wehub-resource-sync
61 lines
2.4 KiB
C++
61 lines
2.4 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <Python.h>
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#include "paddle/phi/common/data_type.h"
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#include "paddle/phi/core/compat/convert_utils.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/tensor_utils.h"
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namespace paddle {
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namespace pybind {
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static void tensor_uva(DenseTensor *self_tensor, int device_id) {
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VLOG(4) << "Running in _uva interface.";
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#if defined(PADDLE_WITH_CUDA)
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phi::DeviceContextPool &pool = phi::DeviceContextPool::Instance();
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auto *dev_ctx = pool.Get(GPUPlace(device_id));
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VLOG(4) << "Init the DeviceContext, and the place is " << dev_ctx->GetPlace();
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// Register the cpu memory as the cuda host memory
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const auto &data_numel = self_tensor->numel();
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const size_t &need_allocate_size =
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data_numel * framework::SizeOfType(
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framework::TransToProtoVarType(self_tensor->dtype()));
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void *data_ptr = self_tensor->data();
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auto result =
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cudaHostRegister(data_ptr, need_allocate_size, cudaHostRegisterDefault);
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if (cudaSuccess != result) {
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VLOG(4) << "UVA(unified virtual addressing) failed allocate:"
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<< need_allocate_size << ", the error code:" << result;
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}
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// Get device pointer from the function of cudaHostGetDevicePointer
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void *cuda_device_pointer = nullptr;
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cudaHostGetDevicePointer(reinterpret_cast<void **>(&cuda_device_pointer),
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reinterpret_cast<void *>(data_ptr),
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0);
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// Reset the memory with device pointer
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std::shared_ptr<memory::allocation::Allocation> holder =
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std::make_shared<memory::allocation::Allocation>(
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cuda_device_pointer, need_allocate_size, GPUPlace(device_id));
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self_tensor->ResetHolderWithType(holder, self_tensor->dtype());
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#endif
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}
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} // namespace pybind
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} // namespace paddle
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