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Unverified Commit 4be7f019 authored by ltqin's avatar ltqin Committed by GitHub
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add split-k GEMM (#59) 



* add DeviceGemmSplitKXdl

* add file device_gemm_splitk_xdl.hpp

* set c matrix zero

* using atomic

* add all tuning parameter to f32 mkkn

* grid size change to 720

* add tunning parameter for NT

* add tunning parameter for TN

* add tunning parameter for TT

* add m=96tunning parameter

* add lost config

* add element wise operation

* fixed MPerBlock=96

* remove marco for slpitk swtich

* add test

* add new line at the end of device_gemm_xdl_instance.hpp

* remove step hack

* seperate split-k instance files

* add tunning parameters

* change disired grid size to parameters

* remove slice length

* add desiredgridsize parameter to ckProfiler

* add losting file device_gemm_xdl_splitk_instance.hpp

* change desired gride size to kbatch

* format

* format

* clean up

* add selection of device_instances

* clean code

* fix build issue
Co-authored-by: default avatarltqin <letaoqin@amd.com>
Co-authored-by: default avatarChao Liu <chao.liu2@amd.com>
Co-authored-by: default avatarJing Zhang <jizhan@amd.com>
parent ca47a6cf
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Showing with 1057 additions and 277 deletions
composable_kernel/include/tensor_operation/gridwise_gemm_xdlops_v2r4.hpp
View file @ 4be7f019
......@@ -62,7 +62,10 @@ template <typename GridwiseGemm,
typename ABK0MK1GridDesc,
typename BBK0NK1GridDesc,
typename CM0N0M1N1M2M3M4N2GridDesc,
typename CBlockClusterAdaptor,
typename AElementwiseOperation,
typename BElementwiseOperation,
typename CElementwiseOperation,
typename Block2CTileMap,
bool HasMainKBlockLoop>
__global__ void
#if CK_USE_LAUNCH_BOUNDS
......@@ -74,7 +77,10 @@ __global__ void
const void CONSTANT* p_a_b_k0_m_k1_grid_desc,
const void CONSTANT* p_b_b_k0_n_k1_grid_desc,
const void CONSTANT* p_c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
const void CONSTANT* p_c_block_cluster_adaptor)
const void CONSTANT* p_a_element_op,
const void CONSTANT* p_b_element_op,
const void CONSTANT* p_c_element_op,
const void CONSTANT* p_block_2_ctile_map)
{
constexpr index_t shared_block_size =
GridwiseGemm::GetSharedMemoryNumberOfByte() / sizeof(FloatAB);
......@@ -86,8 +92,14 @@ __global__ void
const auto c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc =
*reinterpret_cast<const CM0N0M1N1M2M3M4N2GridDesc*>(
cast_pointer_to_generic_address_space(p_c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc));
const auto c_block_cluster_adaptor = *reinterpret_cast<const CBlockClusterAdaptor*>(
cast_pointer_to_generic_address_space(p_c_block_cluster_adaptor));
const auto block_2_ctile_map = *reinterpret_cast<const Block2CTileMap*>(
cast_pointer_to_generic_address_space(p_block_2_ctile_map));
const auto a_element_op = *reinterpret_cast<const AElementwiseOperation*>(
cast_pointer_to_generic_address_space(p_a_element_op));
const auto b_element_op = *reinterpret_cast<const BElementwiseOperation*>(
cast_pointer_to_generic_address_space(p_b_element_op));
const auto c_element_op = *reinterpret_cast<const CElementwiseOperation*>(
cast_pointer_to_generic_address_space(p_c_element_op));
__shared__ FloatAB p_shared_block[shared_block_size];
......@@ -98,7 +110,10 @@ __global__ void
a_b_k0_m_k1_grid_desc,
b_b_k0_n_k1_grid_desc,
c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
c_block_cluster_adaptor);
a_element_op,
b_element_op,
c_element_op,
block_2_ctile_map);
}
#endif
......@@ -110,6 +125,9 @@ template <index_t BlockSize,
typename ABK0MK1GridDesc,
typename BBK0NK1GridDesc,
typename CMNGridDesc,
typename AElementwiseOperation,
typename BElementwiseOperation,
typename CElementwiseOperation,
index_t MPerBlock,
index_t NPerBlock,
index_t K0PerBlock,
......@@ -118,7 +136,6 @@ template <index_t BlockSize,
index_t K1Value,
index_t MRepeat,
index_t NRepeat,
typename ABlockTransferThreadSliceLengths_K0_M_K1,
typename ABlockTransferThreadClusterLengths_K0_M_K1,
typename ABlockTransferThreadClusterArrangeOrder,
typename ABlockTransferSrcAccessOrder,
......@@ -126,7 +143,7 @@ template <index_t BlockSize,
index_t ABlockTransferSrcScalarPerVector,
index_t ABlockTransferDstScalarPerVector_K1,
bool AThreadTransferSrcResetCoordinateAfterRun,
typename BBlockTransferThreadSliceLengths_K0_N_K1,
bool ABlockLdsExtraM,
typename BBlockTransferThreadClusterLengths_K0_N_K1,
typename BBlockTransferThreadClusterArrangeOrder,
typename BBlockTransferSrcAccessOrder,
......@@ -134,12 +151,10 @@ template <index_t BlockSize,
index_t BBlockTransferSrcScalarPerVector,
index_t BBlockTransferDstScalarPerVector_K1,
bool BThreadTransferSrcResetCoordinateAfterRun,
bool BBlockLdsExtraN,
typename CThreadTransferSrcDstAccessOrder,
index_t CThreadTransferSrcDstVectorDim,
index_t CThreadTransferDstScalarPerVector,
bool CAccessOrderMRepeatNRepeat,
bool ABlockLdsExtraM,
bool BBlockLdsExtraN>
index_t CThreadTransferDstScalarPerVector>
struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4
{
static constexpr auto I0 = Number<0>{};
......@@ -358,6 +373,9 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4
const ABK0MK1GridDesc& a_b_k0_m_k1_grid_desc,
const BBK0NK1GridDesc& b_b_k0_n_k1_grid_desc,
const CM0N0M1N1M2M3M4N2GridDesc& c_m0_n0_m1_n1_m2_m3_m4_n2_grid_desc,
const AElementwiseOperation& a_element_op,
const BElementwiseOperation& b_element_op,
const CElementwiseOperation& c_element_op,
const CBlockClusterAdaptor& c_block_cluster_adaptor)
{
const auto a_grid_buf = make_dynamic_buffer<AddressSpaceEnum_t::Global>(
......@@ -456,7 +474,6 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4
ck::tensor_operation::element_wise::PassThrough,
InMemoryDataOperationEnum_t::Set,
Sequence<1, K0PerBlock, MPerBlock, K1>,
ABlockTransferThreadSliceLengths_K0_M_K1,
ABlockTransferThreadClusterLengths_K0_M_K1,
ABlockTransferThreadClusterArrangeOrder,
FloatAB,
......@@ -487,7 +504,6 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4
ck::tensor_operation::element_wise::PassThrough,
InMemoryDataOperationEnum_t::Set,
Sequence<1, K0PerBlock, NPerBlock, K1>,
BBlockTransferThreadSliceLengths_K0_N_K1,
BBlockTransferThreadClusterLengths_K0_N_K1,
BBlockTransferThreadClusterArrangeOrder,
FloatAB,
......@@ -583,8 +599,8 @@ struct GridwiseGemm_bk0mk1_bk0nk1_mn_xdlops_v2r4
a_blockwise_copy.RunWrite(a_b_k0_m_k1_block_desc, a_block_buf);
b_blockwise_copy.RunWrite(b_b_k0_n_k1_block_desc, b_block_buf);
k_block_data_begin += K0PerBlock;
} while(k_block_data_begin < (K0 - K0PerBlock));
k0_block_data_begin += K0PerBlock;
} while(k0_block_data_begin < (K0 - K0PerBlock));
}
// tail
......
device_operation/device_gemm_xdl_instance_f16_f16_f16_km_kn_mn.cpp → device_operation/device_gemm_xdl_f16_f16_f16_km_kn_mn_instance.cpp
View file @ 4be7f019
#include <stdlib.h>
#include "config.hpp"
#include "device_gemm_xdl.hpp"
#include "device_gemm_instance.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......@@ -21,7 +21,7 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[k, m] * b[k, n] = c[m, n]
using device_gemm_xdl_instance_f16_f16_f16_km_kn_mn =
using device_gemm_xdl_f16_f16_f16_km_kn_mn_instances =
std::tuple<
// clang-format off
//##########| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
......@@ -39,21 +39,10 @@ using device_gemm_xdl_instance_f16_f16_f16_km_kn_mn =
// clang-format on
>;
template <>
void add_device_gemm_instance<F16, F16, F16, Col, Row, Row>(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& device_op_instances)
void add_device_gemm_xdl_f16_f16_f16_km_kn_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
using DeviceGemms = device_gemm_instance::device_gemm_xdl_instance_f16_f16_f16_km_kn_mn;
const auto device_gemms = DeviceGemms{};
ck::static_for<0, std::tuple_size_v<DeviceGemms>, 1>{}([&](auto i) {
using Gemm = remove_cvref_t<decltype(std::get<i>(device_gemms))>;
auto gemm = Gemm{};
device_op_instances.push_back(std::make_unique<Gemm>(gemm));
});
add_device_operation_instances(instances, device_gemm_xdl_f16_f16_f16_km_kn_mn_instances{});
}
} // namespace device_gemm_instance
......
device_operation/device_gemm_xdl_instance_f16_f16_f16_km_nk_mn.cpp → device_operation/device_gemm_xdl_f16_f16_f16_km_nk_mn_instance.cpp
View file @ 4be7f019
#include <stdlib.h>
#include "config.hpp"
#include "device_gemm_xdl.hpp"
#include "device_gemm_instance.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......@@ -21,7 +21,7 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[k, m] * b[n, k] = c[m, n]
using device_gemm_xdl_instance_f16_f16_f16_km_nk_mn =
using device_gemm_xdl_f16_f16_f16_km_nk_mn_instances =
std::tuple<
// clang-format off
//##########| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
......@@ -39,21 +39,10 @@ using device_gemm_xdl_instance_f16_f16_f16_km_nk_mn =
// clang-format on
>;
template <>
void add_device_gemm_instance<F16, F16, F16, Col, Col, Row>(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& device_op_instances)
void add_device_gemm_xdl_f16_f16_f16_km_nk_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
using DeviceGemms = device_gemm_instance::device_gemm_xdl_instance_f16_f16_f16_km_nk_mn;
const auto device_gemms = DeviceGemms{};
ck::static_for<0, std::tuple_size_v<DeviceGemms>, 1>{}([&](auto i) {
using Gemm = remove_cvref_t<decltype(std::get<i>(device_gemms))>;
auto gemm = Gemm{};
device_op_instances.push_back(std::make_unique<Gemm>(gemm));
});
add_device_operation_instances(instances, device_gemm_xdl_f16_f16_f16_km_nk_mn_instances{});
}
} // namespace device_gemm_instance
......
device_operation/device_gemm_xdl_instance_f16_f16_f16_mk_kn_mn.cpp → device_operation/device_gemm_xdl_f16_f16_f16_mk_kn_mn_instance.cpp
View file @ 4be7f019
#include <stdlib.h>
#include "config.hpp"
#include "device_gemm_xdl.hpp"
#include "device_gemm_instance.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......@@ -21,7 +21,7 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_instance_f16_f16_f16_mk_kn_mn =
using device_gemm_xdl_f16_f16_f16_mk_kn_mn_instances =
std::tuple<
// clang-format off
//##########| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
......@@ -39,21 +39,10 @@ using device_gemm_xdl_instance_f16_f16_f16_mk_kn_mn =
// clang-format on
>;
template <>
void add_device_gemm_instance<F16, F16, F16, Row, Row, Row>(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& device_op_instances)
void add_device_gemm_xdl_f16_f16_f16_mk_kn_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
using DeviceGemms = device_gemm_instance::device_gemm_xdl_instance_f16_f16_f16_mk_kn_mn;
const auto device_gemms = DeviceGemms{};
ck::static_for<0, std::tuple_size_v<DeviceGemms>, 1>{}([&](auto i) {
using Gemm = remove_cvref_t<decltype(std::get<i>(device_gemms))>;
auto gemm = Gemm{};
device_op_instances.push_back(std::make_unique<Gemm>(gemm));
});
add_device_operation_instances(instances, device_gemm_xdl_f16_f16_f16_mk_kn_mn_instances{});
}
} // namespace device_gemm_instance
......
device_operation/device_gemm_xdl_instance_f16_f16_f16_mk_nk_mn.cpp → device_operation/device_gemm_xdl_f16_f16_f16_mk_nk_mn_instance.cpp
View file @ 4be7f019
#include <stdlib.h>
#include "config.hpp"
#include "device_gemm_xdl.hpp"
#include "device_gemm_instance.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......@@ -21,7 +21,7 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[m, k] * b[n, k] = c[m, n]
using device_gemm_xdl_instance_f16_f16_f16_mk_nk_mn =
using device_gemm_xdl_f16_f16_f16_mk_nk_mn_instances =
std::tuple<
// clang-format off
//##########| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
......@@ -44,21 +44,10 @@ using device_gemm_xdl_instance_f16_f16_f16_mk_nk_mn =
// clang-format on
>;
template <>
void add_device_gemm_instance<F16, F16, F16, Row, Col, Row>(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& device_op_instances)
void add_device_gemm_xdl_f16_f16_f16_mk_nk_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
using DeviceGemms = device_gemm_instance::device_gemm_xdl_instance_f16_f16_f16_mk_nk_mn;
const auto device_gemms = DeviceGemms{};
ck::static_for<0, std::tuple_size_v<DeviceGemms>, 1>{}([&](auto i) {
using Gemm = remove_cvref_t<decltype(std::get<i>(device_gemms))>;
auto gemm = Gemm{};
device_op_instances.push_back(std::make_unique<Gemm>(gemm));
});
add_device_operation_instances(instances, device_gemm_xdl_f16_f16_f16_mk_nk_mn_instances{});
}
} // namespace device_gemm_instance
......
device_operation/device_gemm_xdl_instance_f32_f32_f32_km_kn_mn.cpp → device_operation/device_gemm_xdl_f32_f32_f32_km_kn_mn_instance.cpp
View file @ 4be7f019
#include <stdlib.h>
#include "config.hpp"
#include "device_gemm_xdl.hpp"
#include "device_gemm_instance.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......@@ -21,7 +21,7 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[k, m] * b[k, n] = c[m, n]
using device_gemm_xdl_instance_f32_f32_f32_km_kn_mn =
using device_gemm_xdl_f32_f32_f32_km_kn_mn_instances =
std::tuple<
// clang-format off
//##########| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
......@@ -39,21 +39,10 @@ using device_gemm_xdl_instance_f32_f32_f32_km_kn_mn =
// clang-format on
>;
template <>
void add_device_gemm_instance<F32, F32, F32, Col, Row, Row>(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& device_op_instances)
void add_device_gemm_xdl_f32_f32_f32_km_kn_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
using DeviceGemms = device_gemm_instance::device_gemm_xdl_instance_f32_f32_f32_km_kn_mn;
const auto device_gemms = DeviceGemms{};
ck::static_for<0, std::tuple_size_v<DeviceGemms>, 1>{}([&](auto i) {
using Gemm = remove_cvref_t<decltype(std::get<i>(device_gemms))>;
auto gemm = Gemm{};
device_op_instances.push_back(std::make_unique<Gemm>(gemm));
});
add_device_operation_instances(instances, device_gemm_xdl_f32_f32_f32_km_kn_mn_instances{});
}
} // namespace device_gemm_instance
......
device_operation/device_gemm_xdl_instance_f32_f32_f32_km_nk_mn.cpp → device_operation/device_gemm_xdl_f32_f32_f32_km_nk_mn_instance.cpp
View file @ 4be7f019
#include <stdlib.h>
#include "config.hpp"
#include "device_gemm_xdl.hpp"
#include "device_gemm_instance.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......@@ -21,7 +21,7 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[k, m] * b[n, k] = c[m, n]
using device_gemm_xdl_instance_f32_f32_f32_km_nk_mn =
using device_gemm_xdl_f32_f32_f32_km_nk_mn_instances =
std::tuple<
// clang-format off
//##########| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
......@@ -39,21 +39,10 @@ using device_gemm_xdl_instance_f32_f32_f32_km_nk_mn =
// clang-format on
>;
template <>
void add_device_gemm_instance<F32, F32, F32, Col, Col, Row>(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& device_op_instances)
void add_device_gemm_xdl_f32_f32_f32_km_nk_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
using DeviceGemms = device_gemm_instance::device_gemm_xdl_instance_f32_f32_f32_km_nk_mn;
const auto device_gemms = DeviceGemms{};
ck::static_for<0, std::tuple_size_v<DeviceGemms>, 1>{}([&](auto i) {
using Gemm = remove_cvref_t<decltype(std::get<i>(device_gemms))>;
auto gemm = Gemm{};
device_op_instances.push_back(std::make_unique<Gemm>(gemm));
});
add_device_operation_instances(instances, device_gemm_xdl_f32_f32_f32_km_nk_mn_instances{});
}
} // namespace device_gemm_instance
......
device_operation/device_gemm_xdl_instance_f32_f32_f32_mk_kn_mn.cpp → device_operation/device_gemm_xdl_f32_f32_f32_mk_kn_mn_instance.cpp
View file @ 4be7f019
#include <stdlib.h>
#include "config.hpp"
#include "device_gemm_xdl.hpp"
#include "device_gemm_instance.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......@@ -21,7 +21,7 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_instance_f32_f32_f32_mk_kn_mn =
using device_gemm_xdl_f32_f32_f32_mk_kn_mn_instances =
std::tuple<
// clang-format off
//##########| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
......@@ -39,21 +39,10 @@ using device_gemm_xdl_instance_f32_f32_f32_mk_kn_mn =
// clang-format on
>;
template <>
void add_device_gemm_instance<F32, F32, F32, Row, Row, Row>(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& device_op_instances)
void add_device_gemm_xdl_f32_f32_f32_mk_kn_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
using DeviceGemms = device_gemm_instance::device_gemm_xdl_instance_f32_f32_f32_mk_kn_mn;
const auto device_gemms = DeviceGemms{};
ck::static_for<0, std::tuple_size_v<DeviceGemms>, 1>{}([&](auto i) {
using Gemm = remove_cvref_t<decltype(std::get<i>(device_gemms))>;
auto gemm = Gemm{};
device_op_instances.push_back(std::make_unique<Gemm>(gemm));
});
add_device_operation_instances(instances, device_gemm_xdl_f32_f32_f32_mk_kn_mn_instances{});
}
} // namespace device_gemm_instance
......
device_operation/device_gemm_xdl_instance_f32_f32_f32_mk_nk_mn.cpp → device_operation/device_gemm_xdl_f32_f32_f32_mk_nk_mn_instance.cpp
View file @ 4be7f019
#include <stdlib.h>
#include "config.hpp"
#include "device_gemm_xdl.hpp"
#include "device_gemm_instance.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
......@@ -21,7 +21,7 @@ using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[m, k] * b[n, k] = c[m, n]
using device_gemm_xdl_instance_f32_f32_f32_mk_nk_mn =
using device_gemm_xdl_f32_f32_f32_mk_nk_mn_instances =
std::tuple<
// clang-format off
//##########| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
......@@ -44,21 +44,10 @@ using device_gemm_xdl_instance_f32_f32_f32_mk_nk_mn =
// clang-format on
>;
template <>
void add_device_gemm_instance<F32, F32, F32, Row, Col, Row>(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& device_op_instances)
void add_device_gemm_xdl_f32_f32_f32_mk_nk_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
using DeviceGemms = device_gemm_instance::device_gemm_xdl_instance_f32_f32_f32_mk_nk_mn;
const auto device_gemms = DeviceGemms{};
ck::static_for<0, std::tuple_size_v<DeviceGemms>, 1>{}([&](auto i) {
using Gemm = remove_cvref_t<decltype(std::get<i>(device_gemms))>;
auto gemm = Gemm{};
device_op_instances.push_back(std::make_unique<Gemm>(gemm));
});
add_device_operation_instances(instances, device_gemm_xdl_f32_f32_f32_mk_nk_mn_instances{});
}
} // namespace device_gemm_instance
......
device_operation/device_gemm_xdl_splitk_f32_f32_f32_km_kn_mn_instance.cpp 0 → 100644
View file @ 4be7f019
#include <stdlib.h>
#include "config.hpp"
#include "device_gemm_xdl_splitk.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_gemm_instance {
using F16 = ck::half_t;
using F32 = float;
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[k, m] * b[k, n] = c[m, n]
using device_gemm_xdl_splitk_f32_f32_f32_km_kn_mn_instances = std::tuple<
// clang-format off
//#################| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
//#################| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//#################| | | | | | | | Operation| Operation| Operation| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//#################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, 256, 256, 128, 4, 4, 32, 32, 4, 2, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 4, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, 256, 128, 256, 4, 4, 32, 32, 2, 4, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, 128, 128, 128, 4, 4, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 4, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, 256, 128, 128, 4, 4, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, 128, 128, 64, 4, 4, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 4, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, 128, 64, 128, 4, 4, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, 256, 128, 64, 4, 4, 32, 32, 2, 1, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Row, Row, PassThrough, PassThrough, PassThrough, 256, 64, 128, 4, 4, 32, 32, 1, 2, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 4, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, 7, 1>
// clang-format on
>;
void add_device_gemm_xdl_splitk_f32_f32_f32_km_kn_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_gemm_xdl_splitk_f32_f32_f32_km_kn_mn_instances{});
}
} // namespace device_gemm_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
device_operation/device_gemm_xdl_splitk_f32_f32_f32_km_nk_mn_instance.cpp 0 → 100644
View file @ 4be7f019
#include <stdlib.h>
#include "config.hpp"
#include "device_gemm_xdl_splitk.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_gemm_instance {
using F16 = ck::half_t;
using F32 = float;
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[k, m] * b[n, k] = c[m, n]
using device_gemm_xdl_splitk_f32_f32_f32_km_nk_mn_instances = std::tuple<
// clang-format off
//#################| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
//#################| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//#################| | | | | | | | Operation| Operation| Operation| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//#################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 256, 128, 4, 4, 32, 32, 4, 2, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 4, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 256, 4, 4, 32, 32, 2, 4, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 128, 4, 4, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 4, true, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 128, 4, 4, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 64, 4, 4, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 4, true, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, 128, 64, 128, 4, 4, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 64, 4, 4, 32, 32, 2, 1, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Col, Col, Row, PassThrough, PassThrough, PassThrough, 256, 64, 128, 4, 4, 32, 32, 1, 2, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 4, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>
// clang-format on
>;
void add_device_gemm_xdl_splitk_f32_f32_f32_km_nk_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_gemm_xdl_splitk_f32_f32_f32_km_nk_mn_instances{});
}
} // namespace device_gemm_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
device_operation/device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_instance.cpp 0 → 100644
View file @ 4be7f019
#include <stdlib.h>
#include "config.hpp"
#include "device_gemm_xdl_splitk.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_gemm_instance {
using F16 = ck::half_t;
using F32 = float;
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[m, k] * b[k, n] = c[m, n]
using device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_instances = std::tuple<
// clang-format off
//#################| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
//#################| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//#################| | | | | | | | Operation| Operation| Operation| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//#################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, 256, 96, 128, 4, 8, 16, 16, 3, 4, S<1, 4, 32, 2>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, 256, 256, 128, 4, 4, 32, 32, 4, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, 256, 128, 256, 4, 4, 32, 32, 2, 4, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, 128, 128, 128, 4, 4, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, 256, 128, 128, 4, 4, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, 128, 128, 64, 4, 4, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, 128, 64, 128, 4, 4, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 32, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, 256, 128, 64, 4, 4, 32, 32, 2, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 1, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Row, Row, PassThrough, PassThrough, PassThrough, 256, 64, 128, 4, 4, 32, 32, 1, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 64, 1>, S<0, 1, 3, 2>, S<0, 1, 3, 2>, 2, 2, 4, true, 7, 1>
>;
void add_device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_instances{});
}
} // namespace device_gemm_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
device_operation/device_gemm_xdl_splitk_f32_f32_f32_mk_nk_mn_instance.cpp 0 → 100644
View file @ 4be7f019
#include <stdlib.h>
#include "config.hpp"
#include "device_gemm_xdl_splitk.hpp"
#include "element_wise_operation.hpp"
#include "device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_gemm_instance {
using F16 = ck::half_t;
using F32 = float;
using Row = ck::tensor_layout::gemm::RowMajor;
using Col = ck::tensor_layout::gemm::ColumnMajor;
template <ck::index_t... Is>
using S = ck::Sequence<Is...>;
using PassThrough = ck::tensor_operation::element_wise::PassThrough;
// Compilation parameters for a[m, k] * b[n, k] = c[m, n]
using device_gemm_xdl_splitk_f32_f32_f32_mk_nk_mn_instances = std::tuple<
// clang-format off
//#################| AData| BData| CData| AccData| ALayout| BLayout| CLayout| A| B| C| Block| MPer| NPer| K0Per| K1| MPer| NPer| MXdl| NXdl| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockLds| BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| BBlockLds| CThreadTransfer| CThreadTransfer|
//#################| Type| Type| Type| Type| | | | Elementwise| Elementwise| Elementwise| Size| Block| Block| Block| | XDL| XDL| Per| Per| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraM| ThreadCluster| ThreadCluster| SrcAccessOrder| SrcVectorDim| SrcScalar| DstScalar| AddExtraN| SrcDstVectorDim| DstScalar|
//#################| | | | | | | | Operation| Operation| Operation| | | | | | | | Wave| Wave| Lengths_K0_M_K1| ArrangeOrder| | | PerVector| PerVector_K1| | Lengths_K0_N_K1| ArrangeOrder| | | PerVector| PerVector_K1| | | PerVector|
//#################| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 256, 256, 128, 4, 4, 32, 32, 4, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 256, 4, 4, 32, 32, 2, 4, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 128, 4, 4, 32, 32, 4, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 128, 4, 4, 32, 32, 2, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 64, 4, 4, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 128, 64, 128, 4, 4, 32, 32, 2, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 64, 64, 64, 4, 4, 32, 32, 2, 2, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 256, 128, 64, 4, 4, 32, 32, 2, 1, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 256, 64, 128, 4, 4, 32, 32, 1, 2, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 64, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 128, 128, 32, 4, 4, 32, 32, 2, 1, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 128, 32, 128, 4, 4, 32, 32, 1, 2, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 32, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 64, 64, 32, 4, 4, 32, 32, 2, 1, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>,
DeviceGemmXdlSplitK< F32, F32, F32, F32, Row, Col, Row, PassThrough, PassThrough, PassThrough, 64, 32, 64, 4, 4, 32, 32, 1, 2, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, S<1, 4, 16, 1>, S<0, 2, 1, 3>, S<0, 2, 1, 3>, 3, 4, 4, true, 7, 1>
// clang-format on
>;
void add_device_gemm_xdl_splitk_f32_f32_f32_mk_nk_mn_instances(
std::vector<DeviceGemmPtr<PassThrough, PassThrough, PassThrough>>& instances)
{
add_device_operation_instances(instances,
device_gemm_xdl_splitk_f32_f32_f32_mk_nk_mn_instances{});
}
} // namespace device_gemm_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
device_operation/include/device_gemm.hpp
View file @ 4be7f019
......@@ -13,8 +13,7 @@ template <typename AElementwiseOperation,
typename CElementwiseOperation>
struct DeviceGemm : public BaseOperator
{
virtual std::unique_ptr<BaseArgument>
MakeArgumentPointer(const void* p_a,
virtual std::unique_ptr<BaseArgument> MakeArgumentPointer(const void* p_a,
const void* p_b,
void* p_c,
ck::index_t M,
......@@ -25,7 +24,8 @@ struct DeviceGemm : public BaseOperator
ck::index_t StrideC,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
CElementwiseOperation c_element_op) = 0;
CElementwiseOperation c_element_op,
ck::index_t KBatch = 1) = 0;
virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
};
......
device_operation/include/device_gemm_instance.hpp deleted 100644 → 0
View file @ ca47a6cf
#ifndef DEVICE_GEMM_INSTANTCE_HPP
#define DEVICE_GEMM_INSTANTCE_HPP
#include "device_gemm.hpp"
#include "element_wise_operation.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_gemm_instance {
template <typename ADataType,
typename BDataType,
typename CDataType,
typename ALayout,
typename BLayout,
typename CLayout>
void add_device_gemm_instance(
std::vector<DeviceGemmPtr<ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough>>&);
} // namespace device_gemm_instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
#endif
device_operation/include/device_gemm_xdl.hpp
View file @ 4be7f019
......@@ -408,7 +408,8 @@ struct DeviceGemmXdl
index_t StrideC,
AElementwiseOperation a_element_op,
BElementwiseOperation b_element_op,
CElementwiseOperation c_element_op) override
CElementwiseOperation c_element_op,
ck::index_t) override
{
return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
static_cast<const BDataType*>(p_b),
......
device_operation/include/device_gemm_xdl_splitk.hpp 0 → 100644
View file @ 4be7f019
This diff is collapsed.
profiler/CMakeLists.txt
View file @ 4be7f019
......@@ -14,14 +14,18 @@ include_directories(BEFORE
# device_gemm_instance
set(DEVICE_GEMM_INSTANCE_SOURCE
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_instance_f32_f32_f32_mk_kn_mn.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_instance_f32_f32_f32_mk_nk_mn.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_instance_f32_f32_f32_km_kn_mn.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_instance_f32_f32_f32_km_nk_mn.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_instance_f16_f16_f16_mk_kn_mn.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_instance_f16_f16_f16_mk_nk_mn.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_instance_f16_f16_f16_km_kn_mn.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_instance_f16_f16_f16_km_nk_mn.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_f32_f32_f32_mk_kn_mn_instance.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_f32_f32_f32_mk_nk_mn_instance.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_f32_f32_f32_km_kn_mn_instance.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_f32_f32_f32_km_nk_mn_instance.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_f16_f16_f16_mk_kn_mn_instance.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_f16_f16_f16_mk_nk_mn_instance.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_f16_f16_f16_km_kn_mn_instance.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_f16_f16_f16_km_nk_mn_instance.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_instance.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_splitk_f32_f32_f32_mk_nk_mn_instance.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_splitk_f32_f32_f32_km_kn_mn_instance.cpp;
${PROJECT_SOURCE_DIR}/device_operation/device_gemm_xdl_splitk_f32_f32_f32_km_nk_mn_instance.cpp;
)
add_library(device_gemm_instance SHARED ${DEVICE_GEMM_INSTANCE_SOURCE})
......@@ -83,7 +87,8 @@ set(PROFILER_SOURCE
profile_conv_fwd.cpp
profile_conv_fwd_bias_relu.cpp
profile_conv_fwd_bias_relu_add.cpp
profile_conv_fwd_bias_relu_atomic_add.cpp)
profile_conv_fwd_bias_relu_atomic_add.cpp
)
add_executable(ckProfiler ${PROFILER_SOURCE})
target_link_libraries(ckProfiler PRIVATE host_tensor)
......
profiler/include/profile_gemm_impl.hpp
View file @ 4be7f019
#pragma once
#include "device_gemm_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace device_gemm_instance {
using DeviceGemmNoOpPtr = DeviceGemmPtr<ck::tensor_operation::element_wise::PassThrough,
using DeviceGemmNoOpPtr =
ck::tensor_operation::device::DeviceGemmPtr<ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough,
ck::tensor_operation::element_wise::PassThrough>;
template <>
void add_device_gemm_instance<float,
float,
float,
ck::tensor_layout::gemm::RowMajor,
ck::tensor_layout::gemm::RowMajor,
ck::tensor_layout::gemm::RowMajor>(std::vector<DeviceGemmNoOpPtr>&);
template <>
void add_device_gemm_instance<float,
float,
float,
ck::tensor_layout::gemm::RowMajor,
ck::tensor_layout::gemm::ColumnMajor,
ck::tensor_layout::gemm::RowMajor>(std::vector<DeviceGemmNoOpPtr>&);
template <>
void add_device_gemm_instance<float,
float,
float,
ck::tensor_layout::gemm::ColumnMajor,
ck::tensor_layout::gemm::RowMajor,
ck::tensor_layout::gemm::RowMajor>(std::vector<DeviceGemmNoOpPtr>&);
template <>
void add_device_gemm_instance<float,
float,
float,
ck::tensor_layout::gemm::ColumnMajor,
ck::tensor_layout::gemm::ColumnMajor,
ck::tensor_layout::gemm::RowMajor>(std::vector<DeviceGemmNoOpPtr>&);
template <>
void add_device_gemm_instance<ck::half_t,
ck::half_t,
ck::half_t,
ck::tensor_layout::gemm::RowMajor,
ck::tensor_layout::gemm::RowMajor,
ck::tensor_layout::gemm::RowMajor>(std::vector<DeviceGemmNoOpPtr>&);
template <>
void add_device_gemm_instance<ck::half_t,
ck::half_t,
ck::half_t,
ck::tensor_layout::gemm::RowMajor,
ck::tensor_layout::gemm::ColumnMajor,
ck::tensor_layout::gemm::RowMajor>(std::vector<DeviceGemmNoOpPtr>&);
template <>
void add_device_gemm_instance<ck::half_t,
ck::half_t,
ck::half_t,
ck::tensor_layout::gemm::ColumnMajor,
ck::tensor_layout::gemm::RowMajor,
ck::tensor_layout::gemm::RowMajor>(std::vector<DeviceGemmNoOpPtr>&);
template <>
void add_device_gemm_instance<ck::half_t,
ck::half_t,
ck::half_t,
ck::tensor_layout::gemm::ColumnMajor,
ck::tensor_layout::gemm::ColumnMajor,
ck::tensor_layout::gemm::RowMajor>(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_f16_f16_f16_mk_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_f16_f16_f16_mk_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_f16_f16_f16_km_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_f16_f16_f16_km_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_f32_f32_f32_mk_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_f32_f32_f32_mk_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_f32_f32_f32_km_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_f32_f32_f32_km_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_splitk_f32_f32_f32_mk_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_splitk_f32_f32_f32_km_kn_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
void add_device_gemm_xdl_splitk_f32_f32_f32_km_nk_mn_instances(std::vector<DeviceGemmNoOpPtr>&);
} // namespace device_gemm_instance
} // namespace device
......@@ -97,7 +48,8 @@ void profile_gemm_impl(int do_verification,
int K,
int StrideA,
int StrideB,
int StrideC)
int StrideC,
int KBatch = 1)
{
auto f_host_tensor_descriptor =
[](std::size_t row, std::size_t col, std::size_t stride, auto layout) {
......@@ -122,17 +74,20 @@ void profile_gemm_impl(int do_verification,
std::cout << "b_k_n: " << b_k_n.mDesc << std::endl;
std::cout << "c_m_n: " << c_m_n_host_result.mDesc << std::endl;
std::size_t num_thread = std::thread::hardware_concurrency();
switch(init_method)
{
case 0: break;
case 1:
a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5});
b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5});
a_m_k.GenerateTensorValue(GeneratorTensor_2<ADataType>{-5, 5}, num_thread);
b_k_n.GenerateTensorValue(GeneratorTensor_2<BDataType>{-5, 5}, num_thread);
break;
default:
a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0});
b_k_n.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5});
a_m_k.GenerateTensorValue(GeneratorTensor_3<ADataType>{0.0, 1.0}, num_thread);
b_k_n.GenerateTensorValue(GeneratorTensor_3<BDataType>{-0.5, 0.5}, num_thread);
}
// set zero to c_device_buf
c_m_n_device_result.GenerateTensorValue(GeneratorTensor_0<CDataType>{}, num_thread);
if(do_verification)
{
......@@ -155,9 +110,103 @@ void profile_gemm_impl(int do_verification,
// add device GEMM instances
std::vector<ck::tensor_operation::device::device_gemm_instance::DeviceGemmNoOpPtr> gemm_ptrs;
if constexpr(is_same<ADataType, float>::value && is_same<BDataType, float>::value &&
is_same<CDataType, float>::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)
{
if(KBatch > 1)
{
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_xdl_splitk_f32_f32_f32_mk_kn_mn_instances(gemm_ptrs);
}
else
{
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_xdl_f32_f32_f32_mk_kn_mn_instances(gemm_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)
{
if(KBatch > 1)
{
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_xdl_splitk_f32_f32_f32_mk_nk_mn_instances(gemm_ptrs);
}
else
{
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_xdl_f32_f32_f32_mk_nk_mn_instances(gemm_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)
{
if(KBatch > 1)
{
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_xdl_splitk_f32_f32_f32_km_kn_mn_instances(gemm_ptrs);
}
else
{
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_instance<ADataType, BDataType, CDataType, ALayout, BLayout, CLayout>(
gemm_ptrs);
add_device_gemm_xdl_f32_f32_f32_km_kn_mn_instances(gemm_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)
{
if(KBatch > 1)
{
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_xdl_splitk_f32_f32_f32_km_nk_mn_instances(gemm_ptrs);
}
else
{
ck::tensor_operation::device::device_gemm_instance::
add_device_gemm_xdl_f32_f32_f32_km_nk_mn_instances(gemm_ptrs);
}
}
}
else 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_xdl_f16_f16_f16_mk_kn_mn_instances(gemm_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_xdl_f16_f16_f16_mk_nk_mn_instances(gemm_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_xdl_f16_f16_f16_km_kn_mn_instances(gemm_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_xdl_f16_f16_f16_km_nk_mn_instances(gemm_ptrs);
}
}
if(gemm_ptrs.size() <= 0)
{
......@@ -184,7 +233,8 @@ void profile_gemm_impl(int do_verification,
StrideC,
ck::tensor_operation::element_wise::PassThrough{},
ck::tensor_operation::element_wise::PassThrough{},
ck::tensor_operation::element_wise::PassThrough{});
ck::tensor_operation::element_wise::PassThrough{},
KBatch);
auto invoker_ptr = gemm_ptr->MakeInvokerPointer();
......
profiler/profile_gemm.cpp
View file @ 4be7f019
......@@ -35,19 +35,20 @@ enum GemmDataType
int profile_gemm(int argc, char* argv[])
{
if(argc != 14)
if(!(argc == 14 || argc == 15))
{
printf("arg1: tensor operation (gemm: GEMM)\n");
printf("arg2: data type (0: fp32; 1: fp16)\n");
printf("arg3: matrix layout (0: A[m, k] * B[k, n] = C[m, n];\n");
printf(" 1: A[m, k] * B[n, k] = C[m, n];\n");
printf(" 2: A[k, n] * B[k, n] = C[m, n];\n");
printf(" 3: A[k, n] * B[n, k] = C[m, n])\n");
printf(" 2: A[k, m] * B[k, n] = C[m, n];\n");
printf(" 3: A[k, m] * B[n, k] = C[m, n])\n");
printf("arg4: verification (0: no; 1: yes)\n");
printf("arg5: initialization (0: no init; 1: integer value; 2: decimal value)\n");
printf("arg8: print tensor value (0: no; 1: yes)\n");
printf("arg7: run kernel # of times (>1)\n");
printf("arg8 to 13: M, N, K, StrideA, StrideB, StrideC\n");
printf("arg14: split k into mulitiple batch\n");
exit(1);
}
......@@ -65,6 +66,9 @@ int profile_gemm(int argc, char* argv[])
const int StrideA = std::stoi(argv[11]);
const int StrideB = std::stoi(argv[12]);
const int StrideC = std::stoi(argv[13]);
int KBatch = 1;
if(argc == 15)
KBatch = std::stoi(argv[14]);
if(data_type == GemmDataType::F16_F16_F16 && layout == GemmMatrixLayout::MK_KN_MN)
{
......@@ -159,7 +163,8 @@ int profile_gemm(int argc, char* argv[])
K,
(StrideA < 0) ? K : StrideA,
(StrideB < 0) ? N : StrideB,
(StrideC < 0) ? N : StrideC);
(StrideC < 0) ? N : StrideC,
KBatch);
}
else if(data_type == GemmDataType::F32_F32_F32 && layout == GemmMatrixLayout::MK_NK_MN)
{
......@@ -178,7 +183,8 @@ int profile_gemm(int argc, char* argv[])
K,
(StrideA < 0) ? K : StrideA,
(StrideB < 0) ? K : StrideB,
(StrideC < 0) ? N : StrideC);
(StrideC < 0) ? N : StrideC,
KBatch);
}
else if(data_type == GemmDataType::F32_F32_F32 && layout == GemmMatrixLayout::KM_KN_MN)
{
......@@ -197,7 +203,8 @@ int profile_gemm(int argc, char* argv[])
K,
(StrideA < 0) ? M : StrideA,
(StrideB < 0) ? N : StrideB,
(StrideC < 0) ? N : StrideC);
(StrideC < 0) ? N : StrideC,
KBatch);
}
else if(data_type == GemmDataType::F32_F32_F32 && layout == GemmMatrixLayout::KM_NK_MN)
{
......@@ -216,7 +223,8 @@ int profile_gemm(int argc, char* argv[])
K,
(StrideA < 0) ? M : StrideA,
(StrideB < 0) ? K : StrideB,
(StrideC < 0) ? N : StrideC);
(StrideC < 0) ? N : StrideC,
KBatch);
}
else
{
......
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