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体验新版 GitCode,发现更多精彩内容 >>
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907433a7
编写于
3月 16, 2023
作者:
H
Huang Jiyi
提交者:
GitHub
3月 16, 2023
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差异文件
[phi decoupling] remove fluid gpu_info usage in phi (#51699)
* remove fluid thread_data_registry * update * fix bug
上级
3f3372b6
变更
12
隐藏空白更改
内联
并排
Showing
12 changed file
with
79 addition
and
204 deletion
+79
-204
paddle/fluid/framework/new_executor/workqueue/thread_data_registry.h
...d/framework/new_executor/workqueue/thread_data_registry.h
+0
-177
paddle/fluid/memory/stats.h
paddle/fluid/memory/stats.h
+2
-2
paddle/fluid/platform/device/gpu/gpu_info.cc
paddle/fluid/platform/device/gpu/gpu_info.cc
+3
-16
paddle/fluid/platform/device/gpu/gpu_info.h
paddle/fluid/platform/device/gpu/gpu_info.h
+2
-1
paddle/fluid/platform/init.cc
paddle/fluid/platform/init.cc
+4
-0
paddle/fluid/platform/profiler/host_event_recorder.h
paddle/fluid/platform/profiler/host_event_recorder.h
+0
-1
paddle/phi/backends/gpu/gpu_info.cc
paddle/phi/backends/gpu/gpu_info.cc
+27
-0
paddle/phi/backends/gpu/gpu_info.h
paddle/phi/backends/gpu/gpu_info.h
+5
-4
paddle/phi/common/memory_utils.cc
paddle/phi/common/memory_utils.cc
+7
-0
paddle/phi/common/memory_utils.h
paddle/phi/common/memory_utils.h
+28
-0
paddle/phi/kernels/gpudnn/conv_gpudnn_base.h
paddle/phi/kernels/gpudnn/conv_gpudnn_base.h
+1
-2
paddle/phi/kernels/gpudnn/conv_grad_kernel.cu
paddle/phi/kernels/gpudnn/conv_grad_kernel.cu
+0
-1
未找到文件。
paddle/fluid/framework/new_executor/workqueue/thread_data_registry.h
已删除
100644 → 0
浏览文件 @
3f3372b6
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include <functional>
#include <memory>
#include <mutex>
#include <shared_mutex>
#include <thread>
#include <type_traits>
#include <unordered_map>
namespace
paddle
{
namespace
framework
{
template
<
typename
T
>
class
ThreadDataRegistry
{
public:
// Singleton
static
ThreadDataRegistry
&
GetInstance
()
{
static
ThreadDataRegistry
instance
;
return
instance
;
}
T
*
GetMutableCurrentThreadData
()
{
return
&
CurrentThreadData
();
}
const
T
&
GetCurrentThreadData
()
{
return
CurrentThreadData
();
}
template
<
typename
Alias
=
T
,
typename
=
std
::
enable_if_t
<
std
::
is_copy_assignable
<
Alias
>
::
value
>>
void
SetCurrentThreadData
(
const
T
&
val
)
{
CurrentThreadData
()
=
val
;
}
// Returns current snapshot of all threads. Make sure there is no thread
// create/destory when using it.
template
<
typename
Alias
=
T
,
typename
=
std
::
enable_if_t
<
std
::
is_copy_constructible
<
Alias
>
::
value
>>
std
::
unordered_map
<
uint64_t
,
T
>
GetAllThreadDataByValue
()
{
return
impl_
->
GetAllThreadDataByValue
();
}
// Returns current snapshot of all threads. Make sure there is no thread
// create/destory when using it.
std
::
unordered_map
<
uint64_t
,
std
::
reference_wrapper
<
T
>>
GetAllThreadDataByRef
()
{
return
impl_
->
GetAllThreadDataByRef
();
}
private:
// types
// Lock types
#if defined(__clang__) || defined(__GNUC__) // CLANG or GCC
#ifndef __APPLE__
#if __cplusplus >= 201703L
using
LockType
=
std
::
shared_mutex
;
using
SharedLockGuardType
=
std
::
shared_lock
<
std
::
shared_mutex
>
;
#elif __cplusplus >= 201402L
using
LockType
=
std
::
shared_timed_mutex
;
using
SharedLockGuardType
=
std
::
shared_lock
<
std
::
shared_timed_mutex
>
;
#else
using
LockType
=
std
::
mutex
;
using
SharedLockGuardType
=
std
::
lock_guard
<
std
::
mutex
>
;
#endif
// Special case : mac. https://github.com/facebook/react-native/issues/31250
#else
using
LockType
=
std
::
mutex
;
using
SharedLockGuardType
=
std
::
lock_guard
<
std
::
mutex
>
;
#endif
#elif defined(_MSC_VER) // MSVC
#if _MSVC_LANG >= 201703L
using
LockType
=
std
::
shared_mutex
;
using
SharedLockGuardType
=
std
::
shared_lock
<
std
::
shared_mutex
>
;
#elif _MSVC_LANG >= 201402L
using
LockType
=
std
::
shared_timed_mutex
;
using
SharedLockGuardType
=
std
::
shared_lock
<
std
::
shared_timed_mutex
>
;
#else
using
LockType
=
std
::
mutex
;
using
SharedLockGuardType
=
std
::
lock_guard
<
std
::
mutex
>
;
#endif
#else // other compilers
using
LockType
=
std
::
mutex
;
using
SharedLockGuardType
=
std
::
lock_guard
<
std
::
mutex
>
;
#endif
class
ThreadDataHolder
;
class
ThreadDataRegistryImpl
{
public:
void
RegisterData
(
uint64_t
tid
,
ThreadDataHolder
*
tls_obj
)
{
std
::
lock_guard
<
LockType
>
guard
(
lock_
);
tid_map_
[
tid
]
=
tls_obj
;
}
void
UnregisterData
(
uint64_t
tid
)
{
std
::
lock_guard
<
LockType
>
guard
(
lock_
);
tid_map_
.
erase
(
tid
);
}
template
<
typename
Alias
=
T
,
typename
=
std
::
enable_if_t
<
std
::
is_copy_constructible
<
Alias
>
::
value
>>
std
::
unordered_map
<
uint64_t
,
T
>
GetAllThreadDataByValue
()
{
std
::
unordered_map
<
uint64_t
,
T
>
data_copy
;
SharedLockGuardType
guard
(
lock_
);
data_copy
.
reserve
(
tid_map_
.
size
());
for
(
auto
&
kv
:
tid_map_
)
{
data_copy
.
emplace
(
kv
.
first
,
kv
.
second
->
GetData
());
}
return
data_copy
;
}
std
::
unordered_map
<
uint64_t
,
std
::
reference_wrapper
<
T
>>
GetAllThreadDataByRef
()
{
std
::
unordered_map
<
uint64_t
,
std
::
reference_wrapper
<
T
>>
data_ref
;
SharedLockGuardType
guard
(
lock_
);
data_ref
.
reserve
(
tid_map_
.
size
());
for
(
auto
&
kv
:
tid_map_
)
{
data_ref
.
emplace
(
kv
.
first
,
std
::
ref
(
kv
.
second
->
GetData
()));
}
return
data_ref
;
}
private:
LockType
lock_
;
std
::
unordered_map
<
uint64_t
,
ThreadDataHolder
*>
tid_map_
;
// not owned
};
class
ThreadDataHolder
{
public:
explicit
ThreadDataHolder
(
std
::
shared_ptr
<
ThreadDataRegistryImpl
>
registry
)
{
registry_
=
std
::
move
(
registry
);
tid_
=
std
::
hash
<
std
::
thread
::
id
>
()(
std
::
this_thread
::
get_id
());
registry_
->
RegisterData
(
tid_
,
this
);
}
~
ThreadDataHolder
()
{
registry_
->
UnregisterData
(
tid_
);
}
T
&
GetData
()
{
return
data_
;
}
private:
std
::
shared_ptr
<
ThreadDataRegistryImpl
>
registry_
;
uint64_t
tid_
;
T
data_
;
};
// methods
ThreadDataRegistry
()
{
impl_
=
std
::
make_shared
<
ThreadDataRegistryImpl
>
();
}
ThreadDataRegistry
(
const
ThreadDataRegistry
&
)
=
delete
;
ThreadDataRegistry
&
operator
=
(
const
ThreadDataRegistry
&
)
=
delete
;
T
&
CurrentThreadData
()
{
static
thread_local
ThreadDataHolder
thread_data
(
impl_
);
return
thread_data
.
GetData
();
}
// data
std
::
shared_ptr
<
ThreadDataRegistryImpl
>
impl_
;
};
}
// namespace framework
}
// namespace paddle
paddle/fluid/memory/stats.h
浏览文件 @
907433a7
...
...
@@ -18,15 +18,15 @@ limitations under the License. */
#include <map>
#include <string>
#include "paddle/fluid/framework/new_executor/workqueue/thread_data_registry.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/errors.h"
#include "paddle/fluid/platform/macros.h"
#include "paddle/phi/common/thread_data_registry.h"
namespace
paddle
{
namespace
memory
{
using
framework
::
ThreadDataRegistry
;
using
phi
::
ThreadDataRegistry
;
struct
ThreadLocalStatBase
{
int64_t
current
{
0
};
...
...
paddle/fluid/platform/device/gpu/gpu_info.cc
浏览文件 @
907433a7
...
...
@@ -61,8 +61,6 @@ PADDLE_DEFINE_EXPORTED_bool(enable_gpu_memory_usage_log_mb,
"Whether to print the message of gpu memory usage "
"MB as a unit of measurement."
);
constexpr
static
float
fraction_reserve_gpu_memory
=
0.05
f
;
USE_GPU_MEM_STAT
;
namespace
paddle
{
namespace
platform
{
...
...
@@ -77,20 +75,7 @@ void GpuMemoryUsage(size_t *available, size_t *total) {
}
size_t
GpuAvailableMemToAlloc
()
{
size_t
total
=
0
;
size_t
available
=
0
;
GpuMemoryUsage
(
&
available
,
&
total
);
size_t
reserving
=
static_cast
<
size_t
>
(
fraction_reserve_gpu_memory
*
available
);
// If available size is less than minimum chunk size, no usable memory exists
size_t
available_to_alloc
=
available
-
reserving
;
size_t
min_chunk_size
=
GpuMinChunkSize
();
if
(
available_to_alloc
<
min_chunk_size
)
{
available_to_alloc
=
0
;
}
VLOG
(
10
)
<<
"GPU usage "
<<
(
available
>>
20
)
<<
"M/"
<<
(
total
>>
20
)
<<
"M, "
<<
(
available_to_alloc
>>
20
)
<<
"M available to allocate"
;
return
available_to_alloc
;
return
phi
::
backends
::
gpu
::
GpuAvailableMemToAlloc
();
}
size_t
GpuMaxAllocSize
()
{
...
...
@@ -124,6 +109,8 @@ size_t GpuInitAllocSize() { return GpuAllocSize(/* realloc = */ false); }
size_t
GpuReallocSize
()
{
return
GpuAllocSize
(
/* realloc = */
true
);
}
size_t
GpuMinChunkSize
()
{
return
phi
::
backends
::
gpu
::
GpuMinChunkSize
();
}
size_t
GpuMaxChunkSize
()
{
size_t
max_chunk_size
=
GpuMaxAllocSize
();
VLOG
(
10
)
<<
"Max chunk size "
<<
(
max_chunk_size
>>
20
)
<<
"M"
;
...
...
paddle/fluid/platform/device/gpu/gpu_info.h
浏览文件 @
907433a7
...
...
@@ -82,7 +82,8 @@ size_t GpuInitAllocSize();
//! Get the re-allocation size of current GPU device.
size_t
GpuReallocSize
();
using
phi
::
backends
::
gpu
::
GpuMinChunkSize
;
//! Get the minimum chunk size for GPU buddy allocator.
size_t
GpuMinChunkSize
();
//! Get the maximum chunk size for GPU buddy allocator.
size_t
GpuMaxChunkSize
();
...
...
paddle/fluid/platform/init.cc
浏览文件 @
907433a7
...
...
@@ -21,6 +21,7 @@ limitations under the License. */
#include "paddle/phi/backends/cpu/cpu_info.h"
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
#include "paddle/fluid/platform/cuda_device_guard.h"
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#endif
#ifdef PADDLE_WITH_CUDA
#include "paddle/fluid/platform/dynload/cupti.h"
...
...
@@ -468,6 +469,9 @@ void InitMemoryMethod() {
memory_method
->
copy
=
paddle
::
memory
::
Copy
<
phi
::
Place
,
phi
::
Place
>
;
memory_method
->
device_memory_stat_current_value
=
paddle
::
memory
::
DeviceMemoryStatCurrentValue
;
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
memory_method
->
gpu_memory_usage
=
paddle
::
platform
::
GpuMemoryUsage
;
#endif
memory_utils
.
Init
(
std
::
move
(
memory_method
));
});
}
...
...
paddle/fluid/platform/profiler/host_event_recorder.h
浏览文件 @
907433a7
...
...
@@ -18,7 +18,6 @@
#include <type_traits>
#include <vector>
#include "paddle/fluid/framework/new_executor/workqueue/thread_data_registry.h"
#include "paddle/fluid/platform/macros.h"
#include "paddle/fluid/platform/os_info.h"
#include "paddle/phi/api/profiler/host_event_recorder.h"
...
...
paddle/phi/backends/gpu/gpu_info.cc
浏览文件 @
907433a7
...
...
@@ -18,6 +18,9 @@ limitations under the License. */
#include <vector>
#include "gflags/gflags.h"
#include "glog/logging.h"
#include "paddle/phi/common/memory_utils.h"
DECLARE_string
(
selected_gpus
);
...
...
@@ -56,6 +59,30 @@ std::vector<int> GetSelectedDevices() {
return
devices
;
}
constexpr
static
float
fraction_reserve_gpu_memory
=
0.05
f
;
size_t
GpuAvailableMemToAlloc
()
{
size_t
total
=
0
;
size_t
available
=
0
;
memory_utils
::
GpuMemoryUsage
(
&
available
,
&
total
);
size_t
reserving
=
static_cast
<
size_t
>
(
fraction_reserve_gpu_memory
*
available
);
// If available size is less than minimum chunk size, no usable memory exists
size_t
available_to_alloc
=
available
-
reserving
;
size_t
min_chunk_size
=
GpuMinChunkSize
();
if
(
available_to_alloc
<
min_chunk_size
)
{
available_to_alloc
=
0
;
}
VLOG
(
10
)
<<
"GPU usage "
<<
(
available
>>
20
)
<<
"M/"
<<
(
total
>>
20
)
<<
"M, "
<<
(
available_to_alloc
>>
20
)
<<
"M available to allocate"
;
return
available_to_alloc
;
}
size_t
GpuMinChunkSize
()
{
// Allow to allocate the minimum chunk size is 256 bytes.
return
1
<<
8
;
}
}
// namespace gpu
}
// namespace backends
}
// namespace phi
paddle/phi/backends/gpu/gpu_info.h
浏览文件 @
907433a7
...
...
@@ -70,11 +70,12 @@ const gpuDeviceProp &GetDeviceProperties(int id);
//! Set the GPU device id for next execution.
void
SetDeviceId
(
int
device_id
);
//! Get the available memory to allocate, which is the size of available gpu
//! minus reserving.
size_t
GpuAvailableMemToAlloc
();
//! Get the minimum chunk size for GPU buddy allocator.
inline
size_t
GpuMinChunkSize
()
{
// Allow to allocate the minimum chunk size is 256 bytes.
return
1
<<
8
;
}
size_t
GpuMinChunkSize
();
//! Copy memory from address src to dst asynchronously.
void
GpuMemcpyAsync
(
void
*
dst
,
...
...
paddle/phi/common/memory_utils.cc
浏览文件 @
907433a7
...
...
@@ -68,6 +68,13 @@ int64_t DeviceMemoryStatCurrentValue(const std::string& stat_type, int dev_id) {
return
MemoryUtils
::
Instance
().
DeviceMemoryStatCurrentValue
(
stat_type
,
dev_id
);
}
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
void
GpuMemoryUsage
(
size_t
*
available
,
size_t
*
total
)
{
return
MemoryUtils
::
Instance
().
GpuMemoryUsage
(
available
,
total
);
}
#endif
}
// namespace memory_utils
}
// namespace phi
paddle/phi/common/memory_utils.h
浏览文件 @
907433a7
...
...
@@ -113,6 +113,16 @@ struct MemoryInterface {
*/
int64_t
(
*
device_memory_stat_current_value
)(
const
std
::
string
&
stat_type
,
int
dev_id
);
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
/**
* @brief get the memory usage of current GPU device.
*
* @param[size_t] available device available memory to alloc
* @param[size_t] total device total memory
*/
void
(
*
gpu_memory_usage
)(
size_t
*
available
,
size_t
*
total
);
#endif
};
class
MemoryUtils
{
...
...
@@ -234,6 +244,18 @@ class MemoryUtils {
return
memory_method_
->
device_memory_stat_current_value
(
stat_type
,
dev_id
);
}
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
void
GpuMemoryUsage
(
size_t
*
available
,
size_t
*
total
)
{
CheckMemoryMethod
();
PADDLE_ENFORCE_NOT_NULL
(
memory_method_
->
gpu_memory_usage
,
phi
::
errors
::
Unavailable
(
"gpu_memory_usage method in memory_method_ is not initiazed "
"yet. You need init it first."
));
return
memory_method_
->
gpu_memory_usage
(
available
,
total
);
}
#endif
void
CheckMemoryMethod
()
{
PADDLE_ENFORCE_NE
(
memory_method_
.
get
(),
...
...
@@ -288,7 +310,13 @@ void Copy(const Place& dst_place,
const
Place
&
src_place
,
const
void
*
src
,
size_t
num
);
int64_t
DeviceMemoryStatCurrentValue
(
const
std
::
string
&
stat_type
,
int
dev_id
);
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
void
GpuMemoryUsage
(
size_t
*
available
,
size_t
*
total
);
#endif
}
// namespace memory_utils
}
// namespace phi
paddle/phi/kernels/gpudnn/conv_gpudnn_base.h
浏览文件 @
907433a7
...
...
@@ -20,7 +20,6 @@ limitations under the License. */
#include <string>
#include <vector>
#include "paddle/fluid/platform/device/gpu/gpu_info.h"
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/common/memory_utils.h"
#include "paddle/phi/kernels/autotune/cache.h"
...
...
@@ -53,7 +52,7 @@ static size_t CalcWorkspaceLimitInBytes(bool use_fixed_workspace) {
memory_utils
::
DeviceMemoryStatCurrentValue
(
"Allocated"
,
device_id
);
int64_t
reserved
=
memory_utils
::
DeviceMemoryStatCurrentValue
(
"Reserved"
,
device_id
);
int64_t
availble
=
p
addle
::
platform
::
GpuAvailableMemToAlloc
();
int64_t
availble
=
p
hi
::
backends
::
gpu
::
GpuAvailableMemToAlloc
();
VLOG
(
3
)
<<
"[memory] allocated="
<<
ToMegaBytes
(
allocated
)
<<
" MB, reserved="
<<
ToMegaBytes
(
reserved
)
<<
" MB, available_to_alloc="
<<
ToMegaBytes
(
availble
)
<<
" MB."
;
...
...
paddle/phi/kernels/gpudnn/conv_grad_kernel.cu
浏览文件 @
907433a7
...
...
@@ -627,7 +627,6 @@ void ConvCudnnGradKernel(const Context& ctx,
compute_format
==
phi
::
backends
::
gpu
::
DataLayout
::
kNHWC
?
phi
::
backends
::
gpu
::
DataLayout
::
kNHWC
:
phi
::
backends
::
gpu
::
DataLayout
::
kNCHW
;
// TODO(phlrain): replace paddle::platform::DataLaytout to phi::DataLayout
if
(
transformed_input
.
dims
().
size
()
==
5
)
{
layout
=
compute_format
==
phi
::
backends
::
gpu
::
DataLayout
::
kNHWC
?
phi
::
backends
::
gpu
::
DataLayout
::
kNDHWC
...
...
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