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op_task.cc 33 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 "single_op/task/op_task.h"
  17. #include <google/protobuf/extension_set.h>
  18. #include <chrono>
  19. #include <thread>
  20. #include "aicpu/common/aicpu_task_struct.h"
  21. #include "common/dump/dump_manager.h"
  22. #include "common/dump/dump_op.h"
  23. #include "common/formats/formats.h"
  24. #include "common/math/math_util.h"
  25. #include "framework/common/debug/log.h"
  26. #include "register/op_tiling.h"
  27. #include "runtime/rt.h"
  28. #include "build_task_utils.h"
  29. namespace ge {
  30. namespace {
  31. constexpr int kLaunchRetryTimes = 1000;
  32. constexpr int kSleepTime = 10;
  33. constexpr uint64_t kReleaseFlag = 1;
  34. constexpr int kCopyNum = 2;
  35. void FreeHbm(void *var) {
  36. if (var) {
  37. (void)rtFree(var);
  38. }
  39. }
  40. } // namespace
  41. Status OpTask::OpenDump(rtStream_t stream) {
  42. if (DumpManager::GetInstance().GetDumpProperties().IsSingleOpNeedDump()) {
  43. GELOGI("Dump is open in single op,start to set dump info");
  44. std::vector<uint64_t> input_addrs;
  45. std::vector<uint64_t> output_adds;
  46. auto input_size = op_desc_->GetInputsSize();
  47. auto output_size = op_desc_->GetOutputsSize();
  48. uintptr_t *arg_base = nullptr;
  49. size_t arg_num = 0;
  50. GetIoAddr(arg_base, arg_num);
  51. if (arg_num < input_size + output_size) {
  52. GELOGE(FAILED, "io_addrs_for_dump_ size %zu is not equal input and output size %zu",
  53. arg_num,
  54. input_size + output_size);
  55. return FAILED;
  56. }
  57. for (size_t i = 0; i < input_size; i++) {
  58. uint64_t input_addr = arg_base[i];
  59. input_addrs.emplace_back(input_addr);
  60. }
  61. for (size_t j = 0; j < output_size; j++) {
  62. uint64_t output_addr = arg_base[input_size + j];
  63. output_adds.emplace_back(output_addr);
  64. }
  65. dump_op_.SetDumpInfo(DumpManager::GetInstance().GetDumpProperties(), op_desc_, input_addrs, output_adds, stream);
  66. auto status = dump_op_.LaunchDumpOp();
  67. if (status != SUCCESS) {
  68. GELOGE(status, "Launch dump op failed in single op");
  69. return status;
  70. }
  71. return SUCCESS;
  72. }
  73. GELOGI("Dump is not open in single op");
  74. return SUCCESS;
  75. }
  76. void TbeOpTask::SetStubFunc(const std::string &name, const void *stub_func) {
  77. this->stub_name_ = name;
  78. this->stub_func_ = stub_func;
  79. }
  80. void TbeOpTask::SetKernelArgs(std::unique_ptr<uint8_t[]> &&args, size_t arg_size, uint32_t block_dim,
  81. const OpDescPtr &op_desc) {
  82. args_ = std::move(args);
  83. arg_size_ = arg_size;
  84. block_dim_ = block_dim;
  85. op_desc_ = op_desc;
  86. }
  87. void TbeOpTask::SetSmDesc(void *sm_desc) { sm_desc_ = sm_desc; }
  88. void OpTask::SetModelArgs(std::string model_name, uint32_t model_id) {
  89. model_name_ = model_name;
  90. model_id_ = model_id;
  91. }
  92. Status OpTask::GetProfilingArgs(std::string &model_name, std::string &op_name, uint32_t &model_id,
  93. uint32_t &block_dim) {
  94. model_name = model_name_;
  95. model_id = model_id_;
  96. block_dim = block_dim_;
  97. GE_CHECK_NOTNULL(op_desc_);
  98. op_name = op_desc_->GetName();
  99. return SUCCESS;
  100. }
  101. Status OpTask::UpdateRunInfo(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc) {
  102. return UNSUPPORTED;
  103. }
  104. Status OpTask::UpdateArgTable(const SingleOpModelParam &param) {
  105. auto addresses = BuildTaskUtils::GetAddresses(op_desc_, param);
  106. auto all_addresses = BuildTaskUtils::JoinAddresses(addresses);
  107. uintptr_t *arg_base = nullptr;
  108. size_t arg_num = 0;
  109. GetIoAddr(arg_base, arg_num);
  110. if (arg_num != all_addresses.size()) {
  111. GELOGE(INTERNAL_ERROR, "[%s] arg number mismatches, expect = %zu, but got = %zu",
  112. op_desc_->GetName().c_str(),
  113. arg_num,
  114. all_addresses.size());
  115. return INTERNAL_ERROR;
  116. }
  117. for (void *addr : all_addresses) {
  118. *arg_base++ = reinterpret_cast<uintptr_t >(addr);
  119. }
  120. return SUCCESS;
  121. }
  122. Status OpTask::LaunchKernel(const vector<GeTensorDesc> &input_desc,
  123. const vector<DataBuffer> &input_buffers,
  124. vector<GeTensorDesc> &output_desc,
  125. vector<DataBuffer> &output_buffers,
  126. rtStream_t stream) {
  127. return UNSUPPORTED;
  128. }
  129. TbeOpTask::~TbeOpTask() {
  130. if (sm_desc_ != nullptr) {
  131. (void)rtMemFreeManaged(sm_desc_);
  132. }
  133. if (tiling_buffer_ != nullptr) {
  134. (void)rtFree(tiling_buffer_);
  135. }
  136. }
  137. const void *TbeOpTask::GetArgs() const { return args_.get(); }
  138. size_t TbeOpTask::GetArgSize() const { return arg_size_; }
  139. const std::string &TbeOpTask::GetStubName() const { return stub_name_; }
  140. Status TbeOpTask::LaunchKernel(rtStream_t stream) {
  141. GELOGD("To invoke rtKernelLaunch. task = %s, block_dim = %u", this->stub_name_.c_str(), block_dim_);
  142. auto *sm_desc = reinterpret_cast<rtSmDesc_t *>(sm_desc_);
  143. auto ret = rtKernelLaunch(stub_func_, block_dim_, args_.get(), static_cast<uint32_t>(arg_size_), sm_desc, stream);
  144. int retry_times = 0;
  145. while (ret != RT_ERROR_NONE && retry_times < kLaunchRetryTimes) {
  146. retry_times++;
  147. GELOGW("Retry after %d ms, retry_times: %d", kSleepTime, retry_times);
  148. std::this_thread::sleep_for(std::chrono::milliseconds(kSleepTime));
  149. ret = rtKernelLaunch(stub_func_, block_dim_, args_.get(), arg_size_, sm_desc, stream);
  150. }
  151. if (ret != RT_ERROR_NONE) {
  152. GELOGE(RT_FAILED, "Invoke rtKernelLaunch failed. ret = %d, task = %s", ret, this->stub_name_.c_str());
  153. return RT_FAILED;
  154. }
  155. GELOGI("[TASK_INFO] %s", this->stub_name_.c_str());
  156. auto status = OpenDump(stream);
  157. if (status != SUCCESS) {
  158. GELOGE(status, "Open dump failed in the tbe single op %s", this->stub_name_.c_str());
  159. return status;
  160. }
  161. return SUCCESS;
  162. }
  163. Status TbeOpTask::UpdateRunInfo(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc) {
  164. GE_CHK_STATUS_RET_NOLOG(UpdateNodeByShape(input_desc, output_desc));
  165. // invoke OpParaCalculate
  166. GELOGD("Start to invoke OpParaCalculate.");
  167. optiling::OpRunInfo run_info;
  168. run_info.block_dim = 0;
  169. auto ret = optiling::OpParaCalculate(*node_, run_info);
  170. if (ret != GRAPH_SUCCESS) {
  171. GELOGE(FAILED, "Failed to invoke OpParaCalculate. ret = %u", ret);
  172. return FAILED;
  173. }
  174. block_dim_ = run_info.block_dim;
  175. tiling_data_ = run_info.tiling_data.str();
  176. GELOGD("Done invoking OpParaCalculate successfully. block_dim = %u, tiling size = %zu", block_dim_,
  177. tiling_data_.size());
  178. GE_CHK_STATUS_RET(AllocateWorkspaces(run_info.workspaces), "Failed to allocate workspaces");
  179. return SUCCESS;
  180. }
  181. Status TbeOpTask::UpdateTensorDesc(const GeTensorDesc &src_tensor, GeTensorDesc &dst_tensor) {
  182. int64_t storage_format_val = static_cast<Format>(FORMAT_RESERVED);
  183. (void)AttrUtils::GetInt(src_tensor, ge::ATTR_NAME_STORAGE_FORMAT, storage_format_val);
  184. auto storage_format = static_cast<Format>(storage_format_val);
  185. if (storage_format == FORMAT_RESERVED) {
  186. GELOGD("Storage format not set. update shape to [%s], and original shape to [%s]",
  187. src_tensor.GetShape().ToString().c_str(), src_tensor.GetOriginShape().ToString().c_str());
  188. dst_tensor.SetShape(src_tensor.GetShape());
  189. dst_tensor.SetOriginShape(src_tensor.GetOriginShape());
  190. } else {
  191. std::vector<int64_t> storage_shape;
  192. if (!AttrUtils::GetListInt(src_tensor, ge::ATTR_NAME_STORAGE_SHAPE, storage_shape)) {
  193. GELOGE(PARAM_INVALID, "Failed to get storage_shape while storage_format was set");
  194. return PARAM_INVALID;
  195. }
  196. GELOGD("Storage format set. update shape to [%s], and original shape to [%s]",
  197. GeShape(storage_shape).ToString().c_str(), src_tensor.GetShape().ToString().c_str());
  198. dst_tensor.SetShape(GeShape(std::move(storage_shape)));
  199. dst_tensor.SetOriginShape(src_tensor.GetShape());
  200. }
  201. return SUCCESS;
  202. }
  203. Status TbeOpTask::UpdateNodeByShape(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc) {
  204. auto op_desc = node_->GetOpDesc();
  205. GE_CHECK_NOTNULL(op_desc);
  206. // Set runtime shape to node
  207. for (size_t i = 0; i < input_desc.size(); ++i) {
  208. auto tensor_desc = op_desc->MutableInputDesc(i);
  209. auto &runtime_tensor_desc = input_desc[i];
  210. GE_CHECK_NOTNULL(tensor_desc);
  211. GE_CHK_STATUS_RET(UpdateTensorDesc(runtime_tensor_desc, *tensor_desc));
  212. }
  213. for (size_t i = 0; i < output_desc.size(); ++i) {
  214. auto tensor_desc = op_desc->MutableOutputDesc(i);
  215. auto &runtime_tensor_desc = output_desc[i];
  216. GE_CHECK_NOTNULL(tensor_desc);
  217. GE_CHK_STATUS_RET(UpdateTensorDesc(runtime_tensor_desc, *tensor_desc));
  218. }
  219. return SUCCESS;
  220. }
  221. void TbeOpTask::EnableDynamicSupport(const NodePtr &node, void *tiling_buffer, size_t max_tiling_size) {
  222. node_ = node;
  223. tiling_buffer_ = tiling_buffer;
  224. max_tiling_size_ = max_tiling_size;
  225. }
  226. Status TbeOpTask::AllocateWorkspaces(const vector<int64_t> &workspace_sizes) {
  227. static const std::string kPurpose("malloc workspace memory for dynamic op.");
  228. if (workspace_sizes.empty()) {
  229. GELOGD("No need to allocate workspace.");
  230. return SUCCESS;
  231. }
  232. int64_t total_size = 0;
  233. std::vector<int64_t> ws_offsets;
  234. for (auto ws_size : workspace_sizes) {
  235. // alignment and padding should be done in OpParaCalculate
  236. GE_CHK_STATUS_RET_NOLOG(CheckInt64AddOverflow(total_size, ws_size));
  237. ws_offsets.emplace_back(total_size);
  238. total_size += ws_size;
  239. }
  240. GELOGD("Total workspace size is %ld", total_size);
  241. GE_CHECK_NOTNULL(stream_resource_);
  242. auto ws_base = stream_resource_->MallocMemory(kPurpose, static_cast<size_t>(total_size));
  243. if (ws_base == nullptr) {
  244. GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "Failed to allocate memory of size: %ld", total_size);
  245. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  246. }
  247. GELOGD("Done allocating workspace memory successfully.");
  248. for (auto ws_offset : ws_offsets) {
  249. workspaces_.emplace_back(ws_base + ws_offset);
  250. }
  251. return SUCCESS;
  252. }
  253. Status TbeOpTask::LaunchKernel(const vector<GeTensorDesc> &input_desc,
  254. const vector<DataBuffer> &input_buffers,
  255. vector<GeTensorDesc> &output_desc,
  256. vector<DataBuffer> &output_buffers,
  257. rtStream_t stream) {
  258. GE_CHK_STATUS_RET_NOLOG(UpdateRunInfo(input_desc, output_desc));
  259. GELOGD("[%s] Start to launch kernel", node_->GetName().c_str());
  260. std::vector<void *> args;
  261. for (auto &buffer : input_buffers) {
  262. args.emplace_back(buffer.data);
  263. }
  264. for (auto &buffer : output_buffers) {
  265. args.emplace_back(buffer.data);
  266. }
  267. for (auto &buffer : workspaces_) {
  268. args.emplace_back(buffer);
  269. }
  270. if (tiling_buffer_ != nullptr) {
  271. GELOGD("[%s] Start to copy tiling info. size = %zu", node_->GetName().c_str(), tiling_data_.size());
  272. GE_CHK_RT_RET(rtMemcpyAsync(tiling_buffer_, max_tiling_size_, tiling_data_.data(), tiling_data_.size(),
  273. RT_MEMCPY_HOST_TO_DEVICE_EX, stream));
  274. args.emplace_back(tiling_buffer_);
  275. }
  276. if (memcpy_s(args_.get(), arg_size_, args.data(), args.size() * sizeof(void *)) != EOK) {
  277. GELOGE(INTERNAL_ERROR, "[%s] Failed to update kernel args.", node_->GetName().c_str());
  278. return INTERNAL_ERROR;
  279. }
  280. GELOGD("[%s] Start to invoke rtKernelLaunch", node_->GetName().c_str());
  281. GE_CHK_RT_RET(rtKernelLaunch(stub_func_, block_dim_, args_.get(), arg_size_, nullptr, stream));
  282. GELOGD("[%s] Done invoking rtKernelLaunch successfully", node_->GetName().c_str());
  283. return SUCCESS;
  284. }
  285. void TbeOpTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
  286. arg_base = reinterpret_cast<uintptr_t *>(args_.get());
  287. arg_count = arg_size_ / sizeof(void *);
  288. if (tiling_buffer_ != nullptr) {
  289. --arg_count;
  290. }
  291. }
  292. AiCpuBaseTask::~AiCpuBaseTask() {
  293. if (ext_info_addr_dev_ != nullptr) {
  294. (void)rtFree(ext_info_addr_dev_);
  295. }
  296. }
  297. Status AiCpuBaseTask::SetExtInfoAndType(const std::string &kernel_ext_info, uint64_t kernel_id) {
  298. if (kernel_ext_info.empty()) {
  299. GELOGI("Kernel_ext_info is empty, no need copy to device.");
  300. return SUCCESS;
  301. }
  302. int32_t unknown_shape_type_val = 0;
  303. (void) AttrUtils::GetInt(op_desc_, ::ge::ATTR_NAME_UNKNOWN_SHAPE_TYPE, unknown_shape_type_val);
  304. GELOGD("Get unknown_type is %d.", unknown_shape_type_val);
  305. unknown_type_ = static_cast<UnknowShapeOpType>(unknown_shape_type_val);
  306. aicpu_ext_handle_.reset(new(std::nothrow) ::ge::hybrid::AicpuExtInfoHandler(op_desc_->GetName(),
  307. num_inputs_,
  308. num_outputs_,
  309. unknown_type_));
  310. GE_CHK_BOOL_RET_STATUS(aicpu_ext_handle_ != nullptr, FAILED, "Malloc aicpu_ext_handle mem failed!");
  311. Status ret = aicpu_ext_handle_->Parse(kernel_ext_info);
  312. if (ret != SUCCESS) {
  313. GELOGE(ret, "Parse kernel ext info failed, kernel_ext_info_size=%zu.", kernel_ext_info.size());
  314. return ret;
  315. }
  316. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateSessionInfo(ULLONG_MAX, kernel_id, false),
  317. "UpdateSessionInfo failed.");
  318. GE_CHK_RT_RET(rtMalloc(&ext_info_addr_dev_, aicpu_ext_handle_->GetExtInfoLen(), RT_MEMORY_HBM));
  319. GE_CHK_RT_RET(rtMemcpy(ext_info_addr_dev_, aicpu_ext_handle_->GetExtInfoLen(),
  320. aicpu_ext_handle_->GetExtInfo(), aicpu_ext_handle_->GetExtInfoLen(),
  321. RT_MEMCPY_HOST_TO_DEVICE));
  322. return SUCCESS;
  323. }
  324. Status AiCpuBaseTask::UpdateExtInfo(const std::vector<GeTensorDesc> &input_desc,
  325. std::vector<GeTensorDesc> &output_desc,
  326. rtStream_t stream) {
  327. GELOGI("Update ext info begin, unknown_type=%d.", unknown_type_);
  328. if (num_inputs_ == 0 && num_outputs_ == 0) {
  329. GELOGI("No input and output, no need update ext info.");
  330. return SUCCESS;
  331. }
  332. GE_CHECK_NOTNULL(aicpu_ext_handle_);
  333. for (size_t i = 0; i < num_inputs_; ++i) {
  334. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateInputShapeAndType(i, input_desc[i]),
  335. "Input[%zu] update input shape failed.", i);
  336. }
  337. if (unknown_type_ != DEPEND_COMPUTE) {
  338. for (size_t j = 0; j < num_outputs_; ++j) {
  339. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateOutputShapeAndType(j, output_desc[j]),
  340. "Output[%zu] UpdateOutputShapeAndType failed.", j);
  341. }
  342. }
  343. GE_CHK_RT_RET(rtMemcpyAsync(ext_info_addr_dev_,
  344. aicpu_ext_handle_->GetExtInfoLen(), // check size
  345. aicpu_ext_handle_->GetExtInfo(),
  346. aicpu_ext_handle_->GetExtInfoLen(),
  347. RT_MEMCPY_HOST_TO_DEVICE_EX,
  348. stream));
  349. GELOGI("Update ext info end.");
  350. return SUCCESS;
  351. }
  352. Status AiCpuBaseTask::UpdateOutputShape(vector<GeTensorDesc> &output_desc) {
  353. if (num_outputs_ == 0) {
  354. GELOGD("AiCpuBaseTask output_num is 0, no need update output shape.");
  355. return SUCCESS;
  356. }
  357. GELOGD("Start to update DEPEND_SHAPE_RANGE AiCpuBaseTask outputshape.");
  358. GE_CHK_RT_RET(rtMemcpy(aicpu_ext_handle_->GetExtInfo(),
  359. aicpu_ext_handle_->GetExtInfoLen(),
  360. ext_info_addr_dev_,
  361. aicpu_ext_handle_->GetExtInfoLen(),
  362. RT_MEMCPY_DEVICE_TO_HOST));
  363. for (size_t i = 0; i < num_outputs_; ++i) {
  364. GeShape shape;
  365. DataType data_type;
  366. aicpu_ext_handle_->GetOutputShapeAndType(i, shape, data_type);
  367. GE_CHK_STATUS_RET(UpdateShapeToOutputDesc(shape, output_desc[i]),
  368. "AiCpuCCTask Update [%zu]th output shape failed.", i);
  369. }
  370. GELOGD("Update DEPEND_SHAPE_RANGE AiCpuBaseTask outputshape finished.");
  371. return SUCCESS;
  372. }
  373. Status AiCpuBaseTask::UpdateShapeToOutputDesc(const GeShape &shape_new, GeTensorDesc &output_desc) {
  374. auto shape_old = output_desc.GetShape();
  375. output_desc.SetShape(shape_new);
  376. GELOGD("Update AiCpuBaseTask shape from %s to %s", shape_old.ToString().c_str(), shape_new.ToString().c_str());
  377. auto origin_shape_old = output_desc.GetOriginShape();
  378. auto origin_format = output_desc.GetOriginFormat();
  379. auto format = output_desc.GetFormat();
  380. if (origin_format == format) {
  381. output_desc.SetOriginShape(shape_new);
  382. return SUCCESS;
  383. }
  384. std::vector<int64_t> origin_dims_new;
  385. auto trans_ret = formats::TransShape(format, shape_new.GetDims(),
  386. output_desc.GetDataType(), origin_format, origin_dims_new);
  387. GE_CHK_STATUS_RET(trans_ret,
  388. "AiCpuTask originFormat[%d] is not same as format[%d], but TransShape failed, shape=%s.",
  389. origin_format, format, shape_new.ToString().c_str());
  390. auto origin_shape_new = GeShape(origin_dims_new);
  391. output_desc.SetOriginShape(origin_shape_new);
  392. GELOGD("AiCpuTask originFormat[%d] is not same as format[%d], need update from %s ro %s.",
  393. origin_format, format, origin_shape_old.ToString().c_str(), origin_shape_new.ToString().c_str());
  394. return SUCCESS;
  395. }
  396. AiCpuTask::~AiCpuTask() {
  397. FreeHbm(args_);
  398. FreeHbm(io_addr_);
  399. if (dynamic_flag_) {
  400. FreeHbm(workspace_addr_);
  401. }
  402. FreeHbm(copy_workspace_buf_);
  403. FreeHbm(copy_ioaddr_dev_);
  404. FreeHbm(copy_input_release_flag_dev_);
  405. FreeHbm(copy_input_data_size_dev_);
  406. FreeHbm(copy_input_src_dev_);
  407. FreeHbm(copy_input_dst_dev_);
  408. FreeHbm(copy_task_args_buf_);
  409. for (auto summary : output_summary_) {
  410. FreeHbm(summary);
  411. }
  412. for (auto out_shape : out_shape_hbm_) {
  413. FreeHbm(out_shape);
  414. }
  415. }
  416. Status AiCpuTask::LaunchKernel(rtStream_t stream) {
  417. GELOGD("Start to launch kernel. task = %s", this->op_type_.c_str());
  418. auto ret = rtMemcpyAsync(io_addr_,
  419. io_addr_size_,
  420. io_addr_host_.data(),
  421. io_addr_host_.size() * sizeof(void *),
  422. RT_MEMCPY_HOST_TO_DEVICE_EX,
  423. stream);
  424. if (ret != RT_ERROR_NONE) {
  425. GELOGE(RT_FAILED, "rtMemcpyAsync workspace data failed. ret = %d, task = %s", ret, this->op_type_.c_str());
  426. return RT_FAILED;
  427. }
  428. GELOGI("To invoke rtKernelLaunchEx. task = %s", this->op_type_.c_str());
  429. ret = rtKernelLaunchEx(args_, arg_size_, 0, stream);
  430. if (ret != RT_ERROR_NONE) {
  431. GELOGE(RT_FAILED, "Invoke rtKernelLaunch failed. ret = %d, task = %s", ret, this->op_type_.c_str());
  432. return RT_FAILED;
  433. }
  434. GELOGI("[TASK_INFO] %s/%s", std::to_string(kernel_id_).c_str(), op_type_.c_str());
  435. auto status = OpenDump(stream);
  436. if (status != SUCCESS) {
  437. GELOGE(status, "Open dump failed in aicpu single op %s", this->op_type_.c_str());
  438. return status;
  439. }
  440. GELOGD("Done launch kernel successfully. task = %s", this->op_type_.c_str());
  441. return SUCCESS;
  442. }
  443. Status AiCpuTask::PrepareCopyInputs(vector<DataBuffer> &outputs) {
  444. std::vector<uint64_t> copy_input_release_flag;
  445. std::vector<uint64_t> copy_input_data_size;
  446. std::vector<uint64_t> copy_input_src;
  447. std::vector<uint64_t> copy_input_dst;
  448. for (size_t i = 0; i < num_outputs_; ++i) {
  449. const auto &summary = output_summary_host_[i];
  450. GELOGI("Node out[%zu] summary, shape data=0x%lx, shape data size=%lu, raw data=0x%lx, raw data size=%lu.",
  451. i, summary.shape_data_ptr, summary.shape_data_size,
  452. summary.raw_data_ptr, summary.raw_data_size);
  453. auto output = outputs[i];
  454. copy_input_release_flag.emplace_back(kReleaseFlag);
  455. if (summary.raw_data_size > 0) {
  456. copy_input_data_size.emplace_back(output.length);
  457. } else {
  458. copy_input_data_size.emplace_back(summary.raw_data_size);
  459. }
  460. copy_input_src.emplace_back(summary.raw_data_ptr);
  461. copy_input_dst.emplace_back(reinterpret_cast<uintptr_t>(output.data));
  462. const auto &shape_buffer = out_shape_hbm_[i];
  463. copy_input_release_flag.emplace_back(kReleaseFlag);
  464. copy_input_data_size.emplace_back(summary.shape_data_size);
  465. copy_input_src.emplace_back(summary.shape_data_ptr);
  466. copy_input_dst.emplace_back(reinterpret_cast<uintptr_t>(shape_buffer));
  467. }
  468. const size_t copy_input_buf_len = num_outputs_ * kCopyNum * sizeof(uint64_t);
  469. GE_CHK_RT_RET(rtMemcpy(copy_input_release_flag_dev_, copy_input_buf_len,
  470. copy_input_release_flag.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
  471. GE_CHK_RT_RET(rtMemcpy(copy_input_data_size_dev_, copy_input_buf_len,
  472. copy_input_data_size.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
  473. GE_CHK_RT_RET(rtMemcpy(copy_input_src_dev_, copy_input_buf_len,
  474. copy_input_src.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
  475. GE_CHK_RT_RET(rtMemcpy(copy_input_dst_dev_, copy_input_buf_len,
  476. copy_input_dst.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
  477. return SUCCESS;
  478. }
  479. Status AiCpuTask::ReadResultSummaryAndPrepareMemory() {
  480. for (size_t i = 0; i < num_outputs_; ++i) {
  481. auto &result_summary = output_summary_host_[i];
  482. GE_CHK_RT_RET(rtMemcpy(&result_summary, sizeof(aicpu::FWKAdapter::ResultSummary),
  483. output_summary_[i], sizeof(aicpu::FWKAdapter::ResultSummary),
  484. RT_MEMCPY_DEVICE_TO_HOST));
  485. auto shape_data_size = result_summary.shape_data_size;
  486. void *shape_buffer = nullptr;
  487. if (shape_data_size > 0) {
  488. GE_CHK_RT_RET(rtMalloc(&shape_buffer, shape_data_size, RT_MEMORY_HBM));
  489. }
  490. out_shape_hbm_.emplace_back(shape_buffer);
  491. }
  492. return SUCCESS;
  493. }
  494. Status AiCpuTask::CopyDataToHbm(vector<DataBuffer> &outputs,
  495. rtStream_t stream) {
  496. GE_CHK_STATUS_RET_NOLOG(PrepareCopyInputs(outputs));
  497. GE_CHK_RT_RET(rtKernelLaunchEx(copy_task_args_buf_, sizeof(STR_FWK_OP_KERNEL),
  498. RT_KERNEL_DEFAULT, stream));
  499. GE_CHK_RT_RET(rtStreamSynchronize(stream));
  500. return SUCCESS;
  501. }
  502. Status AiCpuTask::UpdateShapeByHbmBuffer(vector<GeTensorDesc> &output_desc) {
  503. for (size_t i = 0; i < num_outputs_; ++i) {
  504. const auto &result_summary = output_summary_host_[i];
  505. std::vector<int64_t> shape_dims;
  506. if (result_summary.shape_data_size > 0) {
  507. const auto &shape_hbm = out_shape_hbm_[i];
  508. uint32_t dim_num = result_summary.shape_data_size / sizeof(int64_t);
  509. std::unique_ptr<int64_t[]> shape_addr(new(std::nothrow) int64_t[dim_num]());
  510. GE_CHECK_NOTNULL(shape_addr);
  511. GE_CHK_RT_RET(rtMemcpy(shape_addr.get(), result_summary.shape_data_size,
  512. shape_hbm, result_summary.shape_data_size, RT_MEMCPY_DEVICE_TO_HOST));
  513. for (uint32_t dim_idx = 0; dim_idx < dim_num; ++dim_idx) {
  514. shape_dims.emplace_back(shape_addr[dim_idx]);
  515. GELOGD("Node [%zu]th output dim[%u]=%ld.", i, dim_idx, shape_addr[dim_idx]);
  516. }
  517. }
  518. GE_CHK_STATUS_RET(UpdateShapeToOutputDesc(GeShape(shape_dims), output_desc[i]),
  519. "AiCpuTask update [%zu]th output shape failed.", i);
  520. }
  521. return SUCCESS;
  522. }
  523. Status AiCpuTask::UpdateShapeAndDataByResultSummary(vector<GeTensorDesc> &output_desc,
  524. vector<DataBuffer> &outputs,
  525. rtStream_t stream) {
  526. if (num_outputs_ == 0) {
  527. GELOGI("Output num is 0, there is no need to update the output and size.");
  528. return SUCCESS;
  529. }
  530. GELOGI("Update shape and data by result summary begin.");
  531. for (auto out_shape : out_shape_hbm_) {
  532. FreeHbm(out_shape);
  533. }
  534. out_shape_hbm_.clear();
  535. GE_CHK_STATUS_RET(ReadResultSummaryAndPrepareMemory(),
  536. "Read ResultSummary and update output shape failed.");
  537. GE_CHK_STATUS_RET(CopyDataToHbm(outputs, stream),
  538. "Copy data to output failed.");
  539. GE_CHK_STATUS_RET(UpdateShapeByHbmBuffer(output_desc),
  540. "Update shape by hbm buffer failed.");
  541. for (auto out_shape : out_shape_hbm_) {
  542. FreeHbm(out_shape);
  543. }
  544. out_shape_hbm_.clear();
  545. GELOGI("Update shape and data by result summary end.");
  546. return SUCCESS;
  547. }
  548. Status AiCpuTask::SetIO(const vector<void *> &inputs, vector<void *> &outputs) {
  549. vector<uint64_t> io_addrs;
  550. io_addrs.reserve(num_inputs_ + num_outputs_);
  551. for (size_t i = 0; i < num_inputs_; ++i) {
  552. GE_CHECK_NOTNULL(inputs[i]);
  553. GELOGD("AiCpuTask input[%zu] addr = %p", i, inputs[i]);
  554. io_addrs.emplace_back(reinterpret_cast<uintptr_t>(inputs[i]));
  555. }
  556. if (unknown_type_ != DEPEND_COMPUTE) {
  557. for (size_t i = 0; i < num_outputs_; ++i) {
  558. GE_CHECK_NOTNULL(outputs[i]);
  559. GELOGD("AiCpuTask output[%zu] addr = %p", i, outputs[i]);
  560. io_addrs.emplace_back(reinterpret_cast<uintptr_t>(outputs[i]));
  561. }
  562. } else {
  563. for (size_t i = 0; i < num_outputs_; ++i) {
  564. void *summary_addr = output_summary_[i];
  565. io_addrs.emplace_back(reinterpret_cast<uintptr_t>(summary_addr));
  566. }
  567. }
  568. if (!io_addrs.empty()) {
  569. auto *dst_io_addr = const_cast<uintptr_t *>(reinterpret_cast<const uintptr_t *>(io_addr_));
  570. GE_CHK_RT_RET(rtMemcpy(dst_io_addr,
  571. sizeof(uint64_t) * io_addrs.size(),
  572. &io_addrs[0],
  573. sizeof(uint64_t) * io_addrs.size(),
  574. RT_MEMCPY_HOST_TO_DEVICE));
  575. GE_CHECK_NOTNULL(dst_io_addr);
  576. };
  577. return SUCCESS;
  578. }
  579. Status AiCpuTask::InitForSummaryAndCopy() {
  580. if (unknown_type_ != DEPEND_COMPUTE || num_outputs_ == 0) {
  581. GELOGI("Unknown_type is %d, output num is %d.", unknown_type_, num_outputs_);
  582. return SUCCESS;
  583. }
  584. output_summary_.resize(num_outputs_);
  585. constexpr auto result_summary_size = sizeof(aicpu::FWKAdapter::ResultSummary);
  586. for (size_t i = 0; i < num_outputs_; ++i) {
  587. GE_CHK_RT_RET(rtMalloc(&output_summary_[i], result_summary_size, RT_MEMORY_HBM));
  588. }
  589. output_summary_host_.resize(num_outputs_);
  590. const size_t copy_input_buf_len = num_outputs_ * kCopyNum * sizeof(uint64_t);
  591. GE_CHK_RT_RET(rtMalloc(&copy_input_release_flag_dev_, copy_input_buf_len, RT_MEMORY_HBM));
  592. GE_CHK_RT_RET(rtMalloc(&copy_input_data_size_dev_, copy_input_buf_len, RT_MEMORY_HBM));
  593. GE_CHK_RT_RET(rtMalloc(&copy_input_src_dev_, copy_input_buf_len, RT_MEMORY_HBM));
  594. GE_CHK_RT_RET(rtMalloc(&copy_input_dst_dev_, copy_input_buf_len, RT_MEMORY_HBM));
  595. GE_CHK_RT_RET(rtMalloc(&copy_task_args_buf_, sizeof(STR_FWK_OP_KERNEL), RT_MEMORY_HBM));
  596. std::vector<uint64_t> copy_io_addr;
  597. copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_release_flag_dev_));
  598. copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_data_size_dev_));
  599. copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_src_dev_));
  600. copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_dst_dev_));
  601. const auto copy_io_addr_size = sizeof(uint64_t) * copy_io_addr.size();
  602. GE_CHK_RT_RET(rtMalloc(&copy_ioaddr_dev_, copy_io_addr_size, RT_MEMORY_HBM));
  603. GE_CHK_RT_RET(rtMemcpy(copy_ioaddr_dev_, copy_io_addr_size,
  604. copy_io_addr.data(), copy_io_addr_size, RT_MEMCPY_HOST_TO_DEVICE));
  605. return SUCCESS;
  606. }
  607. Status AiCpuTask::SetMemCopyTask(const domi::KernelExDef &kernel_def) {
  608. if (kernel_def.args_size() > sizeof(STR_FWK_OP_KERNEL)) {
  609. GELOGE(PARAM_INVALID, "sizeof STR_FWK_OP_KERNEL is: %lu, but args_size is: %d",
  610. sizeof(STR_FWK_OP_KERNEL), kernel_def.args_size());
  611. return PARAM_INVALID;
  612. }
  613. GE_CHK_RT_RET(rtMalloc(&copy_workspace_buf_, kernel_def.task_info_size(), RT_MEMORY_HBM));
  614. GE_CHK_RT_RET(rtMemcpy(copy_workspace_buf_, kernel_def.task_info_size(),
  615. kernel_def.task_info().data(), kernel_def.task_info_size(), RT_MEMCPY_HOST_TO_DEVICE));
  616. STR_FWK_OP_KERNEL aicpu_task = {0};
  617. auto sec_ret = memcpy_s(&aicpu_task, sizeof(STR_FWK_OP_KERNEL),
  618. kernel_def.args().data(), kernel_def.args().size());
  619. if (sec_ret != EOK) {
  620. GELOGE(FAILED, "memcpy failed, ret: %d", sec_ret);
  621. return FAILED;
  622. }
  623. aicpu_task.fwkKernelBase.fwk_kernel.inputOutputAddr = reinterpret_cast<uintptr_t>(copy_ioaddr_dev_);
  624. aicpu_task.fwkKernelBase.fwk_kernel.workspaceBaseAddr = reinterpret_cast<uintptr_t>(copy_workspace_buf_);
  625. aicpu_task.fwkKernelBase.fwk_kernel.extInfoAddr = 0;
  626. aicpu_task.fwkKernelBase.fwk_kernel.extInfoLen = 0;
  627. GE_CHK_RT_RET(rtMemcpy(copy_task_args_buf_, sizeof(STR_FWK_OP_KERNEL),
  628. &aicpu_task, sizeof(STR_FWK_OP_KERNEL), RT_MEMCPY_HOST_TO_DEVICE));
  629. return SUCCESS;
  630. }
  631. Status AiCpuTask::LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
  632. const std::vector<DataBuffer> &input_buffers,
  633. std::vector<GeTensorDesc> &output_desc,
  634. std::vector<DataBuffer> &output_buffers,
  635. rtStream_t stream) {
  636. GE_CHK_STATUS_RET_NOLOG(UpdateExtInfo(input_desc, output_desc, stream));
  637. std::vector<void *> inputs;
  638. std::vector<void *> outputs;
  639. for (auto &buffer : input_buffers) {
  640. inputs.emplace_back(buffer.data);
  641. }
  642. for (auto &buffer : output_buffers) {
  643. outputs.emplace_back(buffer.data);
  644. }
  645. GE_CHK_STATUS_RET_NOLOG(SetIO(inputs, outputs));
  646. GE_CHK_STATUS_RET_NOLOG(LaunchKernel(stream));
  647. if (unknown_type_ == DEPEND_SHAPE_RANGE) {
  648. GE_CHK_RT_RET(rtStreamSynchronize(stream));
  649. GE_CHK_STATUS_RET_NOLOG(UpdateOutputShape(output_desc));
  650. } else if (unknown_type_ == DEPEND_COMPUTE) {
  651. GE_CHK_RT_RET(rtStreamSynchronize(stream));
  652. GE_CHK_STATUS_RET_NOLOG(UpdateShapeAndDataByResultSummary(output_desc, output_buffers, stream));
  653. }
  654. return SUCCESS;
  655. }
  656. Status AiCpuTask::UpdateArgTable(const SingleOpModelParam &param) {
  657. auto addresses = BuildTaskUtils::GetAddresses(op_desc_, param, false);
  658. io_addr_host_ = BuildTaskUtils::JoinAddresses(addresses);
  659. return SUCCESS;
  660. }
  661. void AiCpuTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
  662. arg_base = reinterpret_cast<uintptr_t *>(io_addr_host_.data());
  663. arg_count = io_addr_host_.size();
  664. }
  665. void AiCpuCCTask::SetKernelArgs(std::unique_ptr<uint8_t[]> args, size_t arg_size) {
  666. args_ = std::move(args);
  667. arg_size_ = arg_size;
  668. // The blockdim value is defult "1" for rtCpuKernelLaunch
  669. block_dim_ = 1;
  670. }
  671. void AiCpuCCTask::SetSoName(const std::string &so_name) { so_name_ = so_name; }
  672. void AiCpuCCTask::SetkernelName(const std::string &kernel_Name) { kernel_name_ = kernel_Name; }
  673. void AiCpuCCTask::SetIoAddr(uintptr_t *io_addr) { io_addr_ = io_addr; }
  674. const void *AiCpuCCTask::GetArgs() const { return args_.get(); }
  675. size_t AiCpuCCTask::GetArgSize() const { return arg_size_; }
  676. AiCpuCCTask::~AiCpuCCTask() {
  677. }
  678. Status AiCpuCCTask::LaunchKernel(rtStream_t stream) {
  679. GELOGI("To invoke rtCpuKernelLaunch. block_dim = %u, so_name is %s, kernel_name is %s", block_dim_, so_name_.data(),
  680. kernel_name_.data());
  681. // sm_desc is nullptr, because l2 buffer does not support
  682. auto *sm_desc = reinterpret_cast<rtSmDesc_t *>(sm_desc_);
  683. auto ret = rtCpuKernelLaunchWithFlag(static_cast<const void *>(so_name_.data()),
  684. static_cast<const void *>(kernel_name_.data()),
  685. block_dim_, args_.get(), static_cast<uint32_t>(arg_size_),
  686. sm_desc, stream, dump_flag_);
  687. if (ret != RT_ERROR_NONE) {
  688. GELOGE(ret, "Invoke rtCpuKernelLaunch failed. ret = %d", ret);
  689. return ret;
  690. }
  691. GELOGD("Invoke rtCpuKernelLaunch succeeded");
  692. auto status = OpenDump(stream);
  693. if (status != SUCCESS) {
  694. GELOGE(status, "Open dump failed in the aicpucc single op %s", this->kernel_name_.c_str());
  695. return status;
  696. }
  697. return SUCCESS;
  698. }
  699. Status AiCpuCCTask::LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
  700. const std::vector<DataBuffer> &input_buffers,
  701. std::vector<GeTensorDesc> &output_desc,
  702. std::vector<DataBuffer> &output_buffers,
  703. rtStream_t stream) {
  704. GE_CHK_BOOL_RET_STATUS(unknown_type_ != DEPEND_COMPUTE, FAILED,
  705. "AiCpuCCTask unknown type[%d] is depend compute, it's not supported now.",
  706. unknown_type_);
  707. GE_CHK_STATUS_RET_NOLOG(UpdateExtInfo(input_desc, output_desc, stream));
  708. size_t arg_index = 0;
  709. auto *task_io_addr = reinterpret_cast<uintptr_t *>(io_addr_);
  710. GE_CHECK_NOTNULL(task_io_addr);
  711. for (auto &input : input_buffers) {
  712. task_io_addr[arg_index++] = reinterpret_cast<uintptr_t>(input.data);
  713. }
  714. for (auto &output : output_buffers) {
  715. task_io_addr[arg_index++] = reinterpret_cast<uintptr_t>(output.data);
  716. }
  717. GE_CHK_STATUS_RET_NOLOG(LaunchKernel(stream));
  718. if (unknown_type_ == DEPEND_SHAPE_RANGE) {
  719. GE_CHK_RT_RET(rtStreamSynchronize(stream));
  720. GE_CHK_STATUS_RET_NOLOG(UpdateOutputShape(output_desc));
  721. }
  722. return SUCCESS;
  723. }
  724. void AiCpuCCTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
  725. arg_base = io_addr_;
  726. arg_count = io_addr_num_;
  727. }
  728. } // 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