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gaoqiong
composable_kernel
Commits
7a3b49e5
"docs/vscode:/vscode.git/clone" did not exist on "55b28b1eee3a94a8b1c812d461f68ff8f150d38e"
Commit
7a3b49e5
authored
Jun 25, 2022
by
Chao Liu
Browse files
Merge remote-tracking branch 'origin/develop' into contraction
parents
e07b3d8e
d3051d75
Changes
592
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20 changed files
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148 additions
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457 deletions
+148
-457
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_f16_f16_f16.cpp
.../reduce/device_reduce_instance_threadwise_f16_f16_f16.cpp
+4
-1
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_f16_f32_f16.cpp
.../reduce/device_reduce_instance_threadwise_f16_f32_f16.cpp
+4
-2
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_f32_f32_f32.cpp
.../reduce/device_reduce_instance_threadwise_f32_f32_f32.cpp
+4
-1
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_f32_f64_f32.cpp
.../reduce/device_reduce_instance_threadwise_f32_f64_f32.cpp
+4
-1
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_f64_f64_f64.cpp
.../reduce/device_reduce_instance_threadwise_f64_f64_f64.cpp
+4
-2
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_i8_i32_i8.cpp
...pu/reduce/device_reduce_instance_threadwise_i8_i32_i8.cpp
+4
-1
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_i8_i8_i8.cpp
...gpu/reduce/device_reduce_instance_threadwise_i8_i8_i8.cpp
+4
-1
library/src/utility/CMakeLists.txt
library/src/utility/CMakeLists.txt
+0
-10
library/src/utility/conv_util.cpp
library/src/utility/conv_util.cpp
+3
-1
profiler/CMakeLists.txt
profiler/CMakeLists.txt
+5
-22
profiler/include/data_type_enum.hpp
profiler/include/data_type_enum.hpp
+4
-3
profiler/include/data_type_enum_helper.hpp
profiler/include/data_type_enum_helper.hpp
+6
-5
profiler/include/profile_batched_gemm_impl.hpp
profiler/include/profile_batched_gemm_impl.hpp
+14
-8
profiler/include/profile_batched_gemm_reduce_impl.hpp
profiler/include/profile_batched_gemm_reduce_impl.hpp
+29
-28
profiler/include/profile_conv_bwd_weight_impl.hpp
profiler/include/profile_conv_bwd_weight_impl.hpp
+14
-10
profiler/include/profile_conv_fwd_bias_relu_add_impl.hpp
profiler/include/profile_conv_fwd_bias_relu_add_impl.hpp
+13
-10
profiler/include/profile_conv_fwd_bias_relu_atomic_add_impl.hpp
...er/include/profile_conv_fwd_bias_relu_atomic_add_impl.hpp
+0
-331
profiler/include/profile_conv_fwd_bias_relu_impl.hpp
profiler/include/profile_conv_fwd_bias_relu_impl.hpp
+14
-10
profiler/include/profile_convnd_bwd_data_impl.hpp
profiler/include/profile_convnd_bwd_data_impl.hpp
+15
-10
profiler/include/profile_convnd_fwd.hpp
profiler/include/profile_convnd_fwd.hpp
+3
-0
No files found.
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_f16_f16_f16.cpp
View file @
7a3b49e5
#include "device_reduce_instance_threadwise.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise.hpp"
namespace
ck
{
namespace
tensor_operation
{
...
...
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_f16_f32_f16.cpp
View file @
7a3b49e5
#include "device_reduce_instance_threadwise.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise.hpp"
namespace
ck
{
namespace
tensor_operation
{
...
...
@@ -24,5 +27,4 @@ ADD_THREADWISE_INST_BY_ID(half_t, float, half_t, 7, 0, 0, 2, 1);
}
// namespace device_reduce_instance
}
// namespace device
}
// namespace tensor_operation
}
// namespace ck
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_f32_f32_f32.cpp
View file @
7a3b49e5
#include "device_reduce_instance_threadwise.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise.hpp"
namespace
ck
{
namespace
tensor_operation
{
...
...
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_f32_f64_f32.cpp
View file @
7a3b49e5
#include "device_reduce_instance_threadwise.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise.hpp"
namespace
ck
{
namespace
tensor_operation
{
...
...
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_f64_f64_f64.cpp
View file @
7a3b49e5
#include "device_reduce_instance_threadwise.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise.hpp"
namespace
ck
{
namespace
tensor_operation
{
...
...
@@ -48,5 +51,4 @@ ADD_THREADWISE_INST_BY_ID(double, double, double, 4, 0, 1, 2, 1);
}
// namespace device_reduce_instance
}
// namespace device
}
// namespace tensor_operation
}
// namespace ck
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_i8_i32_i8.cpp
View file @
7a3b49e5
#include "device_reduce_instance_threadwise.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise.hpp"
namespace
ck
{
namespace
tensor_operation
{
...
...
library/src/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise_i8_i8_i8.cpp
View file @
7a3b49e5
#include "device_reduce_instance_threadwise.hpp"
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "ck/library/tensor_operation_instance/gpu/reduce/device_reduce_instance_threadwise.hpp"
namespace
ck
{
namespace
tensor_operation
{
...
...
library/src/utility/CMakeLists.txt
View file @
7a3b49e5
include_directories
(
BEFORE
${
PROJECT_SOURCE_DIR
}
/include/ck
${
PROJECT_SOURCE_DIR
}
/include/ck/tensor_operation/gpu/device
${
PROJECT_SOURCE_DIR
}
/include/ck/tensor_operation/gpu/element
${
PROJECT_SOURCE_DIR
}
/include/ck/utility
${
PROJECT_SOURCE_DIR
}
/library/include/ck/library/host_tensor
${
PROJECT_SOURCE_DIR
}
/library/include/ck/library/reference_tensor_operation/cpu
${
PROJECT_SOURCE_DIR
}
/library/include/ck/library/utility
)
set
(
CONV_UTIL_SOURCE
conv_util.cpp
)
...
...
library/src/utility/conv_util.cpp
View file @
7a3b49e5
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "conv_util.hpp"
#include "
ck/library/utility/
conv_util.hpp"
namespace
ck
{
namespace
utils
{
...
...
profiler/CMakeLists.txt
View file @
7a3b49e5
include_directories
(
BEFORE
${
PROJECT_SOURCE_DIR
}
/include/ck
${
PROJECT_SOURCE_DIR
}
/include/ck/utility
${
PROJECT_SOURCE_DIR
}
/include/ck/host_utility
${
PROJECT_SOURCE_DIR
}
/include/ck/tensor_description
${
PROJECT_SOURCE_DIR
}
/include/ck/tensor
${
PROJECT_SOURCE_DIR
}
/include/ck/problem_transform
${
PROJECT_SOURCE_DIR
}
/include/ck/tensor_operation/gpu/device
${
PROJECT_SOURCE_DIR
}
/include/ck/tensor_operation/gpu/grid
${
PROJECT_SOURCE_DIR
}
/include/ck/tensor_operation/gpu/block
${
PROJECT_SOURCE_DIR
}
/include/ck/tensor_operation/gpu/warp
${
PROJECT_SOURCE_DIR
}
/include/ck/tensor_operation/gpu/thread
${
PROJECT_SOURCE_DIR
}
/include/ck/tensor_operation/gpu/element
${
PROJECT_SOURCE_DIR
}
/library/include/ck/library/host_tensor
${
PROJECT_SOURCE_DIR
}
/library/include/ck/library/tensor_operation_instance
${
PROJECT_SOURCE_DIR
}
/library/include/ck/library/tensor_operation_instance/gpu/reduce
${
PROJECT_SOURCE_DIR
}
/library/include/ck/library/reference_tensor_operation/cpu
${
PROJECT_SOURCE_DIR
}
/library/include/ck/library/reference_tensor_operation/gpu
${
PROJECT_SOURCE_DIR
}
/library/include/ck/library/utility
${
PROJECT_SOURCE_DIR
}
/profiler/include
${
PROJECT_SOURCE_DIR
}
/external/include/half
${
PROJECT_SOURCE_DIR
}
/
)
# ck_profiler
...
...
@@ -29,16 +10,17 @@ set(PROFILER_SOURCE
src/profile_gemm_bias_relu.cpp
src/profile_gemm_bias_relu_add.cpp
src/profile_gemm_reduce.cpp
src/profile_gemm_bias_add_reduce.cpp
src/profile_batched_gemm.cpp
src/profile_conv_fwd_bias_relu.cpp
src/profile_conv_fwd_bias_relu_add.cpp
src/profile_conv_fwd_bias_relu_atomic_add.cpp
src/profile_convnd_fwd.cpp
src/profile_convnd_bwd_data.cpp
src/profile_reduce.cpp
src/profile_grouped_gemm.cpp
src/profile_conv_bwd_weight.cpp
src/profile_batched_gemm_reduce.cpp
src/profile_gemm_add_add_fastgelu.cpp
)
add_executable
(
ckProfiler
${
PROFILER_SOURCE
}
)
...
...
@@ -46,6 +28,7 @@ add_executable(ckProfiler ${PROFILER_SOURCE})
target_link_libraries
(
ckProfiler PRIVATE host_tensor
)
target_link_libraries
(
ckProfiler PRIVATE conv_util
)
target_link_libraries
(
ckProfiler PRIVATE device_gemm_reduce_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_gemm_bias_add_reduce_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_gemm_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_gemm_bias2d_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_gemm_bias_relu_instance
)
...
...
@@ -56,9 +39,9 @@ target_link_libraries(ckProfiler PRIVATE device_conv2d_fwd_instance)
target_link_libraries
(
ckProfiler PRIVATE device_conv3d_fwd_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_conv2d_fwd_bias_relu_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_conv2d_fwd_bias_relu_add_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_conv2d_fwd_bias_relu_atomic_add_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_convnd_bwd_data_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_reduce_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_grouped_gemm_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_conv2d_bwd_weight_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_batched_gemm_reduce_instance
)
target_link_libraries
(
ckProfiler PRIVATE device_gemm_add_add_fastgelu_instance
)
include/ck/utility
/data_type_enum.hpp
→
profiler/include
/data_type_enum.hpp
View file @
7a3b49e5
#ifndef CK_DATA_TYPE_ENUM_HPP
#define CK_DATA_TYPE_ENUM_HPP
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
namespace
ck
{
...
...
@@ -16,4 +18,3 @@ enum struct DataTypeEnum
};
}
// namespace ck
#endif
include/ck/utility
/data_type_enum_helper.hpp
→
profiler/include
/data_type_enum_helper.hpp
View file @
7a3b49e5
#ifndef CK_DATA_TYPE_ENUM_HELPER_HPP
#define CK_DATA_TYPE_ENUM_HELPER_HPP
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#include "data_type.hpp"
#include "data_type_enum.hpp"
#pragma
#include "ck/utility/data_type.hpp"
#include "profiler/include/data_type_enum.hpp"
namespace
ck
{
...
...
@@ -73,4 +75,3 @@ struct get_datatype_enum_from_type<double>
};
}
// namespace ck
#endif
profiler/include/profile_batched_gemm_impl.hpp
View file @
7a3b49e5
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include <memory>
#include "check_err.hpp"
#include "config.hpp"
#include "element_wise_operation.hpp"
#include "tensor_layout.hpp"
#include "device.hpp"
#include "host_tensor_generator.hpp"
#include "device_gemm.hpp"
#include "reference_batched_gemm.hpp"
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_gemm.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/utility/check_err.hpp"
#include "ck/library/utility/conv_util.hpp"
#include "ck/library/host_tensor/device_memory.hpp"
#include "ck/library/host_tensor/host_tensor.hpp"
#include "ck/library/host_tensor/host_tensor_generator.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_batched_gemm.hpp"
namespace
ck
{
namespace
tensor_operation
{
...
...
profiler/include/profile_batched_gemm_reduce_impl.hpp
View file @
7a3b49e5
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "config.hpp"
#include "device.hpp"
#include "host_tensor.hpp"
#include "host_tensor_generator.hpp"
#include "host_conv.hpp"
#include "tensor_layout.hpp"
#include "device_tensor.hpp"
#include "element_wise_operation.hpp"
#include "reduction_operator.hpp"
#include "device_gemm_reduce.hpp"
#include "reference_batched_gemm.hpp"
#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/device_gemm_reduce.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/utility/check_err.hpp"
#include "ck/library/utility/conv_util.hpp"
#include "ck/library/host_tensor/device_memory.hpp"
#include "ck/library/host_tensor/host_tensor.hpp"
#include "ck/library/host_tensor/host_tensor_generator.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_batched_gemm.hpp"
namespace
ck
{
namespace
tensor_operation
{
...
...
@@ -20,13 +24,12 @@ namespace device_gemm_instance {
using
F32
=
float
;
using
F16
=
ck
::
half_t
;
using
DPtrsGlobal
=
ck
::
Tuple
<
F32
*
,
F32
*>
;
using
Identity
=
ck
::
tensor_operation
::
element_wise
::
UnaryIdentic
<
F32
,
F32
,
false
>
;
using
Square
=
ck
::
tensor_operation
::
element_wise
::
UnarySquare
<
F32
,
F32
,
false
>
;
using
Identity
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
Square
=
ck
::
tensor_operation
::
element_wise
::
UnarySquare
;
using
DInElementOps
=
ck
::
Tuple
<
Identity
,
Square
>
;
using
DOutElementOps
=
ck
::
Tuple
<
Identity
,
Identity
>
;
using
DeviceGemmReduceNoOpPtr
=
ck
::
tensor_operation
::
device
::
DeviceGemmReducePtr
<
DPtrsGlobal
,
ck
::
tensor_operation
::
element_wise
::
PassThrough
,
ck
::
tensor_operation
::
element_wise
::
PassThrough
,
ck
::
tensor_operation
::
element_wise
::
PassThrough
,
...
...
@@ -129,17 +132,15 @@ bool profile_batched_gemm_reduce_impl(int do_verification,
b_g_k_n
.
GenerateTensorValue
(
GeneratorTensor_3
<
BDataType
>
{
-
0.5
,
0.5
},
num_thread
);
}
using
AElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
BElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
CElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
D0ReduceOp
=
ck
::
reduce
::
Add
<
float
>
;
using
D1ReduceOp
=
ck
::
reduce
::
Add
<
float
>
;
using
UnaryIdenticElementOp
=
ck
::
tensor_operation
::
element_wise
::
UnaryIdentic
<
float
,
float
,
false
>
;
using
UnarySquareElementOp
=
ck
::
tensor_operation
::
element_wise
::
UnarySquare
<
float
,
float
,
false
>
;
using
DxsInElementOps
=
ck
::
Tuple
<
UnaryIdenticElementOp
,
UnarySquareElementOp
>
;
using
DxsOutElementOps
=
ck
::
Tuple
<
UnaryIdenticElementOp
,
UnaryIdenticElementOp
>
;
using
AElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
BElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
CElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
D0ReduceOp
=
ck
::
reduce
::
Add
;
using
D1ReduceOp
=
ck
::
reduce
::
Add
;
using
UnaryIdenticElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
UnarySquareElementOp
=
ck
::
tensor_operation
::
element_wise
::
UnarySquare
;
using
DxsInElementOps
=
ck
::
Tuple
<
UnaryIdenticElementOp
,
UnarySquareElementOp
>
;
using
DxsOutElementOps
=
ck
::
Tuple
<
UnaryIdenticElementOp
,
UnaryIdenticElementOp
>
;
const
auto
a_element_op
=
AElementOp
{};
const
auto
b_element_op
=
BElementOp
{};
...
...
@@ -171,8 +172,8 @@ bool profile_batched_gemm_reduce_impl(int do_verification,
{
for
(
int
m
=
0
;
m
<
M
;
++
m
)
{
float
d0_acc
=
d0_reduce_op
.
Get
ReductionZeroVal
();
float
d1_acc
=
d1_reduce_op
.
Get
ReductionZeroVal
();
float
d0_acc
=
d0_reduce_op
.
Get
IdentityValue
<
float
>
();
float
d1_acc
=
d1_reduce_op
.
Get
IdentityValue
<
float
>
();
for
(
int
n
=
0
;
n
<
N
;
++
n
)
{
...
...
@@ -260,7 +261,7 @@ bool profile_batched_gemm_reduce_impl(int do_verification,
gemm_ptr
->
MakeArgumentPointer
(
static_cast
<
ADataType
*>
(
a_device_buf
.
GetDeviceBuffer
()),
static_cast
<
BDataType
*>
(
b_device_buf
.
GetDeviceBuffer
()),
static_cast
<
CDataType
*>
(
c_device_buf
.
GetDeviceBuffer
()),
dxs_global
,
&
dxs_global
,
M
,
N
,
K
,
...
...
profiler/include/profile_conv_bwd_weight_impl.hpp
View file @
7a3b49e5
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "stream_config.hpp"
#include "config.hpp"
#include "device.hpp"
#include "host_tensor.hpp"
#include "host_tensor_generator.hpp"
#include "tensor_layout.hpp"
#include "device_tensor.hpp"
#include "device_conv_backward_weight.hpp"
#include "element_wise_operation.hpp"
#include "reference_conv_backward_weight.hpp"
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_conv_backward_weight.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/utility/check_err.hpp"
#include "ck/library/utility/conv_util.hpp"
#include "ck/library/host_tensor/device_memory.hpp"
#include "ck/library/host_tensor/host_tensor.hpp"
#include "ck/library/host_tensor/host_tensor_generator.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_conv_backward_weight.hpp"
namespace
ck
{
namespace
tensor_operation
{
...
...
profiler/include/profile_conv_fwd_bias_relu_add_impl.hpp
View file @
7a3b49e5
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "c
heck_err
.hpp"
#include "c
onfig
.hpp"
#include "
device
.hpp"
#include "
host_tensor
.hpp"
#include "host_tensor_generator.hpp"
#include "
tensor_layout
.hpp"
#include "device_
tens
or.hpp"
#include "
element_wise_operation
.hpp"
#include "
device_conv_fwd_bias_activation_add
.hpp"
#include "reference_conv_fwd_bias_activation_add.hpp"
#include "c
k/ck
.hpp"
#include "c
k/tensor_operation/gpu/device/tensor_layout
.hpp"
#include "
ck/tensor_operation/gpu/device/device_conv_fwd_bias_activation_add
.hpp"
#include "
ck/tensor_operation/gpu/element/element_wise_operation
.hpp"
#include "
ck/library/utility/check_err
.hpp"
#include "
ck/library/host_tensor/
device_
mem
or
y
.hpp"
#include "
ck/library/host_tensor/host_tensor
.hpp"
#include "
ck/library/host_tensor/host_tensor_generator
.hpp"
#include "
ck/library/reference_tensor_operation/cpu/
reference_conv_fwd_bias_activation_add.hpp"
namespace
ck
{
namespace
tensor_operation
{
...
...
profiler/include/profile_conv_fwd_bias_relu_atomic_add_impl.hpp
deleted
100644 → 0
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e07b3d8e
#pragma once
#include "check_err.hpp"
#include "config.hpp"
#include "device.hpp"
#include "host_tensor.hpp"
#include "host_tensor_generator.hpp"
#include "host_conv.hpp"
#include "tensor_layout.hpp"
#include "device_tensor.hpp"
#include "device_conv_fwd_bias_activation.hpp"
#include "element_wise_operation.hpp"
namespace
ck
{
namespace
tensor_operation
{
namespace
device
{
namespace
device_conv2d_fwd_bias_activation_atomic_add_instance
{
using
DeviceConvFwdBiasReluPtr
=
DeviceConvFwdBiasActivationPtr
<
ck
::
tensor_operation
::
element_wise
::
PassThrough
,
ck
::
tensor_operation
::
element_wise
::
PassThrough
,
ck
::
tensor_operation
::
element_wise
::
AddRelu
>
;
void
add_device_conv2d_fwd_xdl_c_shuffle_bias_relu_atomic_add_nhwc_kyxc_nhwk_f16_instances
(
std
::
vector
<
DeviceConvFwdBiasReluPtr
>&
);
}
// namespace device_conv2d_fwd_bias_activation_atomic_add_instance
}
// namespace device
}
// namespace tensor_operation
}
// namespace ck
namespace
ck
{
namespace
profiler
{
void
cpu_conv_bias_relu_atomic_add
(
ck
::
half_t
*
in_ptr
,
ck
::
half_t
*
weight_ptr
,
ck
::
half_t
*
output_ptr
,
ck
::
half_t
*
bias_ptr
,
const
ck
::
index_t
N
,
const
ck
::
index_t
K
,
const
ck
::
index_t
C
,
const
ck
::
index_t
Y
,
const
ck
::
index_t
X
,
const
ck
::
index_t
Hi
,
const
ck
::
index_t
Wi
,
const
ck
::
index_t
Ho
,
const
ck
::
index_t
Wo
,
const
ck
::
index_t
Stride
,
const
ck
::
index_t
Dilation
,
const
ck
::
index_t
Pad
)
{
const
auto
in_desc
=
HostTensorDescriptor
(
std
::
vector
<
std
::
size_t
>
{
static_cast
<
std
::
size_t
>
(
N
),
static_cast
<
std
::
size_t
>
(
Hi
),
static_cast
<
std
::
size_t
>
(
Wi
),
static_cast
<
std
::
size_t
>
(
C
)});
const
auto
wei_desc
=
HostTensorDescriptor
(
std
::
vector
<
std
::
size_t
>
{
static_cast
<
std
::
size_t
>
(
K
),
static_cast
<
std
::
size_t
>
(
Y
),
static_cast
<
std
::
size_t
>
(
X
),
static_cast
<
std
::
size_t
>
(
C
)});
const
auto
out_desc
=
HostTensorDescriptor
(
std
::
vector
<
std
::
size_t
>
{
static_cast
<
std
::
size_t
>
(
N
),
static_cast
<
std
::
size_t
>
(
Ho
),
static_cast
<
std
::
size_t
>
(
Wo
),
static_cast
<
std
::
size_t
>
(
K
)});
const
auto
bias_desc
=
HostTensorDescriptor
(
std
::
vector
<
std
::
size_t
>
{
static_cast
<
std
::
size_t
>
(
K
)});
auto
f_k
=
[
&
](
auto
k
)
{
for
(
int
n
=
0
;
n
<
N
;
++
n
)
{
for
(
int
ho
=
0
;
ho
<
Ho
;
++
ho
)
{
for
(
int
wo
=
0
;
wo
<
Wo
;
++
wo
)
{
double
v
=
0
;
for
(
int
c
=
0
;
c
<
C
;
++
c
)
{
for
(
int
y
=
0
;
y
<
Y
;
++
y
)
{
int
hi
=
ho
*
Stride
+
y
*
Dilation
-
Pad
;
for
(
int
x
=
0
;
x
<
X
;
++
x
)
{
int
wi
=
wo
*
Stride
+
x
*
Dilation
-
Pad
;
if
(
hi
>=
0
&&
hi
<
Hi
&&
wi
>=
0
&&
wi
<
Wi
)
{
double
in
=
in_ptr
[
in_desc
.
GetOffsetFromMultiIndex
(
n
,
hi
,
wi
,
c
)];
double
wei
=
weight_ptr
[
wei_desc
.
GetOffsetFromMultiIndex
(
k
,
y
,
x
,
c
)];
v
+=
in
*
wei
;
}
}
}
}
v
+=
bias_ptr
[
bias_desc
.
GetOffsetFromMultiIndex
(
k
)];
v
=
v
>
0
?
v
:
0
;
output_ptr
[
out_desc
.
GetOffsetFromMultiIndex
(
n
,
ho
,
wo
,
k
)]
=
v
;
}
}
}
};
make_ParallelTensorFunctor
(
f_k
,
K
)(
std
::
thread
::
hardware_concurrency
());
}
template
<
int
NDimSpatial
,
typename
InDataType
,
typename
WeiDataType
,
typename
OutDataType
,
typename
InLayout
,
typename
WeiLayout
,
typename
OutLayout
>
void
profile_conv_fwd_bias_relu_atomic_add_impl
(
int
do_verification
,
int
init_method
,
bool
do_log
,
bool
time_kernel
,
ck
::
index_t
N
,
ck
::
index_t
K
,
ck
::
index_t
C
,
std
::
vector
<
ck
::
index_t
>
input_spatial_lengths
,
std
::
vector
<
ck
::
index_t
>
filter_spatial_lengths
,
std
::
vector
<
ck
::
index_t
>
output_spatial_lengths
,
std
::
vector
<
ck
::
index_t
>
conv_filter_strides
,
std
::
vector
<
ck
::
index_t
>
conv_filter_dilations
,
std
::
vector
<
ck
::
index_t
>
input_left_pads
,
std
::
vector
<
ck
::
index_t
>
input_right_pads
)
{
const
ck
::
index_t
Y
=
filter_spatial_lengths
[
0
];
const
ck
::
index_t
X
=
filter_spatial_lengths
[
1
];
const
ck
::
index_t
Hi
=
input_spatial_lengths
[
0
];
const
ck
::
index_t
Wi
=
input_spatial_lengths
[
1
];
const
ck
::
index_t
Ho
=
output_spatial_lengths
[
0
];
const
ck
::
index_t
Wo
=
output_spatial_lengths
[
1
];
auto
f_host_tensor_descriptor
=
[](
std
::
size_t
N_
,
std
::
size_t
C_
,
std
::
size_t
H
,
std
::
size_t
W
,
auto
layout
)
{
if
constexpr
(
is_same
<
decltype
(
layout
),
ck
::
tensor_layout
::
convolution
::
NCHW
>::
value
||
is_same
<
decltype
(
layout
),
ck
::
tensor_layout
::
convolution
::
KCYX
>::
value
||
is_same
<
decltype
(
layout
),
ck
::
tensor_layout
::
convolution
::
NKHW
>::
value
)
{
return
HostTensorDescriptor
(
std
::
vector
<
std
::
size_t
>
({
N_
,
C_
,
H
,
W
}),
std
::
vector
<
std
::
size_t
>
({
C_
*
H
*
W
,
H
*
W
,
W
,
1
}));
}
else
if
constexpr
(
is_same
<
decltype
(
layout
),
tensor_layout
::
convolution
::
NHWC
>::
value
||
is_same
<
decltype
(
layout
),
tensor_layout
::
convolution
::
KYXC
>::
value
||
is_same
<
decltype
(
layout
),
tensor_layout
::
convolution
::
NHWK
>::
value
)
{
return
HostTensorDescriptor
(
std
::
vector
<
std
::
size_t
>
({
N_
,
C_
,
H
,
W
}),
std
::
vector
<
std
::
size_t
>
({
C_
*
H
*
W
,
1
,
W
*
C_
,
C_
}));
}
};
Tensor
<
InDataType
>
in_n_c_hi_wi
(
f_host_tensor_descriptor
(
N
,
C
,
Hi
,
Wi
,
InLayout
{}));
Tensor
<
WeiDataType
>
wei_k_c_y_x
(
f_host_tensor_descriptor
(
K
,
C
,
Y
,
X
,
WeiLayout
{}));
Tensor
<
OutDataType
>
out_n_k_ho_wo_host_result
(
f_host_tensor_descriptor
(
N
,
K
,
Ho
,
Wo
,
OutLayout
{}));
Tensor
<
OutDataType
>
out_n_k_ho_wo_device_result
(
f_host_tensor_descriptor
(
N
,
K
,
Ho
,
Wo
,
OutLayout
{}));
// bias: assume contiguous 1d vector
Tensor
<
OutDataType
>
bias_k
(
HostTensorDescriptor
(
std
::
vector
<
std
::
size_t
>
({
static_cast
<
std
::
size_t
>
(
K
)})));
std
::
cout
<<
"in_n_c_hi_wi: "
<<
in_n_c_hi_wi
.
mDesc
<<
std
::
endl
;
std
::
cout
<<
"wei_k_c_y_x: "
<<
wei_k_c_y_x
.
mDesc
<<
std
::
endl
;
std
::
cout
<<
"out_n_k_ho_wo: "
<<
out_n_k_ho_wo_host_result
.
mDesc
<<
std
::
endl
;
std
::
cout
<<
"bias_k: "
<<
bias_k
.
mDesc
<<
std
::
endl
;
switch
(
init_method
)
{
case
0
:
break
;
case
1
:
in_n_c_hi_wi
.
GenerateTensorValue
(
GeneratorTensor_2
<
InDataType
>
{
-
5
,
5
});
wei_k_c_y_x
.
GenerateTensorValue
(
GeneratorTensor_2
<
WeiDataType
>
{
-
5
,
5
});
bias_k
.
GenerateTensorValue
(
GeneratorTensor_2
<
OutDataType
>
{
-
5
,
5
});
break
;
default:
in_n_c_hi_wi
.
GenerateTensorValue
(
GeneratorTensor_3
<
InDataType
>
{
0.0
,
1.0
});
wei_k_c_y_x
.
GenerateTensorValue
(
GeneratorTensor_3
<
WeiDataType
>
{
-
0.5
,
0.5
});
bias_k
.
GenerateTensorValue
(
GeneratorTensor_3
<
OutDataType
>
{
0.0
,
1.0
});
}
using
InElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
WeiElementOp
=
ck
::
tensor_operation
::
element_wise
::
PassThrough
;
using
OutElementOp
=
ck
::
tensor_operation
::
element_wise
::
AddRelu
;
if
(
do_verification
)
{
cpu_conv_bias_relu_atomic_add
(
in_n_c_hi_wi
.
mData
.
data
(),
wei_k_c_y_x
.
mData
.
data
(),
out_n_k_ho_wo_host_result
.
mData
.
data
(),
bias_k
.
mData
.
data
(),
N
,
K
,
C
,
Y
,
X
,
Hi
,
Wi
,
Ho
,
Wo
,
conv_filter_strides
[
0
],
conv_filter_dilations
[
0
],
input_left_pads
[
0
]);
}
DeviceMem
in_device_buf
(
sizeof
(
InDataType
)
*
in_n_c_hi_wi
.
mDesc
.
GetElementSpace
());
DeviceMem
wei_device_buf
(
sizeof
(
WeiDataType
)
*
wei_k_c_y_x
.
mDesc
.
GetElementSpace
());
DeviceMem
out_device_buf
(
sizeof
(
OutDataType
)
*
out_n_k_ho_wo_device_result
.
mDesc
.
GetElementSpace
());
DeviceMem
bias_device_buf
(
sizeof
(
OutDataType
)
*
bias_k
.
mDesc
.
GetElementSpace
());
in_device_buf
.
ToDevice
(
in_n_c_hi_wi
.
mData
.
data
());
wei_device_buf
.
ToDevice
(
wei_k_c_y_x
.
mData
.
data
());
bias_device_buf
.
ToDevice
(
bias_k
.
mData
.
data
());
using
DeviceConvFwdBiasReluPtr
=
ck
::
tensor_operation
::
device
::
DeviceConvFwdBiasActivationPtr
<
InElementOp
,
WeiElementOp
,
OutElementOp
>
;
// add device operator instances
std
::
vector
<
DeviceConvFwdBiasReluPtr
>
op_ptrs
;
if
constexpr
(
ck
::
is_same_v
<
ck
::
remove_cv_t
<
InDataType
>
,
ck
::
half_t
>
&&
ck
::
is_same_v
<
ck
::
remove_cv_t
<
WeiDataType
>
,
ck
::
half_t
>
&&
ck
::
is_same_v
<
ck
::
remove_cv_t
<
OutDataType
>
,
ck
::
half_t
>
)
{
ck
::
tensor_operation
::
device
::
device_conv2d_fwd_bias_activation_atomic_add_instance
::
add_device_conv2d_fwd_xdl_c_shuffle_bias_relu_atomic_add_nhwc_kyxc_nhwk_f16_instances
(
op_ptrs
);
}
if
(
op_ptrs
.
size
()
<=
0
)
{
throw
std
::
runtime_error
(
"wrong! no device Conv instance found"
);
}
std
::
string
best_conv_name
;
float
best_ave_time
=
0
;
float
best_tflops
=
0
;
float
best_gb_per_sec
=
0
;
// profile device Conv instances
for
(
auto
&
op_ptr
:
op_ptrs
)
{
auto
argument_ptr
=
op_ptr
->
MakeArgumentPointer
(
static_cast
<
const
InDataType
*>
(
in_device_buf
.
GetDeviceBuffer
()),
static_cast
<
const
WeiDataType
*>
(
wei_device_buf
.
GetDeviceBuffer
()),
static_cast
<
OutDataType
*>
(
out_device_buf
.
GetDeviceBuffer
()),
static_cast
<
const
OutDataType
*>
(
bias_device_buf
.
GetDeviceBuffer
()),
N
,
K
,
C
,
input_spatial_lengths
,
filter_spatial_lengths
,
output_spatial_lengths
,
conv_filter_strides
,
conv_filter_dilations
,
input_left_pads
,
input_right_pads
,
InElementOp
{},
WeiElementOp
{},
OutElementOp
{});
auto
invoker_ptr
=
op_ptr
->
MakeInvokerPointer
();
if
(
op_ptr
->
IsSupportedArgument
(
argument_ptr
.
get
()))
{
std
::
string
conv_name
=
op_ptr
->
GetTypeString
();
float
ave_time
=
invoker_ptr
->
Run
(
argument_ptr
.
get
(),
StreamConfig
{
nullptr
,
time_kernel
});
std
::
size_t
flop
=
std
::
size_t
(
2
)
*
N
*
K
*
Ho
*
Wo
*
C
*
Y
*
X
;
std
::
size_t
num_btype
=
sizeof
(
InDataType
)
*
(
N
*
C
*
Hi
*
Wi
)
+
sizeof
(
WeiDataType
)
*
(
K
*
C
*
Y
*
X
)
+
sizeof
(
OutDataType
)
*
(
N
*
K
*
Ho
*
Wo
)
+
sizeof
(
OutDataType
)
*
(
K
);
float
tflops
=
static_cast
<
float
>
(
flop
)
/
1.E9
/
ave_time
;
float
gb_per_sec
=
num_btype
/
1.E6
/
ave_time
;
std
::
cout
<<
"Perf: "
<<
ave_time
<<
" ms, "
<<
tflops
<<
" TFlops, "
<<
gb_per_sec
<<
" GB/s, "
<<
conv_name
<<
std
::
endl
;
if
(
tflops
>
best_tflops
)
{
best_conv_name
=
conv_name
;
best_tflops
=
tflops
;
best_ave_time
=
ave_time
;
best_gb_per_sec
=
gb_per_sec
;
}
if
(
do_verification
)
{
out_device_buf
.
FromDevice
(
out_n_k_ho_wo_device_result
.
mData
.
data
());
ck
::
utils
::
check_err
(
out_n_k_ho_wo_device_result
.
mData
,
out_n_k_ho_wo_host_result
.
mData
);
if
(
do_log
)
{
LogRangeAsType
<
float
>
(
std
::
cout
<<
"in : "
,
in_n_c_hi_wi
.
mData
,
","
)
<<
std
::
endl
;
LogRangeAsType
<
float
>
(
std
::
cout
<<
"wei: "
,
wei_k_c_y_x
.
mData
,
","
)
<<
std
::
endl
;
LogRangeAsType
<
float
>
(
std
::
cout
<<
"out_host : "
,
out_n_k_ho_wo_host_result
.
mData
,
","
)
<<
std
::
endl
;
LogRangeAsType
<
float
>
(
std
::
cout
<<
"out_device: "
,
out_n_k_ho_wo_device_result
.
mData
,
","
)
<<
std
::
endl
;
}
}
}
}
std
::
cout
<<
"Best Perf: "
<<
best_ave_time
<<
" ms, "
<<
best_tflops
<<
" TFlops, "
<<
best_gb_per_sec
<<
" GB/s, "
<<
best_conv_name
<<
std
::
endl
;
}
}
// namespace profiler
}
// namespace ck
profiler/include/profile_conv_fwd_bias_relu_impl.hpp
View file @
7a3b49e5
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "check_err.hpp"
#include "config.hpp"
#include "device.hpp"
#include "host_tensor.hpp"
#include "host_tensor_generator.hpp"
#include "tensor_layout.hpp"
#include "device_tensor.hpp"
#include "element_wise_operation.hpp"
#include "device_conv_fwd_bias_activation.hpp"
#include "reference_conv_fwd_bias_activation.hpp"
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_conv_fwd_bias_activation.hpp"
#include "ck/library/utility/check_err.hpp"
#include "ck/library/host_tensor/device_memory.hpp"
#include "ck/library/host_tensor/host_tensor.hpp"
#include "ck/library/host_tensor/host_tensor_generator.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_conv_fwd_bias_activation.hpp"
namespace
ck
{
namespace
tensor_operation
{
...
...
profiler/include/profile_convnd_bwd_data_impl.hpp
View file @
7a3b49e5
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
#include "config.hpp"
#include "device.hpp"
#include "conv_util.hpp"
#include "host_tensor.hpp"
#include "host_tensor_generator.hpp"
#include "tensor_layout.hpp"
#include "device_tensor.hpp"
#include "device_conv_bwd_data.hpp"
#include "element_wise_operation.hpp"
#include "reference_conv_bwd_data.hpp"
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
#include "ck/tensor_operation/gpu/device/device_conv_bwd_data.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/utility/conv_util.hpp"
#include "ck/library/host_tensor/device_memory.hpp"
#include "ck/library/host_tensor/host_tensor.hpp"
#include "ck/library/host_tensor/host_tensor_generator.hpp"
#include "ck/library/reference_tensor_operation/cpu/reference_conv_bwd_data.hpp"
using
F16
=
ck
::
half_t
;
using
F32
=
float
;
using
BF16
=
ck
::
bhalf_t
;
using
INT8
=
int8_t
;
namespace
ck
{
namespace
tensor_operation
{
namespace
device
{
...
...
profiler/include/profile_convnd_fwd.hpp
View file @
7a3b49e5
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
#pragma once
namespace
ck
{
...
...
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