Skip to content
体验新版
项目
组织
正在加载...
登录
切换导航
打开侧边栏
PaddlePaddle
PaddleDetection
提交
06f3c857
P
PaddleDetection
项目概览
PaddlePaddle
/
PaddleDetection
大约 1 年 前同步成功
通知
695
Star
11112
Fork
2696
代码
文件
提交
分支
Tags
贡献者
分支图
Diff
Issue
184
列表
看板
标记
里程碑
合并请求
40
Wiki
0
Wiki
分析
仓库
DevOps
项目成员
Pages
P
PaddleDetection
项目概览
项目概览
详情
发布
仓库
仓库
文件
提交
分支
标签
贡献者
分支图
比较
Issue
184
Issue
184
列表
看板
标记
里程碑
合并请求
40
合并请求
40
Pages
分析
分析
仓库分析
DevOps
Wiki
0
Wiki
成员
成员
收起侧边栏
关闭侧边栏
动态
分支图
创建新Issue
提交
Issue看板
提交
06f3c857
编写于
3月 01, 2019
作者:
C
chengduo
提交者:
ceci3
3月 04, 2019
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Add Event for TensorCopy (#15953)
Add Event for TensorCopy
上级
1a5f31b5
变更
8
显示空白变更内容
内联
并排
Showing
8 changed file
with
111 addition
and
23 deletion
+111
-23
paddle/fluid/framework/CMakeLists.txt
paddle/fluid/framework/CMakeLists.txt
+2
-2
paddle/fluid/framework/tensor_util.cc
paddle/fluid/framework/tensor_util.cc
+7
-0
paddle/fluid/memory/CMakeLists.txt
paddle/fluid/memory/CMakeLists.txt
+1
-1
paddle/fluid/memory/memcpy.cc
paddle/fluid/memory/memcpy.cc
+20
-0
paddle/fluid/operators/reader/buffered_reader.cc
paddle/fluid/operators/reader/buffered_reader.cc
+14
-9
paddle/fluid/platform/device_tracer.cc
paddle/fluid/platform/device_tracer.cc
+54
-9
paddle/fluid/platform/device_tracer.h
paddle/fluid/platform/device_tracer.h
+12
-1
tools/timeline.py
tools/timeline.py
+1
-1
未找到文件。
paddle/fluid/framework/CMakeLists.txt
浏览文件 @
06f3c857
...
...
@@ -38,10 +38,10 @@ if(WITH_GPU)
nv_library
(
tensor SRCS tensor.cc .tensor_util.cu DEPS place memory data_type device_context
)
add_dependencies
(
tensor tensor_util
)
else
()
nv_library
(
tensor SRCS tensor.cc tensor_util.cu DEPS place memory data_type device_context
)
nv_library
(
tensor SRCS tensor.cc tensor_util.cu DEPS place memory data_type device_context
profiler
)
endif
(
WIN32
)
else
()
cc_library
(
tensor SRCS tensor.cc tensor_util.cc DEPS place memory data_type device_context
)
cc_library
(
tensor SRCS tensor.cc tensor_util.cc DEPS place memory data_type device_context
profiler
)
endif
()
cc_test
(
tensor_test SRCS tensor_test.cc DEPS tensor
)
...
...
paddle/fluid/framework/tensor_util.cc
浏览文件 @
06f3c857
...
...
@@ -14,8 +14,11 @@
#include "paddle/fluid/framework/tensor_util.h"
#include <algorithm>
#include <limits>
#include <memory>
#include <utility>
#include <vector>
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/platform/profiler.h"
namespace
paddle
{
namespace
framework
{
...
...
@@ -135,16 +138,19 @@ void TensorCopySync(const Tensor& src, const platform::Place& dst_place,
#ifdef PADDLE_WITH_CUDA
else
if
(
platform
::
is_gpu_place
(
src_place
)
&&
// NOLINT
platform
::
is_cpu_place
(
dst_place
))
{
platform
::
RecordEvent
record_event
(
"TensorCopy:GPU->CPU"
);
auto
src_gpu_place
=
boost
::
get
<
platform
::
CUDAPlace
>
(
src_place
);
auto
dst_cpu_place
=
boost
::
get
<
platform
::
CPUPlace
>
(
dst_place
);
memory
::
Copy
(
dst_cpu_place
,
dst_ptr
,
src_gpu_place
,
src_ptr
,
size
,
nullptr
);
}
else
if
(
platform
::
is_cpu_place
(
src_place
)
&&
platform
::
is_gpu_place
(
dst_place
))
{
platform
::
RecordEvent
record_event
(
"TensorCopy:CPU->GPU"
);
auto
src_cpu_place
=
boost
::
get
<
platform
::
CPUPlace
>
(
src_place
);
auto
dst_gpu_place
=
boost
::
get
<
platform
::
CUDAPlace
>
(
dst_place
);
memory
::
Copy
(
dst_gpu_place
,
dst_ptr
,
src_cpu_place
,
src_ptr
,
size
,
nullptr
);
}
else
if
(
platform
::
is_gpu_place
(
src_place
)
&&
platform
::
is_gpu_place
(
dst_place
))
{
platform
::
RecordEvent
record_event
(
"TensorCopy:GPU->GPU"
);
if
(
src_ptr
==
dst_ptr
&&
platform
::
is_same_place
(
src_place
,
dst_place
))
{
VLOG
(
3
)
<<
"Skip copy the same data from "
<<
src_place
<<
" to "
<<
dst_place
;
...
...
@@ -155,6 +161,7 @@ void TensorCopySync(const Tensor& src, const platform::Place& dst_place,
memory
::
Copy
(
dst_gpu_place
,
dst_ptr
,
src_gpu_place
,
src_ptr
,
size
,
nullptr
);
}
else
if
(
platform
::
is_cuda_pinned_place
(
src_place
)
&&
platform
::
is_gpu_place
(
dst_place
))
{
platform
::
RecordEvent
record_event
(
"TensorCopy:CUDAPinned->GPU"
);
auto
src_pinned_place
=
boost
::
get
<
platform
::
CUDAPinnedPlace
>
(
src_place
);
auto
dst_gpu_place
=
boost
::
get
<
platform
::
CUDAPlace
>
(
dst_place
);
memory
::
Copy
(
dst_gpu_place
,
dst_ptr
,
src_pinned_place
,
src_ptr
,
size
,
...
...
paddle/fluid/memory/CMakeLists.txt
浏览文件 @
06f3c857
add_subdirectory
(
detail
)
add_subdirectory
(
allocation
)
cc_library
(
malloc SRCS malloc.cc DEPS place enforce allocator_facade
)
cc_library
(
malloc SRCS malloc.cc DEPS place enforce allocator_facade
profiler
)
cc_library
(
memcpy SRCS memcpy.cc DEPS place
)
cc_library
(
memory
...
...
paddle/fluid/memory/memcpy.cc
浏览文件 @
06f3c857
...
...
@@ -15,6 +15,7 @@ limitations under the License. */
#include "paddle/fluid/memory/memcpy.h"
#include <cstring> // for memcpy
#include "paddle/fluid/platform/profiler.h"
namespace
paddle
{
namespace
memory
{
...
...
@@ -29,14 +30,23 @@ void Copy<platform::CPUPlace, platform::CPUPlace>(platform::CPUPlace, void* dst,
#ifdef PADDLE_WITH_CUDA
static
constexpr
size_t
kMaxGpuAsyncCopyBytes
=
64
*
1024
;
// 64K
// NOTE(zcd): Do not use GpuMemcpySync as much as possible.
// because GpuMemcpySync issues the copying command to the default stream,
// which will make two commands from different streams cannot run concurrently.
// Reference:
// https://devblogs.nvidia.com/gpu-pro-tip-cuda-7-streams-simplify-concurrency/
template
<
>
void
Copy
<
platform
::
CPUPlace
,
platform
::
CUDAPlace
>
(
platform
::
CPUPlace
dst_place
,
void
*
dst
,
platform
::
CUDAPlace
src_place
,
const
void
*
src
,
size_t
num
,
cudaStream_t
stream
)
{
platform
::
SetDeviceId
(
src_place
.
device
);
if
(
stream
)
{
platform
::
RecordEvent
record_event
(
"GpuMemcpyAsync:GPU->CPU"
);
platform
::
GpuMemcpyAsync
(
dst
,
src
,
num
,
cudaMemcpyDeviceToHost
,
stream
);
}
else
{
platform
::
RecordEvent
record_event
(
"GpuMemcpySync:GPU->CPU"
);
platform
::
GpuMemcpySync
(
dst
,
src
,
num
,
cudaMemcpyDeviceToHost
);
// FIXME(zjl): do we really need it?
if
(
num
<=
kMaxGpuAsyncCopyBytes
)
{
...
...
@@ -51,8 +61,10 @@ void Copy<platform::CUDAPlace, platform::CPUPlace>(
const
void
*
src
,
size_t
num
,
cudaStream_t
stream
)
{
platform
::
SetDeviceId
(
dst_place
.
device
);
if
(
stream
)
{
platform
::
RecordEvent
record_event
(
"GpuMemcpyAsync:CPU->GPU"
);
platform
::
GpuMemcpyAsync
(
dst
,
src
,
num
,
cudaMemcpyHostToDevice
,
stream
);
}
else
{
platform
::
RecordEvent
record_event
(
"GpuMemcpySync:CPU->GPU"
);
platform
::
GpuMemcpySync
(
dst
,
src
,
num
,
cudaMemcpyHostToDevice
);
// FIXME(zjl): do we really need it?
if
(
num
<=
kMaxGpuAsyncCopyBytes
)
{
...
...
@@ -68,15 +80,19 @@ void Copy<platform::CUDAPlace, platform::CUDAPlace>(
if
(
dst_place
==
src_place
)
{
platform
::
SetDeviceId
(
src_place
.
device
);
if
(
stream
)
{
platform
::
RecordEvent
record_event
(
"GpuMemcpyAsync(same_gpu):GPU->GPU"
);
platform
::
GpuMemcpyAsync
(
dst
,
src
,
num
,
cudaMemcpyDeviceToDevice
,
stream
);
}
else
{
platform
::
RecordEvent
record_event
(
"GpuMemcpySync(same_gpu):GPU->GPU"
);
platform
::
GpuMemcpySync
(
dst
,
src
,
num
,
cudaMemcpyDeviceToDevice
);
}
}
else
{
if
(
stream
)
{
platform
::
RecordEvent
record_event
(
"GpuMemcpyPeerAsync:GPU->GPU"
);
platform
::
GpuMemcpyPeerAsync
(
dst
,
dst_place
.
device
,
src
,
src_place
.
device
,
num
,
stream
);
}
else
{
platform
::
RecordEvent
record_event
(
"GpuMemcpyPeerSync:GPU->GPU"
);
platform
::
GpuMemcpyPeerSync
(
dst
,
dst_place
.
device
,
src
,
src_place
.
device
,
num
);
}
...
...
@@ -111,8 +127,10 @@ void Copy<platform::CUDAPinnedPlace, platform::CUDAPlace>(
cudaStream_t
stream
)
{
platform
::
SetDeviceId
(
src_place
.
device
);
if
(
stream
)
{
platform
::
RecordEvent
record_event
(
"GpuMemcpyAsync:GPU->CUDAPinned"
);
platform
::
GpuMemcpyAsync
(
dst
,
src
,
num
,
cudaMemcpyDeviceToHost
,
stream
);
}
else
{
platform
::
RecordEvent
record_event
(
"GpuMemcpySync:GPU->CUDAPinned"
);
platform
::
GpuMemcpySync
(
dst
,
src
,
num
,
cudaMemcpyDeviceToHost
);
}
}
...
...
@@ -124,8 +142,10 @@ void Copy<platform::CUDAPlace, platform::CUDAPinnedPlace>(
cudaStream_t
stream
)
{
platform
::
SetDeviceId
(
dst_place
.
device
);
if
(
stream
)
{
platform
::
RecordEvent
record_event
(
"GpuMemcpyAsync:CUDAPinned->GPU"
);
platform
::
GpuMemcpyAsync
(
dst
,
src
,
num
,
cudaMemcpyHostToDevice
,
stream
);
}
else
{
platform
::
RecordEvent
record_event
(
"GpuMemcpySync:CUDAPinned->GPU"
);
platform
::
GpuMemcpySync
(
dst
,
src
,
num
,
cudaMemcpyHostToDevice
);
}
}
...
...
paddle/fluid/operators/reader/buffered_reader.cc
浏览文件 @
06f3c857
...
...
@@ -13,9 +13,11 @@
// limitations under the License.
#include "paddle/fluid/operators/reader/buffered_reader.h"
#include <memory>
#include <vector>
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/platform/profiler.h"
namespace
paddle
{
namespace
operators
{
namespace
reader
{
...
...
@@ -49,9 +51,10 @@ BufferedReader::BufferedReader(
.
Get
(
place_
)))
->
stream
();
events
.
resize
(
buffer_size
);
for
(
auto
&
event
:
events
)
PADDLE_ENFORCE
(
cudaStreamCreate
(
&
stream
));
for
(
auto
&
event
:
events
)
{
PADDLE_ENFORCE
(
cudaEventCreateWithFlags
(
&
event
,
cudaEventDisableTiming
));
PADDLE_ENFORCE
(
cudaStreamCreateWithFlags
(
&
stream
,
cudaStreamNonBlocking
));
}
}
#endif
cpu_buffer_
.
resize
(
buffer_size
);
...
...
@@ -83,12 +86,15 @@ void BufferedReader::ReadAsync(size_t i) {
#ifdef PADDLE_WITH_CUDA
// NOTE(liangdun): using async copy instead of TensorCopySync
// TensorCopySync would block other stream
// TensorCopySync would block other stream, because TensorCopySync
// issues the copying command to the default stream, it will make two
// commands from different streams cannot run concurrently.
if
(
platform
::
is_gpu_place
(
place_
))
{
platform
::
SetDeviceId
(
boost
::
get
<
platform
::
CUDAPlace
>
(
place_
).
device
);
PADDLE_ENFORCE
(
cudaStreamWaitEvent
(
stream
,
events
[
i
],
0
));
TensorVec
&
gpu
=
gpu_buffer_
[
i
];
gpu
.
resize
(
cpu
.
size
());
platform
::
RecordEvent
record_event
(
"BufferedReader:MemoryCopy"
);
for
(
size_t
i
=
0
;
i
<
cpu
.
size
();
++
i
)
{
gpu
[
i
].
Resize
(
cpu
[
i
].
dims
());
gpu
[
i
].
set_layout
(
cpu
[
i
].
layout
());
...
...
@@ -97,20 +103,19 @@ void BufferedReader::ReadAsync(size_t i) {
auto
gpu_ptr
=
gpu
[
i
].
mutable_data
(
place_
,
cpu
[
i
].
type
());
auto
size
=
cpu
[
i
].
numel
()
*
paddle
::
framework
::
SizeOfType
(
cpu
[
i
].
type
());
if
(
platform
::
is_cuda_pinned_place
(
cpu_place
))
if
(
platform
::
is_cuda_pinned_place
(
cpu_place
))
{
memory
::
Copy
(
boost
::
get
<
platform
::
CUDAPlace
>
(
place_
),
gpu_ptr
,
boost
::
get
<
platform
::
CUDAPinnedPlace
>
(
cpu_place
),
cpu_ptr
,
size
,
stream
);
else
if
((
platform
::
is_gpu_place
(
cpu_place
)))
}
else
if
((
platform
::
is_gpu_place
(
cpu_place
)))
{
memory
::
Copy
(
boost
::
get
<
platform
::
CUDAPlace
>
(
place_
),
gpu_ptr
,
boost
::
get
<
platform
::
CUDAPlace
>
(
cpu_place
),
cpu_ptr
,
size
,
stream
);
else
// if cpu place is not pinned, async copy is slower than sync copy,
// so we use sync copy instead.
}
else
{
memory
::
Copy
(
boost
::
get
<
platform
::
CUDAPlace
>
(
place_
),
gpu_ptr
,
boost
::
get
<
platform
::
CPUPlace
>
(
cpu_place
),
cpu_ptr
,
size
,
0
);
stream
);
}
gpu
[
i
].
set_lod
(
cpu
[
i
].
lod
());
}
PADDLE_ENFORCE
(
cudaStreamSynchronize
(
stream
));
...
...
paddle/fluid/platform/device_tracer.cc
浏览文件 @
06f3c857
...
...
@@ -30,7 +30,6 @@ limitations under the License. */
#include "glog/logging.h"
#include "google/protobuf/text_format.h"
#include "paddle/fluid/framework/block_desc.h"
#include "paddle/fluid/platform/profiler.h"
#include "paddle/fluid/string/printf.h"
namespace
paddle
{
...
...
@@ -222,19 +221,24 @@ void CUPTIAPI bufferCompleted(CUcontext ctx, uint32_t streamId, uint8_t *buffer,
}
case
CUPTI_ACTIVITY_KIND_DRIVER
:
{
auto
*
api
=
reinterpret_cast
<
const
CUpti_ActivityAPI
*>
(
record
);
if
(
api
->
start
!=
0
&&
api
->
end
!=
0
)
// -1 device id represents
CUDA
api call
tracer
->
Add
CPU
Records
(
if
(
api
->
start
!=
0
&&
api
->
end
!=
0
)
{
// -1 device id represents
ActiveKind
api call
tracer
->
Add
ActiveKind
Records
(
DriverKind
(
api
->
cbid
),
api
->
start
,
api
->
end
,
-
1
,
GetThreadIdFromSystemThreadId
(
api
->
threadId
));
GetThreadIdFromSystemThreadId
(
api
->
threadId
),
api
->
correlationId
);
}
break
;
}
case
CUPTI_ACTIVITY_KIND_RUNTIME
:
{
auto
*
api
=
reinterpret_cast
<
const
CUpti_ActivityAPI
*>
(
record
);
if
(
api
->
start
!=
0
&&
api
->
end
!=
0
)
tracer
->
AddCPURecords
(
if
(
api
->
start
!=
0
&&
api
->
end
!=
0
)
{
// -1 device id represents ActiveKind api call
tracer
->
AddActiveKindRecords
(
RuntimeKind
(
api
->
cbid
),
api
->
start
,
api
->
end
,
-
1
,
GetThreadIdFromSystemThreadId
(
api
->
threadId
));
GetThreadIdFromSystemThreadId
(
api
->
threadId
),
api
->
correlationId
);
}
break
;
}
default:
{
break
;
}
...
...
@@ -313,6 +317,25 @@ class DeviceTracerImpl : public DeviceTracer {
stream_id
,
correlation_id
,
bytes
});
}
void
AddActiveKindRecords
(
const
std
::
string
&
anno
,
uint64_t
start_ns
,
uint64_t
end_ns
,
int64_t
device_id
,
int64_t
thread_id
,
uint32_t
correlation_id
)
{
if
(
anno
.
empty
())
{
VLOG
(
1
)
<<
"Empty timeline annotation."
;
return
;
}
thread_local
std
::
forward_list
<
ActiveKindRecord
>
*
local_active_kind_records
=
nullptr
;
if
(
local_active_kind_records
==
nullptr
)
{
std
::
lock_guard
<
std
::
mutex
>
l
(
trace_mu_
);
active_kind_records_
.
emplace_front
();
local_active_kind_records
=
&
active_kind_records_
.
front
();
}
// lock is not needed, only one thread call this function.
local_active_kind_records
->
push_front
(
ActiveKindRecord
{
anno
,
start_ns
,
end_ns
,
device_id
,
thread_id
,
correlation_id
});
}
void
AddKernelRecords
(
std
::
string
name
,
uint64_t
start
,
uint64_t
end
,
int64_t
device_id
,
int64_t
stream_id
,
uint32_t
correlation_id
)
{
...
...
@@ -355,6 +378,7 @@ class DeviceTracerImpl : public DeviceTracer {
}
const
std
::
vector
<
int
>
cbids
{
CUPTI_RUNTIME_TRACE_CBID_cudaMemcpy_v3020
,
CUPTI_RUNTIME_TRACE_CBID_cudaSetupArgument_v3020
,
CUPTI_RUNTIME_TRACE_CBID_cudaMemcpyAsync_v3020
,
CUPTI_RUNTIME_TRACE_CBID_cudaMemset_v3020
,
CUPTI_RUNTIME_TRACE_CBID_cudaMemsetAsync_v3020
,
...
...
@@ -385,6 +409,7 @@ class DeviceTracerImpl : public DeviceTracer {
correlations_
.
clear
();
for
(
auto
&
tmp
:
correlations_pairs
)
tmp
.
clear
();
for
(
auto
&
tmp
:
cpu_records_
)
tmp
.
clear
();
for
(
auto
&
tmp
:
active_kind_records_
)
tmp
.
clear
();
}
void
GenEventKernelCudaElapsedTime
()
{
...
...
@@ -437,7 +462,7 @@ class DeviceTracerImpl : public DeviceTracer {
event
->
set_device_id
(
r
.
device_id
);
}
VLOG
(
1
)
<<
"KernelRecord event miss: "
<<
miss
<<
" find: "
<<
find
;
for
(
auto
&
tmp
:
cpu_records_
)
for
(
auto
&
tmp
:
cpu_records_
)
{
for
(
const
CPURecord
&
r
:
tmp
)
{
auto
*
event
=
profile_pb
.
add_events
();
event
->
set_type
(
proto
::
Event
::
CPU
);
...
...
@@ -447,6 +472,24 @@ class DeviceTracerImpl : public DeviceTracer {
event
->
set_sub_device_id
(
r
.
thread_id
);
event
->
set_device_id
(
r
.
device_id
);
}
}
for
(
auto
&
tmp
:
active_kind_records_
)
{
for
(
const
ActiveKindRecord
&
r
:
tmp
)
{
auto
*
event
=
profile_pb
.
add_events
();
event
->
set_type
(
proto
::
Event
::
CPU
);
auto
c
=
correlations_
.
find
(
r
.
correlation_id
);
if
(
c
!=
correlations_
.
end
()
&&
c
->
second
!=
nullptr
)
{
event
->
set_name
(
c
->
second
->
name
());
event
->
set_detail_info
(
r
.
name
);
}
else
{
event
->
set_name
(
r
.
name
);
}
event
->
set_start_ns
(
r
.
start_ns
);
event
->
set_end_ns
(
r
.
end_ns
);
event
->
set_sub_device_id
(
r
.
thread_id
);
event
->
set_device_id
(
r
.
device_id
);
}
}
miss
=
find
=
0
;
for
(
const
MemRecord
&
r
:
mem_records_
)
{
auto
*
event
=
profile_pb
.
add_events
();
...
...
@@ -510,6 +553,7 @@ class DeviceTracerImpl : public DeviceTracer {
std
::
forward_list
<
KernelRecord
>
kernel_records_
;
std
::
forward_list
<
MemRecord
>
mem_records_
;
std
::
forward_list
<
std
::
forward_list
<
CPURecord
>>
cpu_records_
;
std
::
forward_list
<
std
::
forward_list
<
ActiveKindRecord
>>
active_kind_records_
;
std
::
forward_list
<
std
::
forward_list
<
std
::
pair
<
uint32_t
,
Event
*>>>
correlations_pairs
;
std
::
unordered_map
<
uint32_t
,
Event
*>
correlations_
;
...
...
@@ -613,6 +657,7 @@ void initCuptiCbidStr() {
REGISTER_RUNTIME_CBID_STR
(
cudaUnbindTexture_v3020
);
REGISTER_RUNTIME_CBID_STR
(
cudaSetupArgument_v3020
);
REGISTER_RUNTIME_CBID_STR
(
cudaLaunch_v3020
);
REGISTER_RUNTIME_CBID_STR
(
cudaDeviceGetPCIBusId_v4010
);
#if CUDA_VERSION >= 9000
REGISTER_RUNTIME_CBID_STR
(
cudaLaunchCooperativeKernel_v9000
);
REGISTER_RUNTIME_CBID_STR
(
cudaLaunchCooperativeKernelMultiDevice_v9000
);
...
...
paddle/fluid/platform/device_tracer.h
浏览文件 @
06f3c857
...
...
@@ -63,7 +63,14 @@ class DeviceTracer {
uint32_t
correlation_id
;
uint64_t
bytes
;
};
struct
ActiveKindRecord
{
std
::
string
name
;
uint64_t
start_ns
;
uint64_t
end_ns
;
int64_t
device_id
;
int64_t
thread_id
;
uint32_t
correlation_id
;
};
virtual
~
DeviceTracer
()
{}
// Needs to be called once before use.
virtual
void
Enable
()
=
0
;
...
...
@@ -85,6 +92,10 @@ class DeviceTracer {
virtual
void
AddCPURecords
(
const
std
::
string
&
anno
,
uint64_t
start_ns
,
uint64_t
end_ns
,
int64_t
device_id
,
int64_t
thread_id
)
=
0
;
virtual
void
AddActiveKindRecords
(
const
std
::
string
&
anno
,
uint64_t
start_ns
,
uint64_t
end_ns
,
int64_t
device_id
,
int64_t
thread_id
,
uint32_t
correlation_id
)
=
0
;
// Add a cuda kernel stats. `correlation_id` will be mapped to annotation
// added before for human readability.
...
...
tools/timeline.py
浏览文件 @
06f3c857
...
...
@@ -131,7 +131,7 @@ class Timeline(object):
if
(
k
,
event
.
device_id
,
"CPU"
)
not
in
self
.
_devices
:
pid
=
self
.
_allocate_pid
()
self
.
_devices
[(
k
,
event
.
device_id
,
"CPU"
)]
=
pid
# -1 device id represents CUDA
api call
# -1 device id represents CUDA
API(RunTime) call.(e.g. cudaLaunch, cudaMemcpy)
if
event
.
device_id
==
-
1
:
self
.
_chrome_trace
.
emit_pid
(
"%s:cuda_api"
%
k
,
pid
)
else
:
...
...
编辑
预览
Markdown
is supported
0%
请重试
或
添加新附件
.
添加附件
取消
You are about to add
0
people
to the discussion. Proceed with caution.
先完成此消息的编辑!
取消
想要评论请
注册
或
登录