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体验新版 GitCode,发现更多精彩内容 >>
提交
8393c19c
编写于
11月 21, 2016
作者:
L
liaogang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Add recursive mutex and counter for gpu profiler
上级
9670b9a1
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
42 addition
and
15 deletion
+42
-15
doc/optimization/gpu_profiling.rst
doc/optimization/gpu_profiling.rst
+2
-1
doc/optimization/nvprof.png
doc/optimization/nvprof.png
+0
-0
paddle/math/tests/test_GpuProfiler.cpp
paddle/math/tests/test_GpuProfiler.cpp
+16
-8
paddle/utils/Stat.cpp
paddle/utils/Stat.cpp
+18
-0
paddle/utils/Stat.h
paddle/utils/Stat.h
+6
-6
未找到文件。
doc/optimization/gpu_profiling.rst
浏览文件 @
8393c19c
...
@@ -24,7 +24,7 @@ Why we need profiling?
...
@@ -24,7 +24,7 @@ Why we need profiling?
======================
======================
Since training deep neural network typically take a very long time to get over, performance is gradually becoming
Since training deep neural network typically take a very long time to get over, performance is gradually becoming
the most important thing in deep learning field. The first step to improve performance is to understand what parts
the most important thing in deep learning field. The first step to improve performance is to understand what parts
are slow.
N
o point in improving performance of a region which doesn’t take much time!
are slow.
There is n
o point in improving performance of a region which doesn’t take much time!
How to do profiling?
How to do profiling?
...
@@ -59,6 +59,7 @@ above profilers.
...
@@ -59,6 +59,7 @@ above profilers.
The above code snippet includes two methods, you can use any of them to profile the regions of interest.
The above code snippet includes two methods, you can use any of them to profile the regions of interest.
1. :code:`REGISTER_TIMER_INFO` is a built-in timer wrapper which can calculate the time overhead of both cpu functions and cuda kernels.
1. :code:`REGISTER_TIMER_INFO` is a built-in timer wrapper which can calculate the time overhead of both cpu functions and cuda kernels.
2. :code:`REGISTER_GPU_PROFILER` is a general purpose wrapper object of :code:`cudaProfilerStart` and :code:`cudaProfilerStop` to avoid
2. :code:`REGISTER_GPU_PROFILER` is a general purpose wrapper object of :code:`cudaProfilerStart` and :code:`cudaProfilerStop` to avoid
program crashes when CPU version of PaddlePaddle invokes them.
program crashes when CPU version of PaddlePaddle invokes them.
...
...
doc/optimization/nvprof.png
已删除
100644 → 0
浏览文件 @
9670b9a1
476.3 KB
paddle/math/tests/test_GpuProfiler.cpp
浏览文件 @
8393c19c
...
@@ -70,10 +70,14 @@ void testBilinearFwdBwd(int numSamples, int imgSizeH, int imgSizeW,
...
@@ -70,10 +70,14 @@ void testBilinearFwdBwd(int numSamples, int imgSizeH, int imgSizeW,
input
->
randomizeUniform
();
input
->
randomizeUniform
();
inputGpu
->
copyFrom
(
*
input
);
inputGpu
->
copyFrom
(
*
input
);
target
->
bilinearForward
(
*
input
,
imgSizeH
,
imgSizeW
,
{
2
*
imgSizeH
,
2
*
imgSizeW
,
channels
,
ratioH
,
ratioW
);
// nvprof: GPU Proflier
targetGpu
->
bilinearForward
(
*
inputGpu
,
imgSizeH
,
imgSizeW
,
REGISTER_GPU_PROFILER
(
"testBilinearFwdBwd"
);
2
*
imgSizeH
,
2
*
imgSizeW
,
channels
,
ratioH
,
ratioW
);
target
->
bilinearForward
(
*
input
,
imgSizeH
,
imgSizeW
,
2
*
imgSizeH
,
2
*
imgSizeW
,
channels
,
ratioH
,
ratioW
);
targetGpu
->
bilinearForward
(
*
inputGpu
,
imgSizeH
,
imgSizeW
,
2
*
imgSizeH
,
2
*
imgSizeW
,
channels
,
ratioH
,
ratioW
);
}
// check
// check
targetCheck
->
copyFrom
(
*
targetGpu
);
targetCheck
->
copyFrom
(
*
targetGpu
);
...
@@ -104,25 +108,29 @@ void testBilinearFwdBwd(int numSamples, int imgSizeH, int imgSizeW,
...
@@ -104,25 +108,29 @@ void testBilinearFwdBwd(int numSamples, int imgSizeH, int imgSizeW,
MatrixCheckErr
(
*
inputGrad
,
*
targetCheckGrad
);
MatrixCheckErr
(
*
inputGrad
,
*
targetCheckGrad
);
}
}
TEST
(
Profiler
,
BilinearFwdBwd
)
{
TEST
(
Profiler
,
test
BilinearFwdBwd
)
{
auto
numSamples
=
10
;
auto
numSamples
=
10
;
auto
channels
=
16
;
auto
channels
=
16
;
auto
imgSize
=
64
;
auto
imgSize
=
64
;
{
{
// nvprof: GPU Proflier
// nvprof: GPU Proflier
REGISTER_GPU_PROFILER
(
"testBilinearFwdBwd"
,
REGISTER_GPU_PROFILER
(
"testBilinearFwdBwd"
);
"numSamples = 10, channels = 16, imgSizeX = 64, imgSizeY = 64"
);
// Paddle built-in timer
// Paddle built-in timer
REGISTER_TIMER_INFO
(
"testBilinearFwdBwd"
,
REGISTER_TIMER_INFO
(
"testBilinearFwdBwd"
,
"numSamples = 10, channels = 16, imgSizeX = 64, imgSizeY = 64"
);
"numSamples = 10, channels = 16, imgSizeX = 64, imgSizeY = 64"
);
testBilinearFwdBwd
(
numSamples
,
imgSize
,
imgSize
,
channels
);
testBilinearFwdBwd
(
numSamples
,
imgSize
,
imgSize
,
channels
);
}
}
globalStat
.
print
Status
(
"testBilinearFwdBwd"
);
globalStat
.
print
AllStatus
(
);
}
}
int
main
(
int
argc
,
char
**
argv
)
{
int
main
(
int
argc
,
char
**
argv
)
{
testing
::
InitGoogleTest
(
&
argc
,
argv
);
testing
::
InitGoogleTest
(
&
argc
,
argv
);
initMain
(
argc
,
argv
);
initMain
(
argc
,
argv
);
// nvprof: GPU Proflier
REGISTER_GPU_PROFILER
(
"RecursiveProfilingTest"
,
"numSamples = 10, channels = 16, imgSizeX = 64, imgSizeY = 64"
);
return
RUN_ALL_TESTS
();
return
RUN_ALL_TESTS
();
}
}
...
...
paddle/utils/Stat.cpp
浏览文件 @
8393c19c
...
@@ -203,4 +203,22 @@ StatInfo::~StatInfo() {
...
@@ -203,4 +203,22 @@ StatInfo::~StatInfo() {
}
}
}
}
static
unsigned
g_profileCount
=
0
;
static
std
::
recursive_mutex
g_profileMutex
;
GpuProfiler
::
GpuProfiler
(
std
::
string
statName
,
std
::
string
info
)
:
guard_
(
g_profileMutex
)
{
if
(
++
g_profileCount
==
1
)
{
LOG
(
INFO
)
<<
"Enable GPU Profiler Stat: ["
<<
statName
<<
"] "
<<
info
;
hl_profiler_start
();
}
}
GpuProfiler
::~
GpuProfiler
()
{
if
(
--
g_profileCount
==
0
)
{
hl_profiler_end
();
}
}
}
// namespace paddle
}
// namespace paddle
paddle/utils/Stat.h
浏览文件 @
8393c19c
...
@@ -283,8 +283,10 @@ inline StatSet& registerTimerArg2(uint64_t threshold = -1,
...
@@ -283,8 +283,10 @@ inline StatSet& registerTimerArg2(uint64_t threshold = -1,
class
GpuProfiler
final
{
class
GpuProfiler
final
{
public:
public:
GpuProfiler
()
{
hl_profiler_start
();
}
GpuProfiler
(
std
::
string
statName
,
std
::
string
info
);
~
GpuProfiler
()
{
hl_profiler_end
();
}
~
GpuProfiler
();
private:
std
::
lock_guard
<
std
::
recursive_mutex
>
guard_
;
};
};
#ifdef PADDLE_DISABLE_PROFILER
#ifdef PADDLE_DISABLE_PROFILER
...
@@ -293,10 +295,8 @@ public:
...
@@ -293,10 +295,8 @@ public:
#else
#else
#define REGISTER_GPU_PROFILER(statName, ...) \
#define REGISTER_GPU_PROFILER(statName, ...) \
LOG(INFO) << "Enable GPU Profiler Stat: [" \
GpuProfiler __gpuProfiler(statName, #__VA_ARGS__);
<< statName << "] " << #__VA_ARGS__; \
GpuProfiler __gpuProfiler;
#endif // DISABLE_PROFILER
#endif // DISABLE_PROFILER
...
...
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