{
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_mk_nk_mn_instances(
op_ptrs);
}
else if constexpr(is_same<ALayout, tensor_layout::gemm::ColumnMajor>::value &&
is_same<BLayout, tensor_layout::gemm::RowMajor>::value &&
is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
{
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_km_kn_mn_instances(
op_ptrs);
}
else if constexpr(is_same<ALayout, tensor_layout::gemm::ColumnMajor>::value &&
is_same<BLayout, tensor_layout::gemm::ColumnMajor>::value &&
is_same<CLayout, tensor_layout::gemm::RowMajor>::value)
{
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_km_nk_mn_instances(
op_ptrs);
}
}
return op_ptrs;
}
} // namespace device_gemm_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/CMakeLists.txt
View file @ 12235112
......@@ -5,6 +5,7 @@ function(add_instance_library INSTANCE_NAME)
set_target_properties(${INSTANCE_NAME} PROPERTIES POSITION_INDEPENDENT_CODE ON)
endfunction(add_instance_library INSTANCE_NAME)
add_subdirectory(elementwise)
add_subdirectory(gemm)
add_subdirectory(gemm_splitk)
add_subdirectory(gemm_bias2d)
......@@ -31,6 +32,7 @@ add_library(device_operations STATIC
$<TARGET_OBJECTS:device_gemm_splitk_instance>
$<TARGET_OBJECTS:device_gemm_bias_relu_instance>
$<TARGET_OBJECTS:device_gemm_bias_relu_add_instance>
$<TARGET_OBJECTS:device_gemm_bias_add_reduce_instance>
$<TARGET_OBJECTS:device_gemm_bias2d_instance>
$<TARGET_OBJECTS:device_gemm_add_add_fastgelu_instance>
$<TARGET_OBJECTS:device_batched_gemm_instance>
......@@ -44,6 +46,8 @@ add_library(device_operations STATIC
$<TARGET_OBJECTS:device_conv2d_bwd_data_instance>
$<TARGET_OBJECTS:device_convnd_bwd_data_instance>
$<TARGET_OBJECTS:device_conv2d_bwd_weight_instance>
$<TARGET_OBJECTS:device_elementwise_instance>
$<TARGET_OBJECTS:device_gemm_add_add_fastgelu_instance>
$<TARGET_OBJECTS:device_reduce_instance>
)
add_library(composablekernels::device_operations ALIAS device_operations)
......
library/src/tensor_operation_instance/gpu/elementwise/CMakeLists.txt 0 → 100644
View file @ 12235112
set(DEVICE_ELEMENTWISE_INSTANCE_SOURCE
device_normalize_instance.cpp
)
add_instance_library(device_elementwise_instance ${DEVICE_ELEMENTWISE_INSTANCE_SOURCE})
target_compile_features(device_elementwise_instance PUBLIC)
set_target_properties(device_elementwise_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
clang_tidy_check(device_elementwise_instance)
library/src/tensor_operation_instance/gpu/elementwise/device_normalize_instance.cpp 0 → 100644
View file @ 12235112
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, 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/device_5ary_elementwise.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
using F16 = ck::half_t;
using F32 = float;
using inputType = F16;
using MeanType = F32;
using SquareMeanType = F32;
using GammaDataType = F16;
using BetaDataType = F16;
using outputType = F16;
using Normalize = ck::tensor_operation::element_wise::Normalize;
using device_normalize_from_mean_squaremean_f16_f32_f32_f16_f16_instances = std::tuple<
// clang-format off
//###################|in | mean| square_mean| gamma| beta| out| ComputeDataType| functor| NDim| MPerThread| in, mean, square_mean, gamma, beta, out ScalarPerVector|
//###################|in | mean| square_mean| gamma| beta| out| ComputeDataType| functor| NDim| MPerThread| in, mean, square_mean, gamma, beta, out ScalarPerVector|
//###################|in | mean| square_mean| gamma| beta| out| ComputeDataType| functor| NDim| MPerThread| in, mean, square_mean, gamma, beta, out ScalarPerVector|
//###################|in | mean| square_mean| gamma| beta| out| ComputeDataType| functor| NDim| MPerThread| in, mean, square_mean, gamma, beta, out ScalarPerVector|
Device5AryElementwise<F16, F32, F32, F16, F16, F16, F32, Normalize, 2, 8, 8, 1, 1, 8, 8, 8 >,
Device5AryElementwise<F16, F32, F32, F16, F16, F16, F32, Normalize, 2, 4, 4, 1, 1, 4, 4, 4 >,
Device5AryElementwise<F16, F32, F32, F16, F16, F16, F32, Normalize, 2, 2, 2, 1, 1, 2, 2, 2 >,
Device5AryElementwise<F16, F32, F32, F16, F16, F16, F32, Normalize, 2, 1, 1, 1, 1, 1, 1, 1 >
// clang-format on
>;
void add_device_normalize_from_mean_squaremean_f16_f32_f32_f16_f16_instances(
std::vector<DeviceElementwisePtr<5, 1, 2, Normalize>>& instances)
{
add_device_operation_instances(
instances, device_normalize_from_mean_squaremean_f16_f32_f32_f16_f16_instances{});
}
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_bias_add_reduce/CMakeLists.txt
View file @ 12235112
set(DEVICE_GEMM_REDUCE_INSTANCE_SOURCE
device_gemm_bias_add_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_mk_kn_mn_instance.cpp
device_gemm_bias_add_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_mk_nk_mn_instance.cpp
device_gemm_bias_add_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_km_kn_mn_instance.cpp
device_gemm_bias_add_reduce_xdl_cshuffle_f16_f16_f16_f32_f32_km_nk_mn_instance.cpp
set(DEVICE_GEMM_BIAS_ADD_REDUCE_INSTANCE_SOURCE
device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f32_f32_mk_kn_mn_instance.cpp
device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f32_f32_mk_nk_mn_instance.cpp
device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f32_f32_km_kn_mn_instance.cpp
device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f32_f32_km_nk_mn_instance.cpp
)
add_instance_library(device_gemm_bias_add_reduce_instance ${DEVICE_GEMM_REDUCE_INSTANCE_SOURCE})
rocm_install(TARGETS device_gemm_bias_add_reduce_instance)
add_library(device_gemm_bias_add_reduce_instance OBJECT ${DEVICE_GEMM_BIAS_ADD_REDUCE_INSTANCE_SOURCE})
target_compile_features(device_gemm_bias_add_reduce_instance PUBLIC)
set_target_properties(device_gemm_bias_add_reduce_instance PROPERTIES POSITION_INDEPENDENT_CODE ON)
clang_tidy_check(device_gemm_bias_add_reduce_instance)
library/src/tensor_operation_instance/gpu/gemm_bias_add_reduce/device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f32_f32_km_kn_mn_instance.cpp 0 → 100644
View file @ 12235112
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/utility/reduction_operator.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_gemm_bias_add_reduce_xdl_cshuffle.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_gemm_instance {
using F16 = ck::half_t;
using F32 = float;
using ReducePtrsGlobal = ck::Tuple<F32*, F32*>;
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;
using ReduceSum = ck::reduce::Add;
using ReduceOps = ck::Tuple<ReduceSum, ReduceSum>;
using Div = ck::tensor_operation::element_wise::UnaryDivide;
using Identity = ck::tensor_operation::element_wise::PassThrough;
using Square = ck::tensor_operation::element_wise::UnarySquare;
using ReduceInElementOps = ck::Tuple<Identity, Square>;
using ReduceOutElementOps = ck::Tuple<Div, Div>;
using ReduceMemOp = ck::InMemoryDataOperationEnumSequence<ck::InMemoryDataOperationEnum::AtomicAdd,
ck::InMemoryDataOperationEnum::AtomicAdd>;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// c[m, n] = a[k, m] * b[k, n]
using device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_km_kn_mn_instances =
std::tuple<
// clang-format off
//##################################| ALayout| BLayout| CLayout|AData| BData| CData|C0Data|C1Data| GemmAcc| CShuffle| ReduceAcc| ReduceData| A| B| C| C1| Reduce| ReduceInEleOp| ReduceAccEleOp| Reduce| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer| CReduce| CReduceThreadLds2VGprCopy| CReduceThreadVgpr2GlobalCopy|
//##################################| | | | Type| Type| Type| Type| Type| DataType| DataType| DataType| Type Tuple| Elementwise| Elementwise| Elementwise| Elementwise| Operation| | | MemoryData|Spacialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MPerBlock| ScalarPerVector| ThreadClusterLengths| SrcDstScalarPerVector| SrcDstScalarPerVector|
//##################################| | | | | | | | | | | | | Operation| Operation| 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_NPerBlock| _NPerBlock| _MPerBlock_NPerBlock| _NPerBlock| _MPerBlock|
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 256, 128, 32, 2, 2, 32, 32, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 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, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 128, 256, 32, 2, 2, 32, 32, 2, 4, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 128, 256, 32, 8, 8, 32, 32, 2, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 128, 128, 128, 32, 2, 2, 32, 32, 4, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 1, S<1, 16, 1, 8>, 8, S<32, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 128, 128, 128, 32, 8, 8, 32, 32, 4, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8, S<32, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 128, 128, 32, 2, 2, 32, 32, 2, 2, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 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, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 128, 128, 64, 32, 2, 2, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<4, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 1, S<1, 32, 1, 4>, 8, S<64, 2>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 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, true, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, 1, 1, S<1, 32, 1, 4>, 8, S<64, 2>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 128, 64, 128, 32, 2, 2, 32, 32, 2, 2, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 1, S<1, 16, 1, 8>, 8, S<32, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 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, true, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, 1, 1, S<1, 16, 1, 8>, 8, S<32, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 128, 64, 32, 2, 2, 32, 32, 2, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<16,16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 1, S<1, 16, 1, 4>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 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, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, true, 1, 1, S<1, 16, 1, 4>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 64, 128, 32, 2, 2, 32, 32, 1, 2, S<16,16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Row, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 64, 128, 32, 8, 8, 32, 32, 1, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, true, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>
// clang-format on
>;
void add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_km_kn_mn_instances(
std::vector<DeviceGemmReducePtr<1, ReduceOps::Size()>>& instances)
{
add_device_operation_instances(
instances,
device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_km_kn_mn_instances{});
}
} // namespace device_gemm_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/gemm_bias_add_reduce/device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f32_f32_km_nk_mn_instance.cpp 0 → 100644
View file @ 12235112
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/utility/reduction_operator.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_gemm_bias_add_reduce_xdl_cshuffle.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_gemm_instance {
using F16 = ck::half_t;
using F32 = float;
using ReducePtrsGlobal = ck::Tuple<F32*, F32*>;
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;
using ReduceSum = ck::reduce::Add;
using ReduceOps = ck::Tuple<ReduceSum, ReduceSum>;
using Div = ck::tensor_operation::element_wise::UnaryDivide;
using Identity = ck::tensor_operation::element_wise::PassThrough;
using Square = ck::tensor_operation::element_wise::UnarySquare;
using ReduceInElementOps = ck::Tuple<Identity, Square>;
using ReduceOutElementOps = ck::Tuple<Div, Div>;
using ReduceMemOp = ck::InMemoryDataOperationEnumSequence<ck::InMemoryDataOperationEnum::AtomicAdd,
ck::InMemoryDataOperationEnum::AtomicAdd>;
static constexpr auto GemmDefault = ck::tensor_operation::device::GemmSpecialization::Default;
// c[m, n] = a[k, m] * b[n, k]
using device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_km_nk_mn_instances =
std::tuple<
// clang-format off
//##################################| ALayout| BLayout| CLayout|AData| BData| CData|C0Data|C1Data| GemmAcc| CShuffle| ReduceAcc| ReduceData| A| B| C| C1| Reduce| ReduceInEleOp| ReduceAccEleOp| Reduce| GEMM| NumGemmK| Block| MPer| NPer| KPer| AK1| BK1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CShuffle| CShuffle| CBlockTransferClusterLengths| CBlockTransfer| CReduce| CReduceThreadLds2VGprCopy| CReduceThreadVgpr2GlobalCopy|
//##################################| | | | Type| Type| Type| Type| Type| DataType| DataType| DataType| Type Tuple| Elementwise| Elementwise| Elementwise| Elementwise| Operation| | | MemoryData|Spacialization| Prefetch| Size| Block| Block| Block| | | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| MXdlPerWave| NXdlPerWave| _MBlock_MPerBlock| ScalarPerVector| ThreadClusterLengths| SrcDstScalarPerVector| SrcDstScalarPerVector|
//##################################| | | | | | | | | | | | | Operation| Operation| 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_NPerBlock| _NPerBlock| _MPerBlock_NPerBlock| _NPerBlock| _MPerBlock|
//##################################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 256, 128, 32, 2, 8, 32, 32, 4, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 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, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 128, 256, 32, 2, 8, 32, 32, 2, 4, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 128, 256, 32, 8, 8, 32, 32, 2, 4, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 2, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 128, 128, 128, 32, 2, 8, 32, 32, 4, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 16, 1, 8>, 8, S<32, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 128, 128, 128, 32, 8, 8, 32, 32, 4, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 8, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 16, 1, 8>, 8, S<32, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 128, 128, 32, 2, 8, 32, 32, 2, 2, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 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, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 128, 128, 64, 32, 2, 8, 32, 32, 2, 2, S<4, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 4>, 8, S<64, 2>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 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, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 4>, 8, S<64, 2>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 128, 64, 128, 32, 2, 8, 32, 32, 2, 2, S<8, 16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 16, 1, 8>, 8, S<32, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 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, true, S<4, 32, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 16, 1, 8>, 8, S<32, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 128, 64, 32, 2, 8, 32, 32, 2, 1, S<8, 32, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 16, 1, 4>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 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, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 16, 1, 4>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 64, 128, 32, 2, 8, 32, 32, 1, 2, S<16,16, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 4, 2, false, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>,
DeviceGemmBiasAddReduce_Xdl_CShuffle< Col, Col, Row, F16, F16, F16, F16, F16, F32, F32, F32, ReducePtrsGlobal, PassThrough, PassThrough, PassThrough, PassThrough, ReduceOps, ReduceInElementOps, ReduceOutElementOps, ReduceMemOp, GemmDefault, 1, 256, 64, 128, 32, 8, 8, 32, 32, 1, 2, S<4, 64, 1>, S<0, 2, 1>, S<0, 2, 1>, 1, 1, 8, true, S<4, 64, 1>, S<1, 0, 2>, S<1, 0, 2>, 2, 8, 8, true, 1, 1, S<1, 32, 1, 8>, 8, S<64, 4>, 4, 1>
// clang-format on
>;
void add_device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_km_nk_mn_instances(
std::vector<DeviceGemmReducePtr<1, ReduceOps::Size()>>& instances)
{
add_device_operation_instances(
instances,
device_gemm_bias_add_mean_squaremean_xdl_cshuffle_f16_f16_f16_f16_f16_f32_f32_km_nk_mn_instances{});
}
} // namespace device_gemm_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
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