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npu_memory_allocator.cc 4.7 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. #include "npu_memory_allocator.h"
  17. #include <mutex>
  18. #include "framework/common/debug/log.h"
  19. #include "graph/manager/graph_caching_allocator.h"
  20. #include "graph/manager/graph_mem_allocator.h"
  21. #include "graph/manager/rdma_pool_allocator.h"
  22. namespace ge {
  23. namespace hybrid {
  24. size_t kMaxHbmMemorySize = 1024UL * 1024UL * 1024UL * 1024UL; // 1024G
  25. std::map<uint32_t, std::unique_ptr<NpuMemoryAllocator>> NpuMemoryAllocator::allocators_;
  26. std::mutex NpuMemoryAllocator::mu_;
  27. AllocationAttr::AllocationAttr(int padding, void *try_reuse_addr, MemStorageType mem_type)
  28. : padding_(padding), try_reuse_addr_(try_reuse_addr), mem_type_(mem_type) {}
  29. AllocationAttr::AllocationAttr(int padding) : AllocationAttr(padding, nullptr) {}
  30. AllocationAttr::AllocationAttr(void *try_reuse_addr) : AllocationAttr(0, try_reuse_addr) {}
  31. NpuMemoryAllocator *NpuMemoryAllocator::GetAllocator() {
  32. int32_t device_id = 0;
  33. if (rtGetDevice(&device_id) != RT_ERROR_NONE) {
  34. GELOGE(RT_FAILED, "Failed to get device id");
  35. return nullptr;
  36. }
  37. GELOGD("Got device id = %d from context", device_id);
  38. return GetAllocator(static_cast<uint32_t>(device_id));
  39. }
  40. NpuMemoryAllocator::NpuMemoryAllocator(uint32_t device_id) : device_id_(device_id) {}
  41. void *NpuMemoryAllocator::Allocate(std::size_t size, AllocationAttr *attr) {
  42. size_t allocate_size = size;
  43. MemStorageType mem_type = HBM;
  44. if (attr != nullptr) {
  45. mem_type = attr->mem_type_;
  46. }
  47. if (allocate_size == 0) {
  48. GELOGE(MEMALLOC_FAILED, "Memory size is 0, device_id = %u, size = %zu", device_id_, allocate_size);
  49. return nullptr;
  50. }
  51. void *buffer = nullptr;
  52. if (mem_type == RDMA_HBM) {
  53. buffer = MemManager::Instance().RdmaPoolInstance(RT_MEMORY_HBM).Malloc(allocate_size, device_id_);
  54. } else if (mem_type == HOST_DDR) {
  55. buffer = malloc(allocate_size);
  56. } else {
  57. if (allocate_size > kMaxHbmMemorySize) {
  58. GELOGE(PARAM_INVALID, "Invalid HBM memory size: %zu", allocate_size);
  59. return nullptr;
  60. }
  61. void *try_reuse_addr = nullptr;
  62. int padding = kDefaultPadding;
  63. if (attr != nullptr) {
  64. try_reuse_addr = attr->try_reuse_addr_;
  65. if (attr->padding_ > 0) {
  66. padding = attr->padding_;
  67. }
  68. }
  69. // padding up to multiple of padding, and add extra padding
  70. allocate_size = (size + 2 * padding - 1) / padding * padding;
  71. GELOGD("Padding size %ld by %d. final size = %zu.", size, padding, allocate_size);
  72. buffer = MemManager::Instance()
  73. .CachingInstance(RT_MEMORY_HBM)
  74. .Malloc(allocate_size, reinterpret_cast<uint8_t *>(try_reuse_addr), device_id_);
  75. }
  76. if (buffer == nullptr) {
  77. GELOGE(MEMALLOC_FAILED, "Failed to malloc memory, device_id = %u, size = %zu", device_id_, allocate_size);
  78. return nullptr;
  79. }
  80. GELOGI("Allocating buffer of size %zu successfully. device_id = %u, address = %p", allocate_size, device_id_, buffer);
  81. return buffer;
  82. }
  83. void NpuMemoryAllocator::Deallocate(void *data, MemStorageType mem_type) {
  84. GELOGI("To deallocating buffer, addr = %p", data);
  85. if (data != nullptr) {
  86. GELOGI("Deallocating buffer successfully. addr = %p", data);
  87. if (mem_type == RDMA_HBM) {
  88. MemManager::Instance().RdmaPoolInstance(RT_MEMORY_HBM).Free(reinterpret_cast<uint8_t *>(data), device_id_);
  89. } else if (mem_type == HOST_DDR) {
  90. free(data);
  91. } else {
  92. MemManager::Instance().CachingInstance(RT_MEMORY_HBM).Free(reinterpret_cast<uint8_t *>(data), device_id_);
  93. }
  94. }
  95. }
  96. NpuMemoryAllocator *NpuMemoryAllocator::GetAllocator(uint32_t device_id) {
  97. std::lock_guard<std::mutex> lk(mu_);
  98. auto it = allocators_.find(device_id);
  99. if (it == allocators_.end()) {
  100. auto allocator = std::unique_ptr<NpuMemoryAllocator>(new (std::nothrow) NpuMemoryAllocator(device_id));
  101. if (allocator == nullptr) {
  102. return nullptr;
  103. }
  104. allocators_.emplace(device_id, std::move(allocator));
  105. }
  106. return allocators_[device_id].get();
  107. }
  108. void NpuMemoryAllocator::DestroyAllocator() {
  109. std::lock_guard<std::mutex> lk(mu_);
  110. int device_id = 0;
  111. allocators_.erase(device_id);
  112. }
  113. } // namespace hybrid
  114. } // namespace ge

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