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host_mem_allocator.h 1.7 kB

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  1. /**
  2. * Copyright 2019-2020 Huawei Technologies Co., Ltd
  3. *
  4. * Licensed under the Apache License, Version 2.0 (the "License");
  5. * you may not use this file except in compliance with the License.
  6. * You may obtain a copy of the License at
  7. *
  8. * http://www.apache.org/licenses/LICENSE-2.0
  9. *
  10. * Unless required by applicable law or agreed to in writing, software
  11. * distributed under the License is distributed on an "AS IS" BASIS,
  12. * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13. * See the License for the specific language governing permissions and
  14. * limitations under the License.
  15. */
  16. #ifndef GE_GRAPH_MANAGER_HOST_MEM_ALLOCATOR_H_
  17. #define GE_GRAPH_MANAGER_HOST_MEM_ALLOCATOR_H_
  18. #include <mutex>
  19. #include <map>
  20. #include "framework/common/ge_inner_error_codes.h"
  21. #include "graph/aligned_ptr.h"
  22. #include "runtime/mem.h"
  23. namespace ge {
  24. class HostMemAllocator {
  25. public:
  26. explicit HostMemAllocator(rtMemType_t) {}
  27. ~HostMemAllocator() = default;
  28. HostMemAllocator(const HostMemAllocator &) = delete;
  29. HostMemAllocator &operator=(const HostMemAllocator &) = delete;
  30. Status Initialize() {
  31. Clear();
  32. return SUCCESS;
  33. }
  34. void Finalize() { Clear(); }
  35. const void *Malloc(const std::shared_ptr<AlignedPtr>& aligned_ptr, size_t size);
  36. uint8_t *Malloc(size_t size);
  37. Status Free(const void *memory_addr);
  38. std::pair<size_t, std::shared_ptr<AlignedPtr>> GetAlignedPtr(const void *addr) { return allocated_blocks_[addr]; }
  39. private:
  40. void Clear();
  41. std::map<const void *, std::pair<size_t, std::shared_ptr<AlignedPtr>>> allocated_blocks_;
  42. // lock around all operations
  43. mutable std::mutex mutex_;
  44. };
  45. } // namespace ge
  46. #endif // GE_GRAPH_MANAGER_HOST_MEM_ALLOCATOR_H_

图引擎模块(GE)是MindSpore的一个子模块,其代码由C++实现,位于前端模块ME和底层硬件之间,起到承接作用。图引擎模块以ME下发的图作为输入,然后进行一系列的深度图优化操作,最后输出一张可以在底层硬件上高效运行的图。GE针对昇腾AI处理器的硬件结构特点,做了特定的优化工作,以此来充分发挥出昇腾AI处理器的强大算力。在进行模型训练/推理时,GE会被自动调用而用户并不感知。GE主要由GE API和GE Core两部分组成,详细的架构图如下所示