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1280f294
编写于
5月 13, 2022
作者:
W
Wilber
提交者:
GitHub
5月 13, 2022
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
add gpu resources. (#42723)
上级
757b5d31
变更
10
显示空白变更内容
内联
并排
Showing
10 changed file
with
876 addition
and
262 deletion
+876
-262
paddle/fluid/inference/api/CMakeLists.txt
paddle/fluid/inference/api/CMakeLists.txt
+2
-2
paddle/fluid/inference/api/infer_context.cc
paddle/fluid/inference/api/infer_context.cc
+17
-0
paddle/fluid/inference/api/infer_context.h
paddle/fluid/inference/api/infer_context.h
+46
-0
paddle/fluid/inference/api/resource_manager.cc
paddle/fluid/inference/api/resource_manager.cc
+290
-0
paddle/fluid/inference/api/resource_manager.h
paddle/fluid/inference/api/resource_manager.h
+109
-0
paddle/phi/backends/gpu/CMakeLists.txt
paddle/phi/backends/gpu/CMakeLists.txt
+2
-1
paddle/phi/backends/gpu/gpu_context.cc
paddle/phi/backends/gpu/gpu_context.cc
+84
-259
paddle/phi/backends/gpu/gpu_context.h
paddle/phi/backends/gpu/gpu_context.h
+4
-0
paddle/phi/backends/gpu/gpu_resources.cc
paddle/phi/backends/gpu/gpu_resources.cc
+271
-0
paddle/phi/backends/gpu/gpu_resources.h
paddle/phi/backends/gpu/gpu_resources.h
+51
-0
未找到文件。
paddle/fluid/inference/api/CMakeLists.txt
浏览文件 @
1280f294
...
...
@@ -50,10 +50,10 @@ if(WITH_GPU AND TENSORRT_FOUND)
endif
()
if
(
WITH_ONNXRUNTIME
)
cc_library
(
analysis_predictor SRCS analysis_predictor.cc onnxruntime_predictor.cc
${
mkldnn_quantizer_src
}
DEPS
${
inference_deps
}
cc_library
(
analysis_predictor SRCS analysis_predictor.cc onnxruntime_predictor.cc
resource_manager.cc infer_context.cc
${
mkldnn_quantizer_src
}
DEPS
${
inference_deps
}
zero_copy_tensor ir_pass_manager op_compatible_info infer_io_utils onnxruntime paddle2onnx
)
else
(
WITH_ONNXRUNTIME
)
cc_library
(
analysis_predictor SRCS analysis_predictor.cc
${
mkldnn_quantizer_src
}
DEPS
${
inference_deps
}
cc_library
(
analysis_predictor SRCS analysis_predictor.cc
resource_manager.cc infer_context.cc
${
mkldnn_quantizer_src
}
DEPS
${
inference_deps
}
zero_copy_tensor ir_pass_manager op_compatible_info infer_io_utils
)
endif
(
WITH_ONNXRUNTIME
)
...
...
paddle/fluid/inference/api/infer_context.cc
0 → 100644
浏览文件 @
1280f294
// 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.
#include "paddle/fluid/inference/api/infer_context.h"
namespace
paddle
{}
// namespace paddle
paddle/fluid/inference/api/infer_context.h
0 → 100644
浏览文件 @
1280f294
// 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 "paddle/phi/backends/all_context.h"
namespace
paddle
{
class
InferCPUContext
:
public
phi
::
CPUContext
{
public:
using
phi
::
CPUContext
::
SetEigenDevice
;
};
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
class
InferGPUContext
:
public
phi
::
GPUContext
{
public:
using
phi
::
GPUContext
::
SetStream
;
using
phi
::
GPUContext
::
SetEigenDevice
;
using
phi
::
GPUContext
::
SetBlasHandle
;
using
phi
::
GPUContext
::
SetBlasTensorCoreHandle
;
using
phi
::
GPUContext
::
SetBlasTF32Handle
;
using
phi
::
GPUContext
::
SetDnnHandle
;
using
phi
::
GPUContext
::
SetSolverHandle
;
using
phi
::
GPUContext
::
SetSparseHandle
;
// using phi::GPUContext::SetDnnWorkspaceHandle;
using
phi
::
GPUContext
::
SetComputeCapability
;
using
phi
::
GPUContext
::
SetMaxThreadsPerMultiProcessor
;
using
phi
::
GPUContext
::
SetMultiProcessors
;
using
phi
::
GPUContext
::
SetMaxThreadsPerBlock
;
using
phi
::
GPUContext
::
SetMaxGridDimSize
;
using
phi
::
GPUContext
::
SetDriverVersion
;
using
phi
::
GPUContext
::
SetRuntimeVersion
;
};
#endif
}
// namespace paddle
paddle/fluid/inference/api/resource_manager.cc
0 → 100644
浏览文件 @
1280f294
// 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.
#include "paddle/fluid/inference/api/resource_manager.h"
#include <unordered_map>
#include "paddle/fluid/memory/allocation/allocator_facade.h"
#include "paddle/phi/backends/gpu/forwards.h"
#include "paddle/phi/backends/gpu/gpu_decls.h"
#include "paddle/phi/backends/gpu/gpu_info.h"
#include "paddle/phi/backends/gpu/gpu_resources.h"
#include "paddle/phi/common/place.h"
#include "paddle/phi/core/allocator.h"
#include "paddle/phi/core/generator.h"
#include "unsupported/Eigen/CXX11/Tensor"
namespace
paddle
{
namespace
internal
{
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
class
EigenGpuStreamDevice
:
public
Eigen
::
StreamInterface
{
public:
EigenGpuStreamDevice
()
:
scratch_
(
nullptr
),
semaphore_
(
nullptr
)
{
Eigen
::
initializeDeviceProp
();
}
~
EigenGpuStreamDevice
()
override
{}
void
Reinitialize
(
gpuStream_t
cuda_stream
,
phi
::
Allocator
*
allocator
,
GPUPlace
place
)
{
stream_
=
cuda_stream
;
allocator_
=
allocator
;
device_prop_
=
&
Eigen
::
m_deviceProperties
[
place
.
device
];
}
const
gpuStream_t
&
stream
()
const
override
{
return
stream_
;
}
const
gpuDeviceProp
&
deviceProperties
()
const
override
{
return
*
device_prop_
;
}
void
*
allocate
(
size_t
num_bytes
)
const
override
{
if
(
UNLIKELY
(
num_bytes
==
0
))
{
return
nullptr
;
}
auto
buf
=
allocator_
->
Allocate
(
num_bytes
);
VLOG
(
4
)
<<
"Eigen allocated at "
<<
buf
->
ptr
()
<<
" requested "
<<
num_bytes
;
void
*
retv
=
buf
->
ptr
();
{
std
::
lock_guard
<
std
::
mutex
>
lock
(
mtx_
);
allocations_
.
emplace
(
retv
,
std
::
move
(
buf
));
}
return
retv
;
}
void
deallocate
(
void
*
buffer
)
const
override
{
if
(
LIKELY
(
buffer
))
{
std
::
lock_guard
<
std
::
mutex
>
lock
(
mtx_
);
allocations_
.
erase
(
buffer
);
}
}
void
*
scratchpad
()
const
override
{
if
(
scratch_
==
NULL
)
{
scratch_
=
allocate
(
Eigen
::
kGpuScratchSize
+
sizeof
(
unsigned
int
));
}
return
scratch_
;
}
unsigned
int
*
semaphore
()
const
override
{
if
(
semaphore_
==
NULL
)
{
char
*
scratch
=
static_cast
<
char
*>
(
scratchpad
())
+
Eigen
::
kGpuScratchSize
;
semaphore_
=
reinterpret_cast
<
unsigned
int
*>
(
scratch
);
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_GPU_SUCCESS
(
hipMemsetAsync
(
semaphore_
,
0
,
sizeof
(
unsigned
int
),
stream_
));
#else
PADDLE_ENFORCE_GPU_SUCCESS
(
cudaMemsetAsync
(
semaphore_
,
0
,
sizeof
(
unsigned
int
),
stream_
));
#endif
}
return
semaphore_
;
}
private:
gpuStream_t
stream_
;
// not owned;
phi
::
Allocator
*
allocator_
;
// not owned;
const
gpuDeviceProp
*
device_prop_
;
// not owned;
mutable
void
*
scratch_
;
mutable
unsigned
int
*
semaphore_
;
mutable
std
::
mutex
mtx_
;
// to protect allocations_
mutable
std
::
unordered_map
<
void
*
,
phi
::
Allocator
::
AllocationPtr
>
allocations_
;
};
#endif
}
// namespace internal
ResourceManager
::
ResourceManager
(
const
phi
::
Place
&
place
,
void
*
stream
)
:
place_
(
place
)
{
InitCPUResource
();
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
InitGPUResource
(
stream
);
#endif
}
ResourceManager
::~
ResourceManager
()
{
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
DestroyGPUResource
();
#endif
}
void
ResourceManager
::
InitCPUResource
()
{
cpu_eigen_device_
.
reset
(
new
Eigen
::
DefaultDevice
());
}
Eigen
::
DefaultDevice
*
ResourceManager
::
GetCpuEigenDevice
()
{
return
cpu_eigen_device_
.
get
();
}
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
void
ResourceManager
::
InitGPUResource
(
void
*
stream
)
{
if
(
stream
==
nullptr
)
{
owned_stream_
=
true
;
phi
::
InitStream
(
&
stream_
);
}
else
{
owned_stream_
=
false
;
stream_
=
reinterpret_cast
<
gpuStream_t
>
(
stream
);
}
InitGpuProperties
();
InitGpuEigenDevice
();
InitDnnHanlde
();
InitBlasHandle
();
InitBlasLtHandle
();
InitSolverHandle
();
InitSparseHandle
();
}
void
ResourceManager
::
DestroyGPUResource
()
{
if
(
owned_stream_
)
{
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_GPU_SUCCESS
(
hipStreamDestroy
(
stream_
));
#else
PADDLE_ENFORCE_GPU_SUCCESS
(
cudaStreamDestroy
(
stream_
));
#endif
stream_
=
nullptr
;
}
DestroyDnnHandle
();
DestroyBlasHandle
();
DestroyBlasLtHandle
();
DestroySolverHandle
();
DestroySparseHandle
();
}
void
ResourceManager
::
InitGpuProperties
()
{
phi
::
backends
::
gpu
::
GPUDeviceGuard
guard
(
place_
.
device
);
phi
::
InitGpuProperties
(
place_
,
&
compute_capability_
,
&
runtime_version_
,
&
driver_version_
,
&
multi_process_
,
&
max_threads_per_mp_
,
&
max_threads_per_block_
,
&
max_grid_dim_size_
);
}
void
ResourceManager
::
InitGpuEigenDevice
()
{
auto
*
allocator
=
paddle
::
memory
::
allocation
::
AllocatorFacade
::
Instance
()
.
GetAllocator
(
place_
)
.
get
();
eigen_stream_
.
reset
(
new
internal
::
EigenGpuStreamDevice
());
eigen_stream_
->
Reinitialize
(
stream_
,
allocator
,
place_
);
gpu_eigen_device_
.
reset
(
new
Eigen
::
GpuDevice
(
eigen_stream_
.
get
()));
}
void
ResourceManager
::
InitDnnHanlde
()
{
phi
::
InitDnnHandle
(
&
dnn_handle_
,
stream_
,
place_
);
}
void
ResourceManager
::
DestroyDnnHandle
()
{
phi
::
DestroyDnnHandle
(
dnn_handle_
);
}
void
ResourceManager
::
InitBlasHandle
()
{
phi
::
InitBlasHandle
(
&
blas_handle_
,
stream_
);
#ifdef PADDLE_WITH_CUDA
#if CUDA_VERSION >= 9000
phi
::
InitBlasHandle
(
&
blas_tensor_core_handle_
,
stream_
);
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasSetMathMode
(
blas_tensor_core_handle_
,
CUBLAS_TENSOR_OP_MATH
));
#endif
#if CUDA_VERSION >= 11000
phi
::
InitBlasHandle
(
&
blas_tf32_tensor_core_handle_
,
stream_
);
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasSetMathMode
(
blas_tf32_tensor_core_handle_
,
CUBLAS_TF32_TENSOR_OP_MATH
));
#endif
#endif
}
void
ResourceManager
::
DestroyBlasHandle
()
{
phi
::
DestroyBlasHandle
(
blas_handle_
);
phi
::
DestroyBlasHandle
(
blas_tensor_core_handle_
);
phi
::
DestroyBlasHandle
(
blas_tf32_tensor_core_handle_
);
}
void
ResourceManager
::
InitBlasLtHandle
()
{
phi
::
InitBlasLtHandle
(
&
blaslt_handle_
);
}
void
ResourceManager
::
DestroyBlasLtHandle
()
{
phi
::
DestroyBlasLtHandle
(
blaslt_handle_
);
}
void
ResourceManager
::
InitSolverHandle
()
{
phi
::
InitSolverHandle
(
&
solver_handle_
,
stream_
);
}
void
ResourceManager
::
DestroySolverHandle
()
{
phi
::
DestroySolverHandle
(
solver_handle_
);
}
void
ResourceManager
::
InitSparseHandle
()
{
phi
::
InitSparseHandle
(
&
sparse_handle_
,
stream_
);
}
void
ResourceManager
::
DestroySparseHandle
()
{
phi
::
DestroySparseHandle
(
sparse_handle_
);
}
gpuStream_t
ResourceManager
::
GetStream
()
const
{
return
stream_
;
}
dnnHandle_t
ResourceManager
::
GetDnnHandle
()
const
{
return
dnn_handle_
;
}
blasHandle_t
ResourceManager
::
GetBlasHandle
()
const
{
return
blas_handle_
;
}
blasHandle_t
ResourceManager
::
GetBlasTensorCoreHandle
()
const
{
return
blas_tensor_core_handle_
;
}
blasHandle_t
ResourceManager
::
GetBlasTF32Handle
()
const
{
return
blas_tf32_tensor_core_handle_
;
}
blasLtHandle_t
ResourceManager
::
GetBlasLtHandle
()
const
{
return
blaslt_handle_
;
}
phi
::
solverHandle_t
ResourceManager
::
GetSolverDnHandle
()
const
{
return
solver_handle_
;
}
phi
::
sparseHandle_t
ResourceManager
::
GetSparseHandle
()
const
{
return
sparse_handle_
;
}
Eigen
::
GpuDevice
*
ResourceManager
::
GetGpuEigenDevice
()
const
{
return
gpu_eigen_device_
.
get
();
}
int
ResourceManager
::
GetGpuComputeCapability
()
const
{
return
compute_capability_
;
}
int
ResourceManager
::
GetGpuRuntimeVersion
()
const
{
return
runtime_version_
;
}
int
ResourceManager
::
GetGpuDriverVersion
()
const
{
return
driver_version_
;
}
int
ResourceManager
::
GetGPUMultiProcessors
()
const
{
return
multi_process_
;
}
int
ResourceManager
::
GetGpuMaxThreadsPerMp
()
const
{
return
max_threads_per_mp_
;
}
int
ResourceManager
::
GetGpuMaxThreadsPerBlock
()
const
{
return
max_threads_per_block_
;
}
std
::
array
<
int
,
3
>
ResourceManager
::
GetGpuMaxGridDimSize
()
const
{
return
max_grid_dim_size_
;
}
#endif
}
// namespace paddle
paddle/fluid/inference/api/resource_manager.h
0 → 100644
浏览文件 @
1280f294
// 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 "paddle/phi/api/include/tensor.h"
#include "paddle/phi/backends/cpu/forwards.h"
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
#include "paddle/fluid/platform/device/gpu/gpu_types.h"
#include "paddle/phi/backends/gpu/forwards.h"
#include "paddle/phi/backends/gpu/gpu_decls.h"
#include "paddle/phi/backends/gpu/gpu_resources.h"
#endif
namespace
paddle
{
namespace
internal
{
class
EigenGpuStreamDevice
;
}
// namespace internal
class
ResourceManager
{
public:
explicit
ResourceManager
(
const
phi
::
Place
&
place
,
void
*
stream
);
~
ResourceManager
();
public:
Eigen
::
DefaultDevice
*
GetCpuEigenDevice
();
private:
void
InitCPUResource
();
private:
phi
::
Place
place_
;
std
::
unique_ptr
<
Eigen
::
DefaultDevice
>
cpu_eigen_device_
;
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
public:
gpuStream_t
GetStream
()
const
;
dnnHandle_t
GetDnnHandle
()
const
;
blasHandle_t
GetBlasHandle
()
const
;
blasHandle_t
GetBlasTensorCoreHandle
()
const
;
blasHandle_t
GetBlasTF32Handle
()
const
;
blasLtHandle_t
GetBlasLtHandle
()
const
;
phi
::
solverHandle_t
GetSolverDnHandle
()
const
;
phi
::
sparseHandle_t
GetSparseHandle
()
const
;
Eigen
::
GpuDevice
*
GetGpuEigenDevice
()
const
;
int
GetGpuComputeCapability
()
const
;
int
GetGpuRuntimeVersion
()
const
;
int
GetGpuDriverVersion
()
const
;
int
GetGPUMultiProcessors
()
const
;
int
GetGpuMaxThreadsPerMp
()
const
;
int
GetGpuMaxThreadsPerBlock
()
const
;
std
::
array
<
int
,
3
>
GetGpuMaxGridDimSize
()
const
;
private:
void
InitGPUResource
(
void
*
stream
);
void
DestroyGPUResource
();
void
InitGpuProperties
();
void
InitGpuEigenDevice
();
void
InitDnnHanlde
();
void
DestroyDnnHandle
();
void
InitBlasHandle
();
void
DestroyBlasHandle
();
void
InitBlasLtHandle
();
void
DestroyBlasLtHandle
();
void
InitSolverHandle
();
void
DestroySolverHandle
();
void
InitSparseHandle
();
void
DestroySparseHandle
();
private:
int
compute_capability_
;
int
runtime_version_
;
int
driver_version_
;
int
multi_process_
;
int
max_threads_per_mp_
;
int
max_threads_per_block_
;
std
::
array
<
int
,
3
>
max_grid_dim_size_
;
bool
owned_stream_
{
true
};
gpuStream_t
stream_
;
std
::
unique_ptr
<
Eigen
::
GpuDevice
>
gpu_eigen_device_
;
std
::
unique_ptr
<
internal
::
EigenGpuStreamDevice
>
eigen_stream_
;
blasHandle_t
blas_handle_
{
nullptr
};
blasHandle_t
blas_tensor_core_handle_
{
nullptr
};
blasHandle_t
blas_tf32_tensor_core_handle_
{
nullptr
};
blasLtHandle_t
blaslt_handle_
{
nullptr
};
dnnHandle_t
dnn_handle_
{
nullptr
};
phi
::
solverHandle_t
solver_handle_
{
nullptr
};
phi
::
sparseHandle_t
sparse_handle_
{
nullptr
};
// DnnWorkspaceHandle
#endif
};
}
// namespace paddle
paddle/phi/backends/gpu/CMakeLists.txt
浏览文件 @
1280f294
...
...
@@ -6,4 +6,5 @@ elseif(WITH_ROCM)
hip_library
(
phi_gpu_info SRCS gpu_info.cc DEPS phi_rocm_info gflags glog enforce phi_dynload_cuda
)
endif
()
cc_library
(
gpu_context SRCS gpu_context.cc DEPS phi_device_context phi_gpu_info eigen3
)
cc_library
(
gpu_resources SRCS gpu_resources.cc DEPS phi_device_context phi_gpu_info
)
cc_library
(
gpu_context SRCS gpu_context.cc DEPS phi_device_context phi_gpu_info eigen3 gpu_resources
)
paddle/phi/backends/gpu/gpu_context.cc
浏览文件 @
1280f294
...
...
@@ -25,6 +25,7 @@ limitations under the License. */
#include "paddle/phi/backends/gpu/gpu_decls.h"
#include "paddle/phi/backends/gpu/gpu_info.h"
#include "paddle/phi/backends/gpu/gpu_resources.h"
#include "paddle/phi/common/float16.h"
#include "paddle/phi/common/place.h"
#include "paddle/phi/core/allocator.h"
...
...
@@ -202,27 +203,65 @@ struct GPUContext::Impl {
void
Init
()
{
owned_
=
true
;
backends
::
gpu
::
GPUDeviceGuard
guard
(
place_
.
device
);
InitGpuProperties
();
InitStream
();
phi
::
InitGpuProperties
(
place_
,
&
compute_capability_
,
&
runtime_version_
,
&
driver_version_
,
&
multi_process_
,
&
max_threads_per_mp_
,
&
max_threads_per_block_
,
&
max_grid_dim_size_
);
phi
::
InitStream
(
&
stream_
);
InitEigenDevice
();
InitBlasHandle
();
InitBlasLtHandle
();
InitDNNHandle
();
InitSolverHandle
();
InitSparseHandle
();
phi
::
InitBlasHandle
(
&
blas_handle_
,
stream_
);
#ifdef PADDLE_WITH_CUDA
#if CUDA_VERSION >= 9000
phi
::
InitBlasHandle
(
&
blas_tensor_core_handle_
,
stream_
);
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasSetMathMode
(
blas_tensor_core_handle_
,
CUBLAS_TENSOR_OP_MATH
));
#endif
#if CUDA_VERSION >= 11000
phi
::
InitBlasHandle
(
&
blas_tf32_tensor_core_handle_
,
stream_
);
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasSetMathMode
(
blas_tf32_tensor_core_handle_
,
CUBLAS_TF32_TENSOR_OP_MATH
));
#endif
#endif
phi
::
InitBlasLtHandle
(
&
blaslt_handle_
);
phi
::
InitDnnHandle
(
&
dnn_handle_
,
stream_
,
place_
);
phi
::
InitSolverHandle
(
&
solver_handle_
,
stream_
);
phi
::
InitSparseHandle
(
&
sparse_handle_
,
stream_
);
InitDnnWorkspace
();
}
void
PartialInitWithoutAllocator
()
{
owned_
=
true
;
backends
::
gpu
::
GPUDeviceGuard
guard
(
place_
.
device
);
InitGpuProperties
();
InitStream
();
InitBlasHandle
();
InitBlasLtHandle
();
InitDNNHandle
();
InitSolverHandle
();
InitSparseHandle
();
phi
::
InitGpuProperties
(
place_
,
&
compute_capability_
,
&
runtime_version_
,
&
driver_version_
,
&
multi_process_
,
&
max_threads_per_mp_
,
&
max_threads_per_block_
,
&
max_grid_dim_size_
);
phi
::
InitStream
(
&
stream_
);
phi
::
InitBlasHandle
(
&
blas_handle_
,
stream_
);
#ifdef PADDLE_WITH_CUDA
#if CUDA_VERSION >= 9000
phi
::
InitBlasHandle
(
&
blas_tensor_core_handle_
,
stream_
);
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasSetMathMode
(
blas_tensor_core_handle_
,
CUBLAS_TENSOR_OP_MATH
));
#endif
#if CUDA_VERSION >= 11000
phi
::
InitBlasHandle
(
&
blas_tf32_tensor_core_handle_
,
stream_
);
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasSetMathMode
(
blas_tf32_tensor_core_handle_
,
CUBLAS_TF32_TENSOR_OP_MATH
));
#endif
#endif
phi
::
InitBlasLtHandle
(
&
blaslt_handle_
);
phi
::
InitDnnHandle
(
&
dnn_handle_
,
stream_
,
place_
);
phi
::
InitSolverHandle
(
&
solver_handle_
,
stream_
);
phi
::
InitSparseHandle
(
&
sparse_handle_
,
stream_
);
}
void
PartialInitWithAllocator
()
{
...
...
@@ -238,19 +277,23 @@ struct GPUContext::Impl {
~
Impl
()
{
backends
::
gpu
::
GPUDeviceGuard
guard
(
place_
.
device
);
if
(
owned_
)
{
DestoryInternalWorkspace
();
DestoryInternalEigenDevice
();
DestroyInternalSparseHandle
(
);
DestroyInternalSolverHandle
(
);
DestroyInternalDnnHandle
(
);
phi
::
DestroySparseHandle
(
sparse_handle_
);
phi
::
DestroySolverHandle
(
solver_handle_
);
phi
::
DestroyDnnHandle
(
dnn_handle_
);
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
if
(
nccl_comm_
)
{
PADDLE_ENFORCE_GPU_SUCCESS
(
dynload
::
ncclCommDestroy
(
nccl_comm_
));
}
#endif
DestroyInternalBlasHandle
();
DestroyInternalBlasLtHandle
();
DestoryInternalStream
();
phi
::
DestroyBlasHandle
(
blas_handle_
);
phi
::
DestroyBlasHandle
(
blas_tensor_core_handle_
);
phi
::
DestroyBlasHandle
(
blas_tf32_tensor_core_handle_
);
phi
::
DestroyBlasLtHandle
(
blaslt_handle_
);
phi
::
DestoryStream
(
stream_
);
}
}
const
Place
&
GetPlace
()
const
{
return
place_
;
}
...
...
@@ -259,73 +302,6 @@ struct GPUContext::Impl {
return
blas_tensor_core_handle_
!=
nullptr
;
}
void
InitGpuProperties
()
{
backends
::
gpu
::
GPUDeviceGuard
guard
(
place_
.
GetDeviceId
());
compute_capability_
=
backends
::
gpu
::
GetGPUComputeCapability
(
place_
.
GetDeviceId
());
multi_process_
=
backends
::
gpu
::
GetGPUMultiProcessors
(
place_
.
GetDeviceId
());
max_threads_per_mp_
=
backends
::
gpu
::
GetGPUMaxThreadsPerMultiProcessor
(
place_
.
GetDeviceId
());
max_grid_dim_size_
=
backends
::
gpu
::
GetGpuMaxGridDimSize
(
place_
.
GetDeviceId
());
max_threads_per_block_
=
backends
::
gpu
::
GetGPUMaxThreadsPerBlock
(
place_
.
GetDeviceId
());
driver_version_
=
backends
::
gpu
::
GetGPUDriverVersion
(
place_
.
GetDeviceId
());
runtime_version_
=
backends
::
gpu
::
GetGPURuntimeVersion
(
place_
.
GetDeviceId
());
// TODO(wilber): glog may be replaced in the future?
LOG_FIRST_N
(
WARNING
,
1
)
<<
"Please NOTE: device: "
<<
static_cast
<
int
>
(
place_
.
device
)
<<
", GPU Compute Capability: "
<<
compute_capability_
/
10
<<
"."
<<
compute_capability_
%
10
<<
", Driver API Version: "
<<
driver_version_
/
1000
<<
"."
<<
(
driver_version_
%
100
)
/
10
<<
", Runtime API Version: "
<<
runtime_version_
/
1000
<<
"."
<<
(
runtime_version_
%
100
)
/
10
;
#ifdef PADDLE_WITH_HIP
size_t
miopen_major
,
miopen_minor
,
miopen_patch
;
PADDLE_ENFORCE_GPU_SUCCESS
(
dynload
::
miopenGetVersion
(
&
miopen_major
,
&
miopen_minor
,
&
miopen_patch
));
auto
cudnn_dso_ver
=
(
miopen_major
*
1000
+
miopen_minor
*
10
+
miopen_patch
)
/
10
;
auto
compile_miopen_version
=
MIOPEN_VERSION
/
10
;
if
(
cudnn_dso_ver
<
static_cast
<
size_t
>
(
compile_miopen_version
))
{
LOG_FIRST_N
(
WARNING
,
1
)
<<
"WARNING: device: "
<<
static_cast
<
int
>
(
place_
.
device
)
<<
". The installed Paddle is compiled with MIOPEN "
<<
compile_miopen_version
/
100
<<
"."
<<
compile_miopen_version
%
100
<<
", but MIOPEN version in your machine is "
<<
cudnn_dso_ver
/
100
<<
"."
<<
cudnn_dso_ver
%
100
<<
", which may cause serious incompatible bug. "
<<
"Please recompile or reinstall Paddle with compatible MIOPEN "
"version."
;
}
#else
size_t
cudnn_dso_ver
=
dynload
::
cudnnGetVersion
();
LOG_FIRST_N
(
WARNING
,
1
)
<<
"device: "
<<
static_cast
<
int
>
(
place_
.
device
)
<<
", cuDNN Version: "
<<
cudnn_dso_ver
/
1000
<<
"."
<<
(
cudnn_dso_ver
%
1000
)
/
100
<<
"."
;
// Check CUDA/CUDNN version compatiblity
auto
local_cuda_version
=
(
driver_version_
/
1000
)
*
10
+
(
driver_version_
%
100
)
/
10
;
auto
compile_cuda_version
=
(
CUDA_VERSION
/
1000
)
*
10
+
(
CUDA_VERSION
%
100
)
/
10
;
if
(
local_cuda_version
<
compile_cuda_version
)
{
LOG_FIRST_N
(
WARNING
,
1
)
<<
"WARNING: device: "
<<
static_cast
<
int
>
(
place_
.
device
)
<<
". The installed Paddle is compiled with CUDA "
<<
compile_cuda_version
/
10
<<
"."
<<
compile_cuda_version
%
10
<<
", but CUDA runtime version in your machine is "
<<
local_cuda_version
/
10
<<
"."
<<
local_cuda_version
%
10
<<
", which may cause serious incompatible bug. "
<<
"Please recompile or reinstall Paddle with compatible CUDA "
"version."
;
}
#endif
}
void
InitDnnWorkspace
()
{
PD_CHECK
(
allocator_
!=
nullptr
,
"the device allocator for gpu context is nullptr."
);
...
...
@@ -350,27 +326,6 @@ struct GPUContext::Impl {
return
DnnWorkspaceHandle
(
allocator_
,
stream_
);
}
void
InitStream
()
{
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_GPU_SUCCESS
(
hipStreamCreateWithPriority
(
&
stream_
,
hipStreamDefault
,
0
));
#else
PADDLE_ENFORCE_GPU_SUCCESS
(
cudaStreamCreateWithPriority
(
&
stream_
,
cudaStreamDefault
,
0
));
#endif
}
void
DestoryInternalStream
()
{
if
(
owned_
&&
stream_
!=
nullptr
)
{
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_GPU_SUCCESS
(
hipStreamDestroy
(
stream_
));
#else
PADDLE_ENFORCE_GPU_SUCCESS
(
cudaStreamDestroy
(
stream_
));
#endif
}
stream_
=
nullptr
;
}
void
SetStream
(
gpuStream_t
stream
)
{
stream_
=
stream
;
}
gpuStream_t
GetStream
()
const
{
...
...
@@ -400,55 +355,6 @@ struct GPUContext::Impl {
return
eigen_device_
;
}
void
InitBlasHandle
()
{
#ifdef PADDLE_WITH_HIP
phi
::
dynload
::
rocblas_create_handle
(
&
blas_handle_
);
phi
::
dynload
::
rocblas_set_stream
(
blas_handle_
,
stream_
);
#else // PADDLE_WITH_CUDA
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasCreate
(
&
blas_handle_
));
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasSetStream
(
blas_handle_
,
stream_
));
#if CUDA_VERSION >= 9000
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasCreate
(
&
blas_tensor_core_handle_
));
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasSetStream
(
blas_tensor_core_handle_
,
stream_
));
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasSetMathMode
(
blas_tensor_core_handle_
,
CUBLAS_TENSOR_OP_MATH
));
#if CUDA_VERSION >= 11000
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasCreate
(
&
blas_tf32_tensor_core_handle_
));
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasSetStream
(
blas_tf32_tensor_core_handle_
,
stream_
));
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasSetMathMode
(
blas_tf32_tensor_core_handle_
,
CUBLAS_TF32_TENSOR_OP_MATH
));
#endif // CUDA_VERSION >= 11000
#endif // CUDA_VERSION >= 9000
#endif // PADDLE_WITH_HIP
}
void
DestroyInternalBlasHandle
()
{
#ifdef PADDLE_WITH_HIP
if
(
owned_
&&
blas_handle_
!=
nullptr
)
{
phi
::
dynload
::
rocblas_destroy_handle
(
blas_handle_
);
blas_handle_
=
nullptr
;
}
#else
if
(
owned_
&&
blas_handle_
!=
nullptr
)
{
phi
::
dynload
::
cublasDestroy
(
blas_handle_
);
blas_handle_
=
nullptr
;
}
if
(
owned_
&&
blas_tensor_core_handle_
!=
nullptr
)
{
phi
::
dynload
::
cublasDestroy
(
blas_tensor_core_handle_
);
blas_tensor_core_handle_
=
nullptr
;
}
if
(
owned_
&&
blas_tf32_tensor_core_handle_
!=
nullptr
)
{
phi
::
dynload
::
cublasDestroy
(
blas_tf32_tensor_core_handle_
);
blas_tf32_tensor_core_handle_
=
nullptr
;
}
#endif // PADDLE_WITH_HIP
}
blasHandle_t
GetBlasHandle
()
const
{
PD_CHECK
(
blas_handle_
!=
nullptr
,
"the gpu blas handle is nullptr."
);
return
blas_handle_
;
...
...
@@ -456,16 +362,12 @@ struct GPUContext::Impl {
void
SetBlasHandle
(
blasHandle_t
blas
)
{
blas_handle_
=
blas
;
}
void
InitBlasLtHandle
()
{
#if defined(PADDLE_WITH_CUDA) && CUDA_VERSION >= 11060
phi
::
dynload
::
cublasLtCreate
(
&
blaslt_handle_
);
#endif
void
SetBlasTensorCoreHandle
(
blasHandle_t
handle
)
{
blas_tensor_core_handle_
=
handle
;
}
void
DestroyInternalBlasLtHandle
()
{
#if defined(PADDLE_WITH_CUDA) && CUDA_VERSION >= 11060
phi
::
dynload
::
cublasLtDestroy
(
blaslt_handle_
);
#endif
void
SetBlasTF32Handle
(
blasHandle_t
handle
)
{
blas_tf32_tensor_core_handle_
=
handle
;
}
void
SetBlasLtHandle
(
blasLtHandle_t
blaslt
)
{
blaslt_handle_
=
blaslt
;
}
...
...
@@ -475,53 +377,6 @@ struct GPUContext::Impl {
return
blaslt_handle_
;
}
void
InitDNNHandle
()
{
if
(
phi
::
dynload
::
HasCUDNN
())
{
#ifdef PADDLE_WITH_HIP
size_t
miopen_major
,
miopen_minor
,
miopen_patch
;
PADDLE_ENFORCE_GPU_SUCCESS
(
dynload
::
miopenGetVersion
(
&
miopen_major
,
&
miopen_minor
,
&
miopen_patch
));
auto
local_miopen_version
=
(
miopen_major
*
1000
+
miopen_minor
*
10
+
miopen_patch
)
/
10
;
auto
compile_miopen_version
=
MIOPEN_VERSION
/
10
;
if
(
local_miopen_version
<
static_cast
<
size_t
>
(
compile_miopen_version
))
{
LOG_FIRST_N
(
WARNING
,
1
)
<<
"WARNING: device: "
<<
place_
.
device
<<
". The installed Paddle is compiled with MIOPEN "
<<
compile_miopen_version
/
100
<<
"."
<<
compile_miopen_version
%
100
<<
", but MIOPEN version in your machine is "
<<
local_miopen_version
/
100
<<
"."
<<
local_miopen_version
%
100
<<
", which may cause serious incompatible bug. "
<<
"Please recompile or reinstall Paddle with compatible MIOPEN "
"version."
;
}
PADDLE_ENFORCE_GPU_SUCCESS
(
dynload
::
miopenCreate
(
&
dnn_handle_
));
PADDLE_ENFORCE_GPU_SUCCESS
(
dynload
::
miopenSetStream
(
dnn_handle_
,
stream_
));
#else
auto
local_cudnn_version
=
phi
::
dynload
::
cudnnGetVersion
()
/
100
;
auto
compile_cudnn_version
=
CUDNN_VERSION
/
100
;
if
(
local_cudnn_version
<
static_cast
<
size_t
>
(
compile_cudnn_version
))
{
LOG_FIRST_N
(
WARNING
,
1
)
<<
"WARNING: device: "
<<
place_
.
device
<<
". The installed Paddle is compiled with CUDNN "
<<
compile_cudnn_version
/
10
<<
"."
<<
compile_cudnn_version
%
10
<<
", but CUDNN version in your machine is "
<<
local_cudnn_version
/
10
<<
"."
<<
local_cudnn_version
%
10
<<
", which may cause serious incompatible bug. "
<<
"Please recompile or reinstall Paddle with compatible CUDNN "
"version."
;
}
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cudnnCreate
(
&
dnn_handle_
));
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cudnnSetStream
(
dnn_handle_
,
stream_
));
#endif
}
else
{
dnn_handle_
=
nullptr
;
}
}
dnnHandle_t
GetDnnHandle
()
{
PD_CHECK
(
dnn_handle_
!=
nullptr
,
"the gpu dnn handle is nullptr."
);
return
dnn_handle_
;
...
...
@@ -543,24 +398,6 @@ struct GPUContext::Impl {
void
SetDnnHandle
(
dnnHandle_t
handle
)
{
dnn_handle_
=
handle
;
}
void
InitSolverHandle
()
{
#ifndef PADDLE_WITH_HIP
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cusolverDnCreate
(
&
solver_handle_
));
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cusolverDnSetStream
(
solver_handle_
,
stream_
));
#endif
}
void
DestroyInternalSolverHandle
()
{
#ifndef PADDLE_WITH_HIP
if
(
owned_
&&
solver_handle_
!=
nullptr
)
{
PADDLE_ENFORCE_GPU_SUCCESS
(
phi
::
dynload
::
cusolverDnDestroy
(
solver_handle_
));
solver_handle_
=
nullptr
;
}
#endif
}
solverHandle_t
GetSolverHandle
()
const
{
PD_CHECK
(
solver_handle_
!=
nullptr
,
"the gpu solver handle is nullptr."
);
return
solver_handle_
;
...
...
@@ -568,29 +405,6 @@ struct GPUContext::Impl {
void
SetSolverHandle
(
solverHandle_t
handle
)
{
solver_handle_
=
handle
;
}
void
InitSparseHandle
()
{
// ROCM is not yet supported
#if defined(PADDLE_WITH_CUDA)
// The generic APIs is supported from CUDA10.1
#if CUDA_VERSION >= 10010
PADDLE_RETRY_CUDA_SUCCESS
(
dynload
::
cusparseCreate
(
&
sparse_handle_
));
PADDLE_RETRY_CUDA_SUCCESS
(
dynload
::
cusparseSetStream
(
sparse_handle_
,
stream_
));
#endif
#endif
}
void
DestroyInternalSparseHandle
()
{
#ifdef PADDLE_WITH_CUDA
#if CUDA_VERSION >= 10010
if
(
owned_
&&
sparse_handle_
!=
nullptr
)
{
PADDLE_RETRY_CUDA_SUCCESS
(
dynload
::
cusparseDestroy
(
sparse_handle_
));
sparse_handle_
=
nullptr
;
}
#endif
#endif
}
sparseHandle_t
GetSparseHandle
()
const
{
PD_CHECK
(
sparse_handle_
!=
nullptr
,
"the gpu sparse handle is nullptr."
);
return
sparse_handle_
;
...
...
@@ -878,7 +692,10 @@ void GPUContext::Init() {
impl_
->
Init
();
}
void
GPUContext
::
SetStream
(
gpuStream_t
stream
)
{
impl_
->
SetStream
(
stream
);
}
void
GPUContext
::
SetStream
(
gpuStream_t
stream
)
{
impl_
->
allocator_
=
const_cast
<
Allocator
*>
(
&
this
->
GetAllocator
());
impl_
->
SetStream
(
stream
);
}
void
GPUContext
::
SetEigenDevice
(
Eigen
::
GpuDevice
*
device
)
{
impl_
->
SetEigenDevice
(
device
);
...
...
@@ -888,6 +705,14 @@ void GPUContext::SetBlasHandle(blasHandle_t blas) {
impl_
->
SetBlasHandle
(
blas
);
}
void
GPUContext
::
SetBlasTensorCoreHandle
(
blasHandle_t
handle
)
{
impl_
->
SetBlasTensorCoreHandle
(
handle
);
}
void
GPUContext
::
SetBlasTF32Handle
(
blasHandle_t
handle
)
{
impl_
->
SetBlasTF32Handle
(
handle
);
}
void
GPUContext
::
SetBlasLtHandle
(
blasLtHandle_t
blaslt
)
{
impl_
->
SetBlasLtHandle
(
blaslt
);
}
...
...
paddle/phi/backends/gpu/gpu_context.h
浏览文件 @
1280f294
...
...
@@ -199,6 +199,10 @@ class PADDLE_API GPUContext : public DeviceContext {
void
SetBlasHandle
(
blasHandle_t
);
void
SetBlasTensorCoreHandle
(
blasHandle_t
);
void
SetBlasTF32Handle
(
blasHandle_t
);
void
SetBlasLtHandle
(
blasLtHandle_t
);
void
SetDnnHandle
(
dnnHandle_t
);
...
...
paddle/phi/backends/gpu/gpu_resources.cc
0 → 100644
浏览文件 @
1280f294
// 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.
#include "paddle/phi/backends/gpu/gpu_resources.h"
#include "paddle/phi/api/include/tensor.h"
#include "paddle/phi/backends/gpu/gpu_decls.h"
#include "paddle/phi/backends/gpu/gpu_info.h"
#include "paddle/phi/common/place.h"
#include "paddle/phi/core/allocator.h"
#ifdef PADDLE_WITH_CUDA
#include "paddle/phi/backends/dynload/cublas.h"
#include "paddle/phi/backends/dynload/cudnn.h"
#include "paddle/phi/backends/dynload/cusolver.h"
#include "paddle/phi/backends/dynload/cusparse.h"
#if !defined(__APPLE__) && defined(PADDLE_WITH_NCCL)
#include "paddle/phi/backends/dynload/nccl.h"
#endif // !defined(__APPLE__) && defined(PADDLE_WITH_NCCL)
#endif // PADDLE_WITH_CUDA
#include "unsupported/Eigen/CXX11/Tensor"
// TODO(phi): remove fluid header.
#include "paddle/fluid/platform/enforce.h"
namespace
phi
{
void
InitGpuProperties
(
Place
place
,
int
*
compute_capability
,
int
*
runtime_version
,
int
*
driver_version
,
int
*
multi_process
,
int
*
max_threads_per_mp
,
int
*
max_threads_per_block
,
std
::
array
<
int
,
3
>*
max_grid_dim_size
)
{
backends
::
gpu
::
GPUDeviceGuard
guard
(
place
.
GetDeviceId
());
*
compute_capability
=
backends
::
gpu
::
GetGPUComputeCapability
(
place
.
GetDeviceId
());
*
multi_process
=
backends
::
gpu
::
GetGPUMultiProcessors
(
place
.
GetDeviceId
());
*
max_threads_per_mp
=
backends
::
gpu
::
GetGPUMaxThreadsPerMultiProcessor
(
place
.
GetDeviceId
());
*
max_grid_dim_size
=
backends
::
gpu
::
GetGpuMaxGridDimSize
(
place
.
GetDeviceId
());
*
max_threads_per_block
=
backends
::
gpu
::
GetGPUMaxThreadsPerBlock
(
place
.
GetDeviceId
());
*
driver_version
=
backends
::
gpu
::
GetGPUDriverVersion
(
place
.
GetDeviceId
());
*
runtime_version
=
backends
::
gpu
::
GetGPURuntimeVersion
(
place
.
GetDeviceId
());
// TODO(wilber): glog may be replaced in the future?
LOG_FIRST_N
(
WARNING
,
1
)
<<
"Please NOTE: device: "
<<
static_cast
<
int
>
(
place
.
device
)
<<
", GPU Compute Capability: "
<<
*
compute_capability
/
10
<<
"."
<<
*
compute_capability
%
10
<<
", Driver API Version: "
<<
*
driver_version
/
1000
<<
"."
<<
(
*
driver_version
%
100
)
/
10
<<
", Runtime API Version: "
<<
*
runtime_version
/
1000
<<
"."
<<
(
*
runtime_version
%
100
)
/
10
;
#ifdef PADDLE_WITH_HIP
size_t
miopen_major
,
miopen_minor
,
miopen_patch
;
PADDLE_ENFORCE_GPU_SUCCESS
(
dynload
::
miopenGetVersion
(
&
miopen_major
,
&
miopen_minor
,
&
miopen_patch
));
auto
cudnn_dso_ver
=
(
miopen_major
*
1000
+
miopen_minor
*
10
+
miopen_patch
)
/
10
;
auto
compile_miopen_version
=
MIOPEN_VERSION
/
10
;
if
(
cudnn_dso_ver
<
static_cast
<
size_t
>
(
compile_miopen_version
))
{
LOG_FIRST_N
(
WARNING
,
1
)
<<
"WARNING: device: "
<<
static_cast
<
int
>
(
place
.
device
)
<<
". The installed Paddle is compiled with MIOPEN "
<<
compile_miopen_version
/
100
<<
"."
<<
compile_miopen_version
%
100
<<
", but MIOPEN version in your machine is "
<<
cudnn_dso_ver
/
100
<<
"."
<<
cudnn_dso_ver
%
100
<<
", which may cause serious incompatible bug. "
<<
"Please recompile or reinstall Paddle with compatible MIOPEN "
"version."
;
}
#else
size_t
cudnn_dso_ver
=
dynload
::
cudnnGetVersion
();
LOG_FIRST_N
(
WARNING
,
1
)
<<
"device: "
<<
static_cast
<
int
>
(
place
.
device
)
<<
", cuDNN Version: "
<<
cudnn_dso_ver
/
1000
<<
"."
<<
(
cudnn_dso_ver
%
1000
)
/
100
<<
"."
;
// Check CUDA/CUDNN version compatiblity
auto
local_cuda_version
=
(
*
driver_version
/
1000
)
*
10
+
(
*
driver_version
%
100
)
/
10
;
auto
compile_cuda_version
=
(
CUDA_VERSION
/
1000
)
*
10
+
(
CUDA_VERSION
%
100
)
/
10
;
if
(
local_cuda_version
<
compile_cuda_version
)
{
LOG_FIRST_N
(
WARNING
,
1
)
<<
"WARNING: device: "
<<
static_cast
<
int
>
(
place
.
device
)
<<
". The installed Paddle is compiled with CUDA "
<<
compile_cuda_version
/
10
<<
"."
<<
compile_cuda_version
%
10
<<
", but CUDA runtime version in your machine is "
<<
local_cuda_version
/
10
<<
"."
<<
local_cuda_version
%
10
<<
", which may cause serious incompatible bug. "
<<
"Please recompile or reinstall Paddle with compatible CUDA "
"version."
;
}
#endif
}
void
InitStream
(
gpuStream_t
*
stream
)
{
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_GPU_SUCCESS
(
hipStreamCreateWithPriority
(
stream
,
hipStreamDefault
,
0
));
#else
PADDLE_ENFORCE_GPU_SUCCESS
(
cudaStreamCreateWithPriority
(
stream
,
cudaStreamDefault
,
0
));
#endif
}
void
DestoryStream
(
gpuStream_t
stream
)
{
if
(
stream
!=
nullptr
)
{
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_GPU_SUCCESS
(
hipStreamDestroy
(
stream
));
#else
PADDLE_ENFORCE_GPU_SUCCESS
(
cudaStreamDestroy
(
stream
));
#endif
}
stream
=
nullptr
;
}
void
InitBlasHandle
(
blasHandle_t
*
blas_handle
,
gpuStream_t
stream
)
{
#ifdef PADDLE_WITH_HIP
phi
::
dynload
::
rocblas_create_handle
(
blas_handle
);
phi
::
dynload
::
rocblas_set_stream
(
*
blas_handle
,
stream
);
#else // PADDLE_WITH_CUDA
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasCreate
(
blas_handle
));
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cublasSetStream
(
*
blas_handle
,
stream
));
#endif // PADDLE_WITH_HIP
}
void
DestroyBlasHandle
(
blasHandle_t
handle
)
{
#ifdef PADDLE_WITH_HIP
if
(
handle
!=
nullptr
)
{
phi
::
dynload
::
rocblas_destroy_handle
(
handle
);
handle
=
nullptr
;
}
#else
if
(
handle
!=
nullptr
)
{
phi
::
dynload
::
cublasDestroy
(
handle
);
handle
=
nullptr
;
}
#endif // PADDLE_WITH_HIP
}
void
InitBlasLtHandle
(
blasLtHandle_t
*
blaslt_handle
)
{
#if defined(PADDLE_WITH_CUDA) && CUDA_VERSION >= 11060
phi
::
dynload
::
cublasLtCreate
(
blaslt_handle
);
#endif
}
void
DestroyBlasLtHandle
(
blasLtHandle_t
handle
)
{
#if defined(PADDLE_WITH_CUDA) && CUDA_VERSION >= 11060
if
(
handle
!=
nullptr
)
{
phi
::
dynload
::
cublasLtDestroy
(
handle
);
handle
=
nullptr
;
}
#endif
}
void
InitDnnHandle
(
dnnHandle_t
*
handle
,
gpuStream_t
stream
,
Place
place
)
{
if
(
phi
::
dynload
::
HasCUDNN
())
{
#ifdef PADDLE_WITH_HIP
size_t
miopen_major
,
miopen_minor
,
miopen_patch
;
PADDLE_ENFORCE_GPU_SUCCESS
(
dynload
::
miopenGetVersion
(
&
miopen_major
,
&
miopen_minor
,
&
miopen_patch
));
auto
local_miopen_version
=
(
miopen_major
*
1000
+
miopen_minor
*
10
+
miopen_patch
)
/
10
;
auto
compile_miopen_version
=
MIOPEN_VERSION
/
10
;
if
(
local_miopen_version
<
static_cast
<
size_t
>
(
compile_miopen_version
))
{
LOG_FIRST_N
(
WARNING
,
1
)
<<
"WARNING: device: "
<<
place
.
device
<<
". The installed Paddle is compiled with MIOPEN "
<<
compile_miopen_version
/
100
<<
"."
<<
compile_miopen_version
%
100
<<
", but MIOPEN version in your machine is "
<<
local_miopen_version
/
100
<<
"."
<<
local_miopen_version
%
100
<<
", which may cause serious incompatible bug. "
<<
"Please recompile or reinstall Paddle with compatible MIOPEN "
"version."
;
}
PADDLE_ENFORCE_GPU_SUCCESS
(
dynload
::
miopenCreate
(
handle
));
PADDLE_ENFORCE_GPU_SUCCESS
(
dynload
::
miopenSetStream
(
*
handle
,
stream
));
#else
auto
local_cudnn_version
=
phi
::
dynload
::
cudnnGetVersion
()
/
100
;
auto
compile_cudnn_version
=
CUDNN_VERSION
/
100
;
if
(
local_cudnn_version
<
static_cast
<
size_t
>
(
compile_cudnn_version
))
{
LOG_FIRST_N
(
WARNING
,
1
)
<<
"WARNING: device: "
<<
place
.
device
<<
". The installed Paddle is compiled with CUDNN "
<<
compile_cudnn_version
/
10
<<
"."
<<
compile_cudnn_version
%
10
<<
", but CUDNN version in your machine is "
<<
local_cudnn_version
/
10
<<
"."
<<
local_cudnn_version
%
10
<<
", which may cause serious incompatible bug. "
<<
"Please recompile or reinstall Paddle with compatible CUDNN "
"version."
;
}
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cudnnCreate
(
handle
));
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cudnnSetStream
(
*
handle
,
stream
));
#endif
}
else
{
*
handle
=
nullptr
;
}
}
void
DestroyDnnHandle
(
dnnHandle_t
handle
)
{
#ifdef PADDLE_WITH_HIP
if
(
handle
!=
nullptr
)
{
PADDLE_ENFORCE_GPU_SUCCESS
(
phi
::
dynload
::
miopenDestroy
(
handle
));
handle
=
nullptr
;
}
#else
if
(
handle
!=
nullptr
)
{
PADDLE_ENFORCE_GPU_SUCCESS
(
phi
::
dynload
::
cudnnDestroy
(
handle
));
handle
=
nullptr
;
}
#endif // PADDLE_WITH_HIP
}
void
InitSolverHandle
(
solverHandle_t
*
handle
,
gpuStream_t
stream
)
{
#ifndef PADDLE_WITH_HIP
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cusolverDnCreate
(
handle
));
PADDLE_RETRY_CUDA_SUCCESS
(
phi
::
dynload
::
cusolverDnSetStream
(
*
handle
,
stream
));
#endif
}
void
DestroySolverHandle
(
solverHandle_t
solver_handle
)
{
#ifndef PADDLE_WITH_HIP
if
(
solver_handle
!=
nullptr
)
{
PADDLE_ENFORCE_GPU_SUCCESS
(
phi
::
dynload
::
cusolverDnDestroy
(
solver_handle
));
solver_handle
=
nullptr
;
}
#endif
}
void
InitSparseHandle
(
sparseHandle_t
*
handle
,
gpuStream_t
stream
)
{
// ROCM is not yet supported
#if defined(PADDLE_WITH_CUDA)
// The generic APIs is supported from CUDA10.1
#if CUDA_VERSION >= 10010
PADDLE_RETRY_CUDA_SUCCESS
(
dynload
::
cusparseCreate
(
handle
));
PADDLE_RETRY_CUDA_SUCCESS
(
dynload
::
cusparseSetStream
(
*
handle
,
stream
));
#endif
#endif
}
void
DestroySparseHandle
(
sparseHandle_t
handle
)
{
#ifdef PADDLE_WITH_CUDA
#if CUDA_VERSION >= 10010
if
(
handle
!=
nullptr
)
{
PADDLE_RETRY_CUDA_SUCCESS
(
dynload
::
cusparseDestroy
(
handle
));
handle
=
nullptr
;
}
#endif
#endif
}
}
// namespace phi
paddle/phi/backends/gpu/gpu_resources.h
0 → 100644
浏览文件 @
1280f294
// 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 <array>
#include "paddle/phi/backends/gpu/gpu_decls.h"
#include "paddle/phi/common/place.h"
namespace
phi
{
void
InitGpuProperties
(
Place
place
,
int
*
compute_capability
,
int
*
runtime_version
,
int
*
driver_version
,
int
*
multi_process
,
int
*
max_threads_per_mp
,
int
*
max_threads_per_block
,
std
::
array
<
int
,
3
>*
max_grid_dim_size
);
void
InitStream
(
gpuStream_t
*
stream
);
void
DestoryStream
(
gpuStream_t
stream
);
void
InitBlasHandle
(
blasHandle_t
*
blas_handle
,
gpuStream_t
stream
);
void
DestroyBlasHandle
(
blasHandle_t
handle
);
void
InitBlasLtHandle
(
blasLtHandle_t
*
blaslt_handle
);
void
DestroyBlasLtHandle
(
blasLtHandle_t
handle
);
void
InitDnnHandle
(
dnnHandle_t
*
handle
,
gpuStream_t
stream
,
Place
place
);
void
DestroyDnnHandle
(
dnnHandle_t
handle
);
void
InitSolverHandle
(
solverHandle_t
*
handle
,
gpuStream_t
stream
);
void
DestroySolverHandle
(
solverHandle_t
solver_handle
);
void
InitSparseHandle
(
sparseHandle_t
*
handle
,
gpuStream_t
stream
);
void
DestroySparseHandle
(
sparseHandle_t
handle
);
// void InitDnnWorkspace();
}
// namespace phi
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