1 //===----RTLs/cuda/src/rtl.cpp - Target RTLs Implementation ------- C++ -*-===// 2 // 3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. 4 // See https://llvm.org/LICENSE.txt for license information. 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 6 // 7 //===----------------------------------------------------------------------===// 8 // 9 // RTL for CUDA machine 10 // 11 //===----------------------------------------------------------------------===// 12 13 #include <cassert> 14 #include <cstddef> 15 #include <cuda.h> 16 #include <list> 17 #include <memory> 18 #include <mutex> 19 #include <string> 20 #include <vector> 21 22 #include "Debug.h" 23 #include "omptargetplugin.h" 24 25 #define TARGET_NAME CUDA 26 #define DEBUG_PREFIX "Target " GETNAME(TARGET_NAME) " RTL" 27 28 #include "MemoryManager.h" 29 30 // Utility for retrieving and printing CUDA error string. 31 #ifdef OMPTARGET_DEBUG 32 #define CUDA_ERR_STRING(err) \ 33 do { \ 34 if (getDebugLevel() > 0) { \ 35 const char *errStr = nullptr; \ 36 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 37 if (errStr_status == CUDA_ERROR_INVALID_VALUE) \ 38 REPORT("Unrecognized CUDA error code: %d\n", err); \ 39 else if (errStr_status == CUDA_SUCCESS) \ 40 REPORT("CUDA error is: %s\n", errStr); \ 41 else { \ 42 REPORT("Unresolved CUDA error code: %d\n", err); \ 43 REPORT("Unsuccessful cuGetErrorString return status: %d\n", \ 44 errStr_status); \ 45 } \ 46 } else { \ 47 const char *errStr = nullptr; \ 48 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 49 if (errStr_status == CUDA_SUCCESS) \ 50 REPORT("%s \n", errStr); \ 51 } \ 52 } while (false) 53 #else // OMPTARGET_DEBUG 54 #define CUDA_ERR_STRING(err) \ 55 do { \ 56 const char *errStr = nullptr; \ 57 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 58 if (errStr_status == CUDA_SUCCESS) \ 59 REPORT("%s \n", errStr); \ 60 } while (false) 61 #endif // OMPTARGET_DEBUG 62 63 #include "elf_common.h" 64 65 /// Keep entries table per device. 66 struct FuncOrGblEntryTy { 67 __tgt_target_table Table; 68 std::vector<__tgt_offload_entry> Entries; 69 }; 70 71 enum ExecutionModeType { 72 SPMD, // constructors, destructors, 73 // combined constructs (`teams distribute parallel for [simd]`) 74 GENERIC, // everything else 75 NONE 76 }; 77 78 /// Use a single entity to encode a kernel and a set of flags. 79 struct KernelTy { 80 CUfunction Func; 81 82 // execution mode of kernel 83 // 0 - SPMD mode (without master warp) 84 // 1 - Generic mode (with master warp) 85 int8_t ExecutionMode; 86 87 /// Maximal number of threads per block for this kernel. 88 int MaxThreadsPerBlock = 0; 89 90 KernelTy(CUfunction _Func, int8_t _ExecutionMode) 91 : Func(_Func), ExecutionMode(_ExecutionMode) {} 92 }; 93 94 /// Device environment data 95 /// Manually sync with the deviceRTL side for now, move to a dedicated header 96 /// file later. 97 struct omptarget_device_environmentTy { 98 int32_t debug_level; 99 }; 100 101 namespace { 102 bool checkResult(CUresult Err, const char *ErrMsg) { 103 if (Err == CUDA_SUCCESS) 104 return true; 105 106 REPORT("%s", ErrMsg); 107 CUDA_ERR_STRING(Err); 108 return false; 109 } 110 111 int memcpyDtoD(const void *SrcPtr, void *DstPtr, int64_t Size, 112 CUstream Stream) { 113 CUresult Err = cuMemcpyDtoDAsync_v2((CUdeviceptr)DstPtr, (CUdeviceptr)SrcPtr, 114 Size, Stream); 115 116 if (Err != CUDA_SUCCESS) { 117 REPORT("Error when copying data from device to device. Pointers: src " 118 "= " DPxMOD ", dst = " DPxMOD ", size = %" PRId64 "\n", 119 DPxPTR(SrcPtr), DPxPTR(DstPtr), Size); 120 CUDA_ERR_STRING(Err); 121 return OFFLOAD_FAIL; 122 } 123 124 return OFFLOAD_SUCCESS; 125 } 126 127 // Structure contains per-device data 128 struct DeviceDataTy { 129 /// List that contains all the kernels. 130 std::list<KernelTy> KernelsList; 131 132 std::list<FuncOrGblEntryTy> FuncGblEntries; 133 134 CUcontext Context = nullptr; 135 // Device properties 136 int ThreadsPerBlock = 0; 137 int BlocksPerGrid = 0; 138 int WarpSize = 0; 139 // OpenMP properties 140 int NumTeams = 0; 141 int NumThreads = 0; 142 }; 143 144 class StreamManagerTy { 145 int NumberOfDevices; 146 // The initial size of stream pool 147 int EnvNumInitialStreams; 148 // Per-device stream mutex 149 std::vector<std::unique_ptr<std::mutex>> StreamMtx; 150 // Per-device stream Id indicates the next available stream in the pool 151 std::vector<int> NextStreamId; 152 // Per-device stream pool 153 std::vector<std::vector<CUstream>> StreamPool; 154 // Reference to per-device data 155 std::vector<DeviceDataTy> &DeviceData; 156 157 // If there is no CUstream left in the pool, we will resize the pool to 158 // allocate more CUstream. This function should be called with device mutex, 159 // and we do not resize to smaller one. 160 void resizeStreamPool(const int DeviceId, const size_t NewSize) { 161 std::vector<CUstream> &Pool = StreamPool[DeviceId]; 162 const size_t CurrentSize = Pool.size(); 163 assert(NewSize > CurrentSize && "new size is not larger than current size"); 164 165 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 166 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) { 167 // We will return if cannot switch to the right context in case of 168 // creating bunch of streams that are not corresponding to the right 169 // device. The offloading will fail later because selected CUstream is 170 // nullptr. 171 return; 172 } 173 174 Pool.resize(NewSize, nullptr); 175 176 for (size_t I = CurrentSize; I < NewSize; ++I) { 177 checkResult(cuStreamCreate(&Pool[I], CU_STREAM_NON_BLOCKING), 178 "Error returned from cuStreamCreate\n"); 179 } 180 } 181 182 public: 183 StreamManagerTy(const int NumberOfDevices, 184 std::vector<DeviceDataTy> &DeviceData) 185 : NumberOfDevices(NumberOfDevices), EnvNumInitialStreams(32), 186 DeviceData(DeviceData) { 187 StreamPool.resize(NumberOfDevices); 188 NextStreamId.resize(NumberOfDevices); 189 StreamMtx.resize(NumberOfDevices); 190 191 if (const char *EnvStr = getenv("LIBOMPTARGET_NUM_INITIAL_STREAMS")) 192 EnvNumInitialStreams = std::stoi(EnvStr); 193 194 // Initialize the next stream id 195 std::fill(NextStreamId.begin(), NextStreamId.end(), 0); 196 197 // Initialize stream mutex 198 for (std::unique_ptr<std::mutex> &Ptr : StreamMtx) 199 Ptr = std::make_unique<std::mutex>(); 200 } 201 202 ~StreamManagerTy() { 203 // Destroy streams 204 for (int I = 0; I < NumberOfDevices; ++I) { 205 checkResult(cuCtxSetCurrent(DeviceData[I].Context), 206 "Error returned from cuCtxSetCurrent\n"); 207 208 for (CUstream &S : StreamPool[I]) { 209 if (S) 210 checkResult(cuStreamDestroy_v2(S), 211 "Error returned from cuStreamDestroy_v2\n"); 212 } 213 } 214 } 215 216 // Get a CUstream from pool. Per-device next stream id always points to the 217 // next available CUstream. That means, CUstreams [0, id-1] have been 218 // assigned, and [id,] are still available. If there is no CUstream left, we 219 // will ask more CUstreams from CUDA RT. Each time a CUstream is assigned, 220 // the id will increase one. 221 // xxxxxs+++++++++ 222 // ^ 223 // id 224 // After assignment, the pool becomes the following and s is assigned. 225 // xxxxxs+++++++++ 226 // ^ 227 // id 228 CUstream getStream(const int DeviceId) { 229 const std::lock_guard<std::mutex> Lock(*StreamMtx[DeviceId]); 230 int &Id = NextStreamId[DeviceId]; 231 // No CUstream left in the pool, we need to request from CUDA RT 232 if (Id == StreamPool[DeviceId].size()) { 233 // By default we double the stream pool every time 234 resizeStreamPool(DeviceId, Id * 2); 235 } 236 return StreamPool[DeviceId][Id++]; 237 } 238 239 // Return a CUstream back to pool. As mentioned above, per-device next 240 // stream is always points to the next available CUstream, so when we return 241 // a CUstream, we need to first decrease the id, and then copy the CUstream 242 // back. 243 // It is worth noting that, the order of streams return might be different 244 // from that they're assigned, that saying, at some point, there might be 245 // two identical CUstreams. 246 // xxax+a+++++ 247 // ^ 248 // id 249 // However, it doesn't matter, because they're always on the two sides of 250 // id. The left one will in the end be overwritten by another CUstream. 251 // Therefore, after several execution, the order of pool might be different 252 // from its initial state. 253 void returnStream(const int DeviceId, CUstream Stream) { 254 const std::lock_guard<std::mutex> Lock(*StreamMtx[DeviceId]); 255 int &Id = NextStreamId[DeviceId]; 256 assert(Id > 0 && "Wrong stream ID"); 257 StreamPool[DeviceId][--Id] = Stream; 258 } 259 260 bool initializeDeviceStreamPool(const int DeviceId) { 261 assert(StreamPool[DeviceId].empty() && "stream pool has been initialized"); 262 263 resizeStreamPool(DeviceId, EnvNumInitialStreams); 264 265 // Check the size of stream pool 266 if (StreamPool[DeviceId].size() != EnvNumInitialStreams) 267 return false; 268 269 // Check whether each stream is valid 270 for (CUstream &S : StreamPool[DeviceId]) 271 if (!S) 272 return false; 273 274 return true; 275 } 276 }; 277 278 class DeviceRTLTy { 279 int NumberOfDevices; 280 // OpenMP environment properties 281 int EnvNumTeams; 282 int EnvTeamLimit; 283 // OpenMP requires flags 284 int64_t RequiresFlags; 285 286 static constexpr const int HardTeamLimit = 1U << 16U; // 64k 287 static constexpr const int HardThreadLimit = 1024; 288 static constexpr const int DefaultNumTeams = 128; 289 static constexpr const int DefaultNumThreads = 128; 290 291 std::unique_ptr<StreamManagerTy> StreamManager; 292 std::vector<DeviceDataTy> DeviceData; 293 std::vector<CUmodule> Modules; 294 295 /// A class responsible for interacting with device native runtime library to 296 /// allocate and free memory. 297 class CUDADeviceAllocatorTy : public DeviceAllocatorTy { 298 const int DeviceId; 299 const std::vector<DeviceDataTy> &DeviceData; 300 301 public: 302 CUDADeviceAllocatorTy(int DeviceId, std::vector<DeviceDataTy> &DeviceData) 303 : DeviceId(DeviceId), DeviceData(DeviceData) {} 304 305 void *allocate(size_t Size, void *) override { 306 if (Size == 0) 307 return nullptr; 308 309 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 310 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 311 return nullptr; 312 313 CUdeviceptr DevicePtr; 314 Err = cuMemAlloc_v2(&DevicePtr, Size); 315 if (!checkResult(Err, "Error returned from cuMemAlloc_v2\n")) 316 return nullptr; 317 318 return (void *)DevicePtr; 319 } 320 321 int free(void *TgtPtr) override { 322 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 323 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 324 return OFFLOAD_FAIL; 325 326 Err = cuMemFree_v2((CUdeviceptr)TgtPtr); 327 if (!checkResult(Err, "Error returned from cuMemFree_v2\n")) 328 return OFFLOAD_FAIL; 329 330 return OFFLOAD_SUCCESS; 331 } 332 }; 333 334 /// A vector of device allocators 335 std::vector<CUDADeviceAllocatorTy> DeviceAllocators; 336 337 /// A vector of memory managers. Since the memory manager is non-copyable and 338 // non-removable, we wrap them into std::unique_ptr. 339 std::vector<std::unique_ptr<MemoryManagerTy>> MemoryManagers; 340 341 /// Whether use memory manager 342 bool UseMemoryManager = true; 343 344 // Record entry point associated with device 345 void addOffloadEntry(const int DeviceId, const __tgt_offload_entry entry) { 346 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 347 E.Entries.push_back(entry); 348 } 349 350 // Return a pointer to the entry associated with the pointer 351 const __tgt_offload_entry *getOffloadEntry(const int DeviceId, 352 const void *Addr) const { 353 for (const __tgt_offload_entry &Itr : 354 DeviceData[DeviceId].FuncGblEntries.back().Entries) 355 if (Itr.addr == Addr) 356 return &Itr; 357 358 return nullptr; 359 } 360 361 // Return the pointer to the target entries table 362 __tgt_target_table *getOffloadEntriesTable(const int DeviceId) { 363 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 364 365 if (E.Entries.empty()) 366 return nullptr; 367 368 // Update table info according to the entries and return the pointer 369 E.Table.EntriesBegin = E.Entries.data(); 370 E.Table.EntriesEnd = E.Entries.data() + E.Entries.size(); 371 372 return &E.Table; 373 } 374 375 // Clear entries table for a device 376 void clearOffloadEntriesTable(const int DeviceId) { 377 DeviceData[DeviceId].FuncGblEntries.emplace_back(); 378 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 379 E.Entries.clear(); 380 E.Table.EntriesBegin = E.Table.EntriesEnd = nullptr; 381 } 382 383 CUstream getStream(const int DeviceId, __tgt_async_info *AsyncInfoPtr) const { 384 assert(AsyncInfoPtr && "AsyncInfoPtr is nullptr"); 385 386 if (!AsyncInfoPtr->Queue) 387 AsyncInfoPtr->Queue = StreamManager->getStream(DeviceId); 388 389 return reinterpret_cast<CUstream>(AsyncInfoPtr->Queue); 390 } 391 392 public: 393 // This class should not be copied 394 DeviceRTLTy(const DeviceRTLTy &) = delete; 395 DeviceRTLTy(DeviceRTLTy &&) = delete; 396 397 DeviceRTLTy() 398 : NumberOfDevices(0), EnvNumTeams(-1), EnvTeamLimit(-1), 399 RequiresFlags(OMP_REQ_UNDEFINED) { 400 401 DP("Start initializing CUDA\n"); 402 403 CUresult Err = cuInit(0); 404 if (!checkResult(Err, "Error returned from cuInit\n")) { 405 return; 406 } 407 408 Err = cuDeviceGetCount(&NumberOfDevices); 409 if (!checkResult(Err, "Error returned from cuDeviceGetCount\n")) 410 return; 411 412 if (NumberOfDevices == 0) { 413 DP("There are no devices supporting CUDA.\n"); 414 return; 415 } 416 417 DeviceData.resize(NumberOfDevices); 418 419 // Get environment variables regarding teams 420 if (const char *EnvStr = getenv("OMP_TEAM_LIMIT")) { 421 // OMP_TEAM_LIMIT has been set 422 EnvTeamLimit = std::stoi(EnvStr); 423 DP("Parsed OMP_TEAM_LIMIT=%d\n", EnvTeamLimit); 424 } 425 if (const char *EnvStr = getenv("OMP_NUM_TEAMS")) { 426 // OMP_NUM_TEAMS has been set 427 EnvNumTeams = std::stoi(EnvStr); 428 DP("Parsed OMP_NUM_TEAMS=%d\n", EnvNumTeams); 429 } 430 431 StreamManager = 432 std::make_unique<StreamManagerTy>(NumberOfDevices, DeviceData); 433 434 for (int I = 0; I < NumberOfDevices; ++I) 435 DeviceAllocators.emplace_back(I, DeviceData); 436 437 // Get the size threshold from environment variable 438 std::pair<size_t, bool> Res = MemoryManagerTy::getSizeThresholdFromEnv(); 439 UseMemoryManager = Res.second; 440 size_t MemoryManagerThreshold = Res.first; 441 442 if (UseMemoryManager) 443 for (int I = 0; I < NumberOfDevices; ++I) 444 MemoryManagers.emplace_back(std::make_unique<MemoryManagerTy>( 445 DeviceAllocators[I], MemoryManagerThreshold)); 446 } 447 448 ~DeviceRTLTy() { 449 // We first destruct memory managers in case that its dependent data are 450 // destroyed before it. 451 for (auto &M : MemoryManagers) 452 M.release(); 453 454 StreamManager = nullptr; 455 456 for (CUmodule &M : Modules) 457 // Close module 458 if (M) 459 checkResult(cuModuleUnload(M), "Error returned from cuModuleUnload\n"); 460 461 for (DeviceDataTy &D : DeviceData) { 462 // Destroy context 463 if (D.Context) { 464 checkResult(cuCtxSetCurrent(D.Context), 465 "Error returned from cuCtxSetCurrent\n"); 466 CUdevice Device; 467 checkResult(cuCtxGetDevice(&Device), 468 "Error returned from cuCtxGetDevice\n"); 469 checkResult(cuDevicePrimaryCtxRelease_v2(Device), 470 "Error returned from cuDevicePrimaryCtxRelease_v2\n"); 471 } 472 } 473 } 474 475 // Check whether a given DeviceId is valid 476 bool isValidDeviceId(const int DeviceId) const { 477 return DeviceId >= 0 && DeviceId < NumberOfDevices; 478 } 479 480 int getNumOfDevices() const { return NumberOfDevices; } 481 482 void setRequiresFlag(const int64_t Flags) { this->RequiresFlags = Flags; } 483 484 int initDevice(const int DeviceId) { 485 CUdevice Device; 486 487 DP("Getting device %d\n", DeviceId); 488 CUresult Err = cuDeviceGet(&Device, DeviceId); 489 if (!checkResult(Err, "Error returned from cuDeviceGet\n")) 490 return OFFLOAD_FAIL; 491 492 // Query the current flags of the primary context and set its flags if 493 // it is inactive 494 unsigned int FormerPrimaryCtxFlags = 0; 495 int FormerPrimaryCtxIsActive = 0; 496 Err = cuDevicePrimaryCtxGetState(Device, &FormerPrimaryCtxFlags, 497 &FormerPrimaryCtxIsActive); 498 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxGetState\n")) 499 return OFFLOAD_FAIL; 500 501 if (FormerPrimaryCtxIsActive) { 502 DP("The primary context is active, no change to its flags\n"); 503 if ((FormerPrimaryCtxFlags & CU_CTX_SCHED_MASK) != 504 CU_CTX_SCHED_BLOCKING_SYNC) 505 DP("Warning the current flags are not CU_CTX_SCHED_BLOCKING_SYNC\n"); 506 } else { 507 DP("The primary context is inactive, set its flags to " 508 "CU_CTX_SCHED_BLOCKING_SYNC\n"); 509 Err = cuDevicePrimaryCtxSetFlags_v2(Device, CU_CTX_SCHED_BLOCKING_SYNC); 510 if (!checkResult(Err, 511 "Error returned from cuDevicePrimaryCtxSetFlags_v2\n")) 512 return OFFLOAD_FAIL; 513 } 514 515 // Retain the per device primary context and save it to use whenever this 516 // device is selected. 517 Err = cuDevicePrimaryCtxRetain(&DeviceData[DeviceId].Context, Device); 518 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxRetain\n")) 519 return OFFLOAD_FAIL; 520 521 Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 522 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 523 return OFFLOAD_FAIL; 524 525 // Initialize stream pool 526 if (!StreamManager->initializeDeviceStreamPool(DeviceId)) 527 return OFFLOAD_FAIL; 528 529 // Query attributes to determine number of threads/block and blocks/grid. 530 int MaxGridDimX; 531 Err = cuDeviceGetAttribute(&MaxGridDimX, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X, 532 Device); 533 if (Err != CUDA_SUCCESS) { 534 DP("Error getting max grid dimension, use default value %d\n", 535 DeviceRTLTy::DefaultNumTeams); 536 DeviceData[DeviceId].BlocksPerGrid = DeviceRTLTy::DefaultNumTeams; 537 } else if (MaxGridDimX <= DeviceRTLTy::HardTeamLimit) { 538 DP("Using %d CUDA blocks per grid\n", MaxGridDimX); 539 DeviceData[DeviceId].BlocksPerGrid = MaxGridDimX; 540 } else { 541 DP("Max CUDA blocks per grid %d exceeds the hard team limit %d, capping " 542 "at the hard limit\n", 543 MaxGridDimX, DeviceRTLTy::HardTeamLimit); 544 DeviceData[DeviceId].BlocksPerGrid = DeviceRTLTy::HardTeamLimit; 545 } 546 547 // We are only exploiting threads along the x axis. 548 int MaxBlockDimX; 549 Err = cuDeviceGetAttribute(&MaxBlockDimX, 550 CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, Device); 551 if (Err != CUDA_SUCCESS) { 552 DP("Error getting max block dimension, use default value %d\n", 553 DeviceRTLTy::DefaultNumThreads); 554 DeviceData[DeviceId].ThreadsPerBlock = DeviceRTLTy::DefaultNumThreads; 555 } else if (MaxBlockDimX <= DeviceRTLTy::HardThreadLimit) { 556 DP("Using %d CUDA threads per block\n", MaxBlockDimX); 557 DeviceData[DeviceId].ThreadsPerBlock = MaxBlockDimX; 558 } else { 559 DP("Max CUDA threads per block %d exceeds the hard thread limit %d, " 560 "capping at the hard limit\n", 561 MaxBlockDimX, DeviceRTLTy::HardThreadLimit); 562 DeviceData[DeviceId].ThreadsPerBlock = DeviceRTLTy::HardThreadLimit; 563 } 564 565 // Get and set warp size 566 int WarpSize; 567 Err = 568 cuDeviceGetAttribute(&WarpSize, CU_DEVICE_ATTRIBUTE_WARP_SIZE, Device); 569 if (Err != CUDA_SUCCESS) { 570 DP("Error getting warp size, assume default value 32\n"); 571 DeviceData[DeviceId].WarpSize = 32; 572 } else { 573 DP("Using warp size %d\n", WarpSize); 574 DeviceData[DeviceId].WarpSize = WarpSize; 575 } 576 577 // Adjust teams to the env variables 578 if (EnvTeamLimit > 0 && DeviceData[DeviceId].BlocksPerGrid > EnvTeamLimit) { 579 DP("Capping max CUDA blocks per grid to OMP_TEAM_LIMIT=%d\n", 580 EnvTeamLimit); 581 DeviceData[DeviceId].BlocksPerGrid = EnvTeamLimit; 582 } 583 584 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 585 "Device supports up to %d CUDA blocks and %d threads with a " 586 "warp size of %d\n", 587 DeviceData[DeviceId].BlocksPerGrid, 588 DeviceData[DeviceId].ThreadsPerBlock, DeviceData[DeviceId].WarpSize); 589 590 // Set default number of teams 591 if (EnvNumTeams > 0) { 592 DP("Default number of teams set according to environment %d\n", 593 EnvNumTeams); 594 DeviceData[DeviceId].NumTeams = EnvNumTeams; 595 } else { 596 DeviceData[DeviceId].NumTeams = DeviceRTLTy::DefaultNumTeams; 597 DP("Default number of teams set according to library's default %d\n", 598 DeviceRTLTy::DefaultNumTeams); 599 } 600 601 if (DeviceData[DeviceId].NumTeams > DeviceData[DeviceId].BlocksPerGrid) { 602 DP("Default number of teams exceeds device limit, capping at %d\n", 603 DeviceData[DeviceId].BlocksPerGrid); 604 DeviceData[DeviceId].NumTeams = DeviceData[DeviceId].BlocksPerGrid; 605 } 606 607 // Set default number of threads 608 DeviceData[DeviceId].NumThreads = DeviceRTLTy::DefaultNumThreads; 609 DP("Default number of threads set according to library's default %d\n", 610 DeviceRTLTy::DefaultNumThreads); 611 if (DeviceData[DeviceId].NumThreads > 612 DeviceData[DeviceId].ThreadsPerBlock) { 613 DP("Default number of threads exceeds device limit, capping at %d\n", 614 DeviceData[DeviceId].ThreadsPerBlock); 615 DeviceData[DeviceId].NumTeams = DeviceData[DeviceId].ThreadsPerBlock; 616 } 617 618 return OFFLOAD_SUCCESS; 619 } 620 621 __tgt_target_table *loadBinary(const int DeviceId, 622 const __tgt_device_image *Image) { 623 // Set the context we are using 624 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 625 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 626 return nullptr; 627 628 // Clear the offload table as we are going to create a new one. 629 clearOffloadEntriesTable(DeviceId); 630 631 // Create the module and extract the function pointers. 632 CUmodule Module; 633 DP("Load data from image " DPxMOD "\n", DPxPTR(Image->ImageStart)); 634 Err = cuModuleLoadDataEx(&Module, Image->ImageStart, 0, nullptr, nullptr); 635 if (!checkResult(Err, "Error returned from cuModuleLoadDataEx\n")) 636 return nullptr; 637 638 DP("CUDA module successfully loaded!\n"); 639 640 Modules.push_back(Module); 641 642 // Find the symbols in the module by name. 643 const __tgt_offload_entry *HostBegin = Image->EntriesBegin; 644 const __tgt_offload_entry *HostEnd = Image->EntriesEnd; 645 646 std::list<KernelTy> &KernelsList = DeviceData[DeviceId].KernelsList; 647 for (const __tgt_offload_entry *E = HostBegin; E != HostEnd; ++E) { 648 if (!E->addr) { 649 // We return nullptr when something like this happens, the host should 650 // have always something in the address to uniquely identify the target 651 // region. 652 DP("Invalid binary: host entry '<null>' (size = %zd)...\n", E->size); 653 return nullptr; 654 } 655 656 if (E->size) { 657 __tgt_offload_entry Entry = *E; 658 CUdeviceptr CUPtr; 659 size_t CUSize; 660 Err = cuModuleGetGlobal_v2(&CUPtr, &CUSize, Module, E->name); 661 // We keep this style here because we need the name 662 if (Err != CUDA_SUCCESS) { 663 REPORT("Loading global '%s' Failed\n", E->name); 664 CUDA_ERR_STRING(Err); 665 return nullptr; 666 } 667 668 if (CUSize != E->size) { 669 DP("Loading global '%s' - size mismatch (%zd != %zd)\n", E->name, 670 CUSize, E->size); 671 return nullptr; 672 } 673 674 DP("Entry point " DPxMOD " maps to global %s (" DPxMOD ")\n", 675 DPxPTR(E - HostBegin), E->name, DPxPTR(CUPtr)); 676 677 Entry.addr = (void *)(CUPtr); 678 679 // Note: In the current implementation declare target variables 680 // can either be link or to. This means that once unified 681 // memory is activated via the requires directive, the variable 682 // can be used directly from the host in both cases. 683 // TODO: when variables types other than to or link are added, 684 // the below condition should be changed to explicitly 685 // check for to and link variables types: 686 // (RequiresFlags & OMP_REQ_UNIFIED_SHARED_MEMORY && (e->flags & 687 // OMP_DECLARE_TARGET_LINK || e->flags == OMP_DECLARE_TARGET_TO)) 688 if (RequiresFlags & OMP_REQ_UNIFIED_SHARED_MEMORY) { 689 // If unified memory is present any target link or to variables 690 // can access host addresses directly. There is no longer a 691 // need for device copies. 692 cuMemcpyHtoD_v2(CUPtr, E->addr, sizeof(void *)); 693 DP("Copy linked variable host address (" DPxMOD 694 ") to device address (" DPxMOD ")\n", 695 DPxPTR(*((void **)E->addr)), DPxPTR(CUPtr)); 696 } 697 698 addOffloadEntry(DeviceId, Entry); 699 700 continue; 701 } 702 703 CUfunction Func; 704 Err = cuModuleGetFunction(&Func, Module, E->name); 705 // We keep this style here because we need the name 706 if (Err != CUDA_SUCCESS) { 707 REPORT("Loading '%s' Failed\n", E->name); 708 CUDA_ERR_STRING(Err); 709 return nullptr; 710 } 711 712 DP("Entry point " DPxMOD " maps to %s (" DPxMOD ")\n", 713 DPxPTR(E - HostBegin), E->name, DPxPTR(Func)); 714 715 // default value GENERIC (in case symbol is missing from cubin file) 716 int8_t ExecModeVal = ExecutionModeType::GENERIC; 717 std::string ExecModeNameStr(E->name); 718 ExecModeNameStr += "_exec_mode"; 719 const char *ExecModeName = ExecModeNameStr.c_str(); 720 721 CUdeviceptr ExecModePtr; 722 size_t CUSize; 723 Err = cuModuleGetGlobal_v2(&ExecModePtr, &CUSize, Module, ExecModeName); 724 if (Err == CUDA_SUCCESS) { 725 if (CUSize != sizeof(int8_t)) { 726 DP("Loading global exec_mode '%s' - size mismatch (%zd != %zd)\n", 727 ExecModeName, CUSize, sizeof(int8_t)); 728 return nullptr; 729 } 730 731 Err = cuMemcpyDtoH_v2(&ExecModeVal, ExecModePtr, CUSize); 732 if (Err != CUDA_SUCCESS) { 733 REPORT("Error when copying data from device to host. Pointers: " 734 "host = " DPxMOD ", device = " DPxMOD ", size = %zd\n", 735 DPxPTR(&ExecModeVal), DPxPTR(ExecModePtr), CUSize); 736 CUDA_ERR_STRING(Err); 737 return nullptr; 738 } 739 740 if (ExecModeVal < 0 || ExecModeVal > 1) { 741 DP("Error wrong exec_mode value specified in cubin file: %d\n", 742 ExecModeVal); 743 return nullptr; 744 } 745 } else { 746 REPORT("Loading global exec_mode '%s' - symbol missing, using default " 747 "value GENERIC (1)\n", 748 ExecModeName); 749 CUDA_ERR_STRING(Err); 750 } 751 752 KernelsList.emplace_back(Func, ExecModeVal); 753 754 __tgt_offload_entry Entry = *E; 755 Entry.addr = &KernelsList.back(); 756 addOffloadEntry(DeviceId, Entry); 757 } 758 759 // send device environment data to the device 760 { 761 omptarget_device_environmentTy DeviceEnv{0}; 762 763 #ifdef OMPTARGET_DEBUG 764 if (const char *EnvStr = getenv("LIBOMPTARGET_DEVICE_RTL_DEBUG")) 765 DeviceEnv.debug_level = std::stoi(EnvStr); 766 #endif 767 768 const char *DeviceEnvName = "omptarget_device_environment"; 769 CUdeviceptr DeviceEnvPtr; 770 size_t CUSize; 771 772 Err = cuModuleGetGlobal_v2(&DeviceEnvPtr, &CUSize, Module, DeviceEnvName); 773 if (Err == CUDA_SUCCESS) { 774 if (CUSize != sizeof(DeviceEnv)) { 775 REPORT( 776 "Global device_environment '%s' - size mismatch (%zu != %zu)\n", 777 DeviceEnvName, CUSize, sizeof(int32_t)); 778 CUDA_ERR_STRING(Err); 779 return nullptr; 780 } 781 782 Err = cuMemcpyHtoD_v2(DeviceEnvPtr, &DeviceEnv, CUSize); 783 if (Err != CUDA_SUCCESS) { 784 REPORT("Error when copying data from host to device. Pointers: " 785 "host = " DPxMOD ", device = " DPxMOD ", size = %zu\n", 786 DPxPTR(&DeviceEnv), DPxPTR(DeviceEnvPtr), CUSize); 787 CUDA_ERR_STRING(Err); 788 return nullptr; 789 } 790 791 DP("Sending global device environment data %zu bytes\n", CUSize); 792 } else { 793 DP("Finding global device environment '%s' - symbol missing.\n", 794 DeviceEnvName); 795 DP("Continue, considering this is a device RTL which does not accept " 796 "environment setting.\n"); 797 } 798 } 799 800 return getOffloadEntriesTable(DeviceId); 801 } 802 803 void *dataAlloc(const int DeviceId, const int64_t Size) { 804 if (UseMemoryManager) 805 return MemoryManagers[DeviceId]->allocate(Size, nullptr); 806 807 return DeviceAllocators[DeviceId].allocate(Size, nullptr); 808 } 809 810 int dataSubmit(const int DeviceId, const void *TgtPtr, const void *HstPtr, 811 const int64_t Size, __tgt_async_info *AsyncInfoPtr) const { 812 assert(AsyncInfoPtr && "AsyncInfoPtr is nullptr"); 813 814 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 815 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 816 return OFFLOAD_FAIL; 817 818 CUstream Stream = getStream(DeviceId, AsyncInfoPtr); 819 820 Err = cuMemcpyHtoDAsync_v2((CUdeviceptr)TgtPtr, HstPtr, Size, Stream); 821 if (Err != CUDA_SUCCESS) { 822 REPORT("Error when copying data from host to device. Pointers: host " 823 "= " DPxMOD ", device = " DPxMOD ", size = %" PRId64 "\n", 824 DPxPTR(HstPtr), DPxPTR(TgtPtr), Size); 825 CUDA_ERR_STRING(Err); 826 return OFFLOAD_FAIL; 827 } 828 829 return OFFLOAD_SUCCESS; 830 } 831 832 int dataRetrieve(const int DeviceId, void *HstPtr, const void *TgtPtr, 833 const int64_t Size, __tgt_async_info *AsyncInfoPtr) const { 834 assert(AsyncInfoPtr && "AsyncInfoPtr is nullptr"); 835 836 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 837 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 838 return OFFLOAD_FAIL; 839 840 CUstream Stream = getStream(DeviceId, AsyncInfoPtr); 841 842 Err = cuMemcpyDtoHAsync_v2(HstPtr, (CUdeviceptr)TgtPtr, Size, Stream); 843 if (Err != CUDA_SUCCESS) { 844 REPORT("Error when copying data from device to host. Pointers: host " 845 "= " DPxMOD ", device = " DPxMOD ", size = %" PRId64 "\n", 846 DPxPTR(HstPtr), DPxPTR(TgtPtr), Size); 847 CUDA_ERR_STRING(Err); 848 return OFFLOAD_FAIL; 849 } 850 851 return OFFLOAD_SUCCESS; 852 } 853 854 int dataExchange(int SrcDevId, const void *SrcPtr, int DstDevId, void *DstPtr, 855 int64_t Size, __tgt_async_info *AsyncInfoPtr) const { 856 assert(AsyncInfoPtr && "AsyncInfoPtr is nullptr"); 857 858 CUresult Err = cuCtxSetCurrent(DeviceData[SrcDevId].Context); 859 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 860 return OFFLOAD_FAIL; 861 862 CUstream Stream = getStream(SrcDevId, AsyncInfoPtr); 863 864 // If they are two devices, we try peer to peer copy first 865 if (SrcDevId != DstDevId) { 866 int CanAccessPeer = 0; 867 Err = cuDeviceCanAccessPeer(&CanAccessPeer, SrcDevId, DstDevId); 868 if (Err != CUDA_SUCCESS) { 869 REPORT("Error returned from cuDeviceCanAccessPeer. src = %" PRId32 870 ", dst = %" PRId32 "\n", 871 SrcDevId, DstDevId); 872 CUDA_ERR_STRING(Err); 873 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 874 } 875 876 if (!CanAccessPeer) { 877 DP("P2P memcpy not supported so fall back to D2D memcpy"); 878 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 879 } 880 881 Err = cuCtxEnablePeerAccess(DeviceData[DstDevId].Context, 0); 882 if (Err != CUDA_SUCCESS) { 883 REPORT("Error returned from cuCtxEnablePeerAccess. src = %" PRId32 884 ", dst = %" PRId32 "\n", 885 SrcDevId, DstDevId); 886 CUDA_ERR_STRING(Err); 887 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 888 } 889 890 Err = cuMemcpyPeerAsync((CUdeviceptr)DstPtr, DeviceData[DstDevId].Context, 891 (CUdeviceptr)SrcPtr, DeviceData[SrcDevId].Context, 892 Size, Stream); 893 if (Err == CUDA_SUCCESS) 894 return OFFLOAD_SUCCESS; 895 896 REPORT("Error returned from cuMemcpyPeerAsync. src_ptr = " DPxMOD 897 ", src_id =%" PRId32 ", dst_ptr = " DPxMOD ", dst_id =%" PRId32 898 "\n", 899 DPxPTR(SrcPtr), SrcDevId, DPxPTR(DstPtr), DstDevId); 900 CUDA_ERR_STRING(Err); 901 } 902 903 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 904 } 905 906 int dataDelete(const int DeviceId, void *TgtPtr) { 907 if (UseMemoryManager) 908 return MemoryManagers[DeviceId]->free(TgtPtr); 909 910 return DeviceAllocators[DeviceId].free(TgtPtr); 911 } 912 913 int runTargetTeamRegion(const int DeviceId, void *TgtEntryPtr, void **TgtArgs, 914 ptrdiff_t *TgtOffsets, const int ArgNum, 915 const int TeamNum, const int ThreadLimit, 916 const unsigned int LoopTripCount, 917 __tgt_async_info *AsyncInfo) const { 918 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 919 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 920 return OFFLOAD_FAIL; 921 922 // All args are references. 923 std::vector<void *> Args(ArgNum); 924 std::vector<void *> Ptrs(ArgNum); 925 926 for (int I = 0; I < ArgNum; ++I) { 927 Ptrs[I] = (void *)((intptr_t)TgtArgs[I] + TgtOffsets[I]); 928 Args[I] = &Ptrs[I]; 929 } 930 931 KernelTy *KernelInfo = reinterpret_cast<KernelTy *>(TgtEntryPtr); 932 933 int CudaThreadsPerBlock; 934 if (ThreadLimit > 0) { 935 DP("Setting CUDA threads per block to requested %d\n", ThreadLimit); 936 CudaThreadsPerBlock = ThreadLimit; 937 // Add master warp if necessary 938 if (KernelInfo->ExecutionMode == GENERIC) { 939 DP("Adding master warp: +%d threads\n", DeviceData[DeviceId].WarpSize); 940 CudaThreadsPerBlock += DeviceData[DeviceId].WarpSize; 941 } 942 } else { 943 DP("Setting CUDA threads per block to default %d\n", 944 DeviceData[DeviceId].NumThreads); 945 CudaThreadsPerBlock = DeviceData[DeviceId].NumThreads; 946 } 947 948 if (CudaThreadsPerBlock > DeviceData[DeviceId].ThreadsPerBlock) { 949 DP("Threads per block capped at device limit %d\n", 950 DeviceData[DeviceId].ThreadsPerBlock); 951 CudaThreadsPerBlock = DeviceData[DeviceId].ThreadsPerBlock; 952 } 953 954 if (!KernelInfo->MaxThreadsPerBlock) { 955 Err = cuFuncGetAttribute(&KernelInfo->MaxThreadsPerBlock, 956 CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, 957 KernelInfo->Func); 958 if (!checkResult(Err, "Error returned from cuFuncGetAttribute\n")) 959 return OFFLOAD_FAIL; 960 } 961 962 if (KernelInfo->MaxThreadsPerBlock < CudaThreadsPerBlock) { 963 DP("Threads per block capped at kernel limit %d\n", 964 KernelInfo->MaxThreadsPerBlock); 965 CudaThreadsPerBlock = KernelInfo->MaxThreadsPerBlock; 966 } 967 968 unsigned int CudaBlocksPerGrid; 969 if (TeamNum <= 0) { 970 if (LoopTripCount > 0 && EnvNumTeams < 0) { 971 if (KernelInfo->ExecutionMode == SPMD) { 972 // We have a combined construct, i.e. `target teams distribute 973 // parallel for [simd]`. We launch so many teams so that each thread 974 // will execute one iteration of the loop. round up to the nearest 975 // integer 976 CudaBlocksPerGrid = ((LoopTripCount - 1) / CudaThreadsPerBlock) + 1; 977 } else { 978 // If we reach this point, then we have a non-combined construct, i.e. 979 // `teams distribute` with a nested `parallel for` and each team is 980 // assigned one iteration of the `distribute` loop. E.g.: 981 // 982 // #pragma omp target teams distribute 983 // for(...loop_tripcount...) { 984 // #pragma omp parallel for 985 // for(...) {} 986 // } 987 // 988 // Threads within a team will execute the iterations of the `parallel` 989 // loop. 990 CudaBlocksPerGrid = LoopTripCount; 991 } 992 DP("Using %d teams due to loop trip count %" PRIu32 993 " and number of threads per block %d\n", 994 CudaBlocksPerGrid, LoopTripCount, CudaThreadsPerBlock); 995 } else { 996 DP("Using default number of teams %d\n", DeviceData[DeviceId].NumTeams); 997 CudaBlocksPerGrid = DeviceData[DeviceId].NumTeams; 998 } 999 } else if (TeamNum > DeviceData[DeviceId].BlocksPerGrid) { 1000 DP("Capping number of teams to team limit %d\n", 1001 DeviceData[DeviceId].BlocksPerGrid); 1002 CudaBlocksPerGrid = DeviceData[DeviceId].BlocksPerGrid; 1003 } else { 1004 DP("Using requested number of teams %d\n", TeamNum); 1005 CudaBlocksPerGrid = TeamNum; 1006 } 1007 1008 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 1009 "Launching kernel %s with %d blocks and %d threads in %s " 1010 "mode\n", 1011 (getOffloadEntry(DeviceId, TgtEntryPtr)) 1012 ? getOffloadEntry(DeviceId, TgtEntryPtr)->name 1013 : "(null)", 1014 CudaBlocksPerGrid, CudaThreadsPerBlock, 1015 (KernelInfo->ExecutionMode == SPMD) ? "SPMD" : "Generic"); 1016 1017 CUstream Stream = getStream(DeviceId, AsyncInfo); 1018 Err = cuLaunchKernel(KernelInfo->Func, CudaBlocksPerGrid, /* gridDimY */ 1, 1019 /* gridDimZ */ 1, CudaThreadsPerBlock, 1020 /* blockDimY */ 1, /* blockDimZ */ 1, 1021 /* sharedMemBytes */ 0, Stream, &Args[0], nullptr); 1022 if (!checkResult(Err, "Error returned from cuLaunchKernel\n")) 1023 return OFFLOAD_FAIL; 1024 1025 DP("Launch of entry point at " DPxMOD " successful!\n", 1026 DPxPTR(TgtEntryPtr)); 1027 1028 return OFFLOAD_SUCCESS; 1029 } 1030 1031 int synchronize(const int DeviceId, __tgt_async_info *AsyncInfoPtr) const { 1032 CUstream Stream = reinterpret_cast<CUstream>(AsyncInfoPtr->Queue); 1033 CUresult Err = cuStreamSynchronize(Stream); 1034 if (Err != CUDA_SUCCESS) { 1035 REPORT("Error when synchronizing stream. stream = " DPxMOD 1036 ", async info ptr = " DPxMOD "\n", 1037 DPxPTR(Stream), DPxPTR(AsyncInfoPtr)); 1038 CUDA_ERR_STRING(Err); 1039 return OFFLOAD_FAIL; 1040 } 1041 1042 // Once the stream is synchronized, return it to stream pool and reset 1043 // async_info. This is to make sure the synchronization only works for its 1044 // own tasks. 1045 StreamManager->returnStream( 1046 DeviceId, reinterpret_cast<CUstream>(AsyncInfoPtr->Queue)); 1047 AsyncInfoPtr->Queue = nullptr; 1048 1049 return OFFLOAD_SUCCESS; 1050 } 1051 }; 1052 1053 DeviceRTLTy DeviceRTL; 1054 } // namespace 1055 1056 // Exposed library API function 1057 #ifdef __cplusplus 1058 extern "C" { 1059 #endif 1060 1061 int32_t __tgt_rtl_is_valid_binary(__tgt_device_image *image) { 1062 return elf_check_machine(image, /* EM_CUDA */ 190); 1063 } 1064 1065 int32_t __tgt_rtl_number_of_devices() { return DeviceRTL.getNumOfDevices(); } 1066 1067 int64_t __tgt_rtl_init_requires(int64_t RequiresFlags) { 1068 DP("Init requires flags to %" PRId64 "\n", RequiresFlags); 1069 DeviceRTL.setRequiresFlag(RequiresFlags); 1070 return RequiresFlags; 1071 } 1072 1073 int32_t __tgt_rtl_is_data_exchangable(int32_t src_dev_id, int dst_dev_id) { 1074 if (DeviceRTL.isValidDeviceId(src_dev_id) && 1075 DeviceRTL.isValidDeviceId(dst_dev_id)) 1076 return 1; 1077 1078 return 0; 1079 } 1080 1081 int32_t __tgt_rtl_init_device(int32_t device_id) { 1082 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1083 1084 return DeviceRTL.initDevice(device_id); 1085 } 1086 1087 __tgt_target_table *__tgt_rtl_load_binary(int32_t device_id, 1088 __tgt_device_image *image) { 1089 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1090 1091 return DeviceRTL.loadBinary(device_id, image); 1092 } 1093 1094 void *__tgt_rtl_data_alloc(int32_t device_id, int64_t size, void *) { 1095 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1096 1097 return DeviceRTL.dataAlloc(device_id, size); 1098 } 1099 1100 int32_t __tgt_rtl_data_submit(int32_t device_id, void *tgt_ptr, void *hst_ptr, 1101 int64_t size) { 1102 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1103 1104 __tgt_async_info async_info; 1105 const int32_t rc = __tgt_rtl_data_submit_async(device_id, tgt_ptr, hst_ptr, 1106 size, &async_info); 1107 if (rc != OFFLOAD_SUCCESS) 1108 return OFFLOAD_FAIL; 1109 1110 return __tgt_rtl_synchronize(device_id, &async_info); 1111 } 1112 1113 int32_t __tgt_rtl_data_submit_async(int32_t device_id, void *tgt_ptr, 1114 void *hst_ptr, int64_t size, 1115 __tgt_async_info *async_info_ptr) { 1116 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1117 assert(async_info_ptr && "async_info_ptr is nullptr"); 1118 1119 return DeviceRTL.dataSubmit(device_id, tgt_ptr, hst_ptr, size, 1120 async_info_ptr); 1121 } 1122 1123 int32_t __tgt_rtl_data_retrieve(int32_t device_id, void *hst_ptr, void *tgt_ptr, 1124 int64_t size) { 1125 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1126 1127 __tgt_async_info async_info; 1128 const int32_t rc = __tgt_rtl_data_retrieve_async(device_id, hst_ptr, tgt_ptr, 1129 size, &async_info); 1130 if (rc != OFFLOAD_SUCCESS) 1131 return OFFLOAD_FAIL; 1132 1133 return __tgt_rtl_synchronize(device_id, &async_info); 1134 } 1135 1136 int32_t __tgt_rtl_data_retrieve_async(int32_t device_id, void *hst_ptr, 1137 void *tgt_ptr, int64_t size, 1138 __tgt_async_info *async_info_ptr) { 1139 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1140 assert(async_info_ptr && "async_info_ptr is nullptr"); 1141 1142 return DeviceRTL.dataRetrieve(device_id, hst_ptr, tgt_ptr, size, 1143 async_info_ptr); 1144 } 1145 1146 int32_t __tgt_rtl_data_exchange_async(int32_t src_dev_id, void *src_ptr, 1147 int dst_dev_id, void *dst_ptr, 1148 int64_t size, 1149 __tgt_async_info *async_info_ptr) { 1150 assert(DeviceRTL.isValidDeviceId(src_dev_id) && "src_dev_id is invalid"); 1151 assert(DeviceRTL.isValidDeviceId(dst_dev_id) && "dst_dev_id is invalid"); 1152 assert(async_info_ptr && "async_info_ptr is nullptr"); 1153 1154 return DeviceRTL.dataExchange(src_dev_id, src_ptr, dst_dev_id, dst_ptr, size, 1155 async_info_ptr); 1156 } 1157 1158 int32_t __tgt_rtl_data_exchange(int32_t src_dev_id, void *src_ptr, 1159 int32_t dst_dev_id, void *dst_ptr, 1160 int64_t size) { 1161 assert(DeviceRTL.isValidDeviceId(src_dev_id) && "src_dev_id is invalid"); 1162 assert(DeviceRTL.isValidDeviceId(dst_dev_id) && "dst_dev_id is invalid"); 1163 1164 __tgt_async_info async_info; 1165 const int32_t rc = __tgt_rtl_data_exchange_async( 1166 src_dev_id, src_ptr, dst_dev_id, dst_ptr, size, &async_info); 1167 if (rc != OFFLOAD_SUCCESS) 1168 return OFFLOAD_FAIL; 1169 1170 return __tgt_rtl_synchronize(src_dev_id, &async_info); 1171 } 1172 1173 int32_t __tgt_rtl_data_delete(int32_t device_id, void *tgt_ptr) { 1174 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1175 1176 return DeviceRTL.dataDelete(device_id, tgt_ptr); 1177 } 1178 1179 int32_t __tgt_rtl_run_target_team_region(int32_t device_id, void *tgt_entry_ptr, 1180 void **tgt_args, 1181 ptrdiff_t *tgt_offsets, 1182 int32_t arg_num, int32_t team_num, 1183 int32_t thread_limit, 1184 uint64_t loop_tripcount) { 1185 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1186 1187 __tgt_async_info async_info; 1188 const int32_t rc = __tgt_rtl_run_target_team_region_async( 1189 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, team_num, 1190 thread_limit, loop_tripcount, &async_info); 1191 if (rc != OFFLOAD_SUCCESS) 1192 return OFFLOAD_FAIL; 1193 1194 return __tgt_rtl_synchronize(device_id, &async_info); 1195 } 1196 1197 int32_t __tgt_rtl_run_target_team_region_async( 1198 int32_t device_id, void *tgt_entry_ptr, void **tgt_args, 1199 ptrdiff_t *tgt_offsets, int32_t arg_num, int32_t team_num, 1200 int32_t thread_limit, uint64_t loop_tripcount, 1201 __tgt_async_info *async_info_ptr) { 1202 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1203 1204 return DeviceRTL.runTargetTeamRegion( 1205 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, team_num, 1206 thread_limit, loop_tripcount, async_info_ptr); 1207 } 1208 1209 int32_t __tgt_rtl_run_target_region(int32_t device_id, void *tgt_entry_ptr, 1210 void **tgt_args, ptrdiff_t *tgt_offsets, 1211 int32_t arg_num) { 1212 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1213 1214 __tgt_async_info async_info; 1215 const int32_t rc = __tgt_rtl_run_target_region_async( 1216 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, &async_info); 1217 if (rc != OFFLOAD_SUCCESS) 1218 return OFFLOAD_FAIL; 1219 1220 return __tgt_rtl_synchronize(device_id, &async_info); 1221 } 1222 1223 int32_t __tgt_rtl_run_target_region_async(int32_t device_id, 1224 void *tgt_entry_ptr, void **tgt_args, 1225 ptrdiff_t *tgt_offsets, 1226 int32_t arg_num, 1227 __tgt_async_info *async_info_ptr) { 1228 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1229 1230 return __tgt_rtl_run_target_team_region_async( 1231 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, 1232 /* team num*/ 1, /* thread_limit */ 1, /* loop_tripcount */ 0, 1233 async_info_ptr); 1234 } 1235 1236 int32_t __tgt_rtl_synchronize(int32_t device_id, 1237 __tgt_async_info *async_info_ptr) { 1238 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1239 assert(async_info_ptr && "async_info_ptr is nullptr"); 1240 assert(async_info_ptr->Queue && "async_info_ptr->Queue is nullptr"); 1241 1242 return DeviceRTL.synchronize(device_id, async_info_ptr); 1243 } 1244 1245 #ifdef __cplusplus 1246 } 1247 #endif 1248