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 <unordered_map> 21 #include <vector> 22 23 #include "Debug.h" 24 #include "omptargetplugin.h" 25 26 #define TARGET_NAME CUDA 27 #define DEBUG_PREFIX "Target " GETNAME(TARGET_NAME) " RTL" 28 29 #include "MemoryManager.h" 30 31 // Utility for retrieving and printing CUDA error string. 32 #ifdef OMPTARGET_DEBUG 33 #define CUDA_ERR_STRING(err) \ 34 do { \ 35 if (getDebugLevel() > 0) { \ 36 const char *errStr = nullptr; \ 37 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 38 if (errStr_status == CUDA_ERROR_INVALID_VALUE) \ 39 REPORT("Unrecognized CUDA error code: %d\n", err); \ 40 else if (errStr_status == CUDA_SUCCESS) \ 41 REPORT("CUDA error is: %s\n", errStr); \ 42 else { \ 43 REPORT("Unresolved CUDA error code: %d\n", err); \ 44 REPORT("Unsuccessful cuGetErrorString return status: %d\n", \ 45 errStr_status); \ 46 } \ 47 } else { \ 48 const char *errStr = nullptr; \ 49 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 50 if (errStr_status == CUDA_SUCCESS) \ 51 REPORT("%s \n", errStr); \ 52 } \ 53 } while (false) 54 #else // OMPTARGET_DEBUG 55 #define CUDA_ERR_STRING(err) \ 56 do { \ 57 const char *errStr = nullptr; \ 58 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 59 if (errStr_status == CUDA_SUCCESS) \ 60 REPORT("%s \n", errStr); \ 61 } while (false) 62 #endif // OMPTARGET_DEBUG 63 64 #include "elf_common.h" 65 66 /// Keep entries table per device. 67 struct FuncOrGblEntryTy { 68 __tgt_target_table Table; 69 std::vector<__tgt_offload_entry> Entries; 70 }; 71 72 enum ExecutionModeType { 73 SPMD, // constructors, destructors, 74 // combined constructs (`teams distribute parallel for [simd]`) 75 GENERIC, // everything else 76 NONE 77 }; 78 79 /// Use a single entity to encode a kernel and a set of flags. 80 struct KernelTy { 81 CUfunction Func; 82 83 // execution mode of kernel 84 // 0 - SPMD mode (without master warp) 85 // 1 - Generic mode (with master warp) 86 int8_t ExecutionMode; 87 88 /// Maximal number of threads per block for this kernel. 89 int MaxThreadsPerBlock = 0; 90 91 KernelTy(CUfunction _Func, int8_t _ExecutionMode) 92 : Func(_Func), ExecutionMode(_ExecutionMode) {} 93 }; 94 95 /// Device environment data 96 /// Manually sync with the deviceRTL side for now, move to a dedicated header 97 /// file later. 98 struct omptarget_device_environmentTy { 99 int32_t debug_level; 100 }; 101 102 namespace { 103 bool checkResult(CUresult Err, const char *ErrMsg) { 104 if (Err == CUDA_SUCCESS) 105 return true; 106 107 REPORT("%s", ErrMsg); 108 CUDA_ERR_STRING(Err); 109 return false; 110 } 111 112 int memcpyDtoD(const void *SrcPtr, void *DstPtr, int64_t Size, 113 CUstream Stream) { 114 CUresult Err = 115 cuMemcpyDtoDAsync((CUdeviceptr)DstPtr, (CUdeviceptr)SrcPtr, Size, Stream); 116 117 if (Err != CUDA_SUCCESS) { 118 DP("Error when copying data from device to device. Pointers: src " 119 "= " DPxMOD ", dst = " DPxMOD ", size = %" PRId64 "\n", 120 DPxPTR(SrcPtr), DPxPTR(DstPtr), Size); 121 CUDA_ERR_STRING(Err); 122 return OFFLOAD_FAIL; 123 } 124 125 return OFFLOAD_SUCCESS; 126 } 127 128 // Structure contains per-device data 129 struct DeviceDataTy { 130 /// List that contains all the kernels. 131 std::list<KernelTy> KernelsList; 132 133 std::list<FuncOrGblEntryTy> FuncGblEntries; 134 135 CUcontext Context = nullptr; 136 // Device properties 137 int ThreadsPerBlock = 0; 138 int BlocksPerGrid = 0; 139 int WarpSize = 0; 140 // OpenMP properties 141 int NumTeams = 0; 142 int NumThreads = 0; 143 }; 144 145 class StreamManagerTy { 146 int NumberOfDevices; 147 // The initial size of stream pool 148 int EnvNumInitialStreams; 149 // Per-device stream mutex 150 std::vector<std::unique_ptr<std::mutex>> StreamMtx; 151 // Per-device stream Id indicates the next available stream in the pool 152 std::vector<int> NextStreamId; 153 // Per-device stream pool 154 std::vector<std::vector<CUstream>> StreamPool; 155 // Reference to per-device data 156 std::vector<DeviceDataTy> &DeviceData; 157 158 // If there is no CUstream left in the pool, we will resize the pool to 159 // allocate more CUstream. This function should be called with device mutex, 160 // and we do not resize to smaller one. 161 void resizeStreamPool(const int DeviceId, const size_t NewSize) { 162 std::vector<CUstream> &Pool = StreamPool[DeviceId]; 163 const size_t CurrentSize = Pool.size(); 164 assert(NewSize > CurrentSize && "new size is not larger than current size"); 165 166 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 167 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) { 168 // We will return if cannot switch to the right context in case of 169 // creating bunch of streams that are not corresponding to the right 170 // device. The offloading will fail later because selected CUstream is 171 // nullptr. 172 return; 173 } 174 175 Pool.resize(NewSize, nullptr); 176 177 for (size_t I = CurrentSize; I < NewSize; ++I) { 178 checkResult(cuStreamCreate(&Pool[I], CU_STREAM_NON_BLOCKING), 179 "Error returned from cuStreamCreate\n"); 180 } 181 } 182 183 public: 184 StreamManagerTy(const int NumberOfDevices, 185 std::vector<DeviceDataTy> &DeviceData) 186 : NumberOfDevices(NumberOfDevices), EnvNumInitialStreams(32), 187 DeviceData(DeviceData) { 188 StreamPool.resize(NumberOfDevices); 189 NextStreamId.resize(NumberOfDevices); 190 StreamMtx.resize(NumberOfDevices); 191 192 if (const char *EnvStr = getenv("LIBOMPTARGET_NUM_INITIAL_STREAMS")) 193 EnvNumInitialStreams = std::stoi(EnvStr); 194 195 // Initialize the next stream id 196 std::fill(NextStreamId.begin(), NextStreamId.end(), 0); 197 198 // Initialize stream mutex 199 for (std::unique_ptr<std::mutex> &Ptr : StreamMtx) 200 Ptr = std::make_unique<std::mutex>(); 201 } 202 203 ~StreamManagerTy() { 204 // Destroy streams 205 for (int I = 0; I < NumberOfDevices; ++I) { 206 checkResult(cuCtxSetCurrent(DeviceData[I].Context), 207 "Error returned from cuCtxSetCurrent\n"); 208 209 for (CUstream &S : StreamPool[I]) { 210 if (S) 211 checkResult(cuStreamDestroy(S), 212 "Error returned from cuStreamDestroy\n"); 213 } 214 } 215 } 216 217 // Get a CUstream from pool. Per-device next stream id always points to the 218 // next available CUstream. That means, CUstreams [0, id-1] have been 219 // assigned, and [id,] are still available. If there is no CUstream left, we 220 // will ask more CUstreams from CUDA RT. Each time a CUstream is assigned, 221 // the id will increase one. 222 // xxxxxs+++++++++ 223 // ^ 224 // id 225 // After assignment, the pool becomes the following and s is assigned. 226 // xxxxxs+++++++++ 227 // ^ 228 // id 229 CUstream getStream(const int DeviceId) { 230 const std::lock_guard<std::mutex> Lock(*StreamMtx[DeviceId]); 231 int &Id = NextStreamId[DeviceId]; 232 // No CUstream left in the pool, we need to request from CUDA RT 233 if (Id == static_cast<int>(StreamPool[DeviceId].size())) { 234 // By default we double the stream pool every time 235 resizeStreamPool(DeviceId, Id * 2); 236 } 237 return StreamPool[DeviceId][Id++]; 238 } 239 240 // Return a CUstream back to pool. As mentioned above, per-device next 241 // stream is always points to the next available CUstream, so when we return 242 // a CUstream, we need to first decrease the id, and then copy the CUstream 243 // back. 244 // It is worth noting that, the order of streams return might be different 245 // from that they're assigned, that saying, at some point, there might be 246 // two identical CUstreams. 247 // xxax+a+++++ 248 // ^ 249 // id 250 // However, it doesn't matter, because they're always on the two sides of 251 // id. The left one will in the end be overwritten by another CUstream. 252 // Therefore, after several execution, the order of pool might be different 253 // from its initial state. 254 void returnStream(const int DeviceId, CUstream Stream) { 255 const std::lock_guard<std::mutex> Lock(*StreamMtx[DeviceId]); 256 int &Id = NextStreamId[DeviceId]; 257 assert(Id > 0 && "Wrong stream ID"); 258 StreamPool[DeviceId][--Id] = Stream; 259 } 260 261 bool initializeDeviceStreamPool(const int DeviceId) { 262 assert(StreamPool[DeviceId].empty() && "stream pool has been initialized"); 263 264 resizeStreamPool(DeviceId, EnvNumInitialStreams); 265 266 // Check the size of stream pool 267 if (static_cast<int>(StreamPool[DeviceId].size()) != EnvNumInitialStreams) 268 return false; 269 270 // Check whether each stream is valid 271 for (CUstream &S : StreamPool[DeviceId]) 272 if (!S) 273 return false; 274 275 return true; 276 } 277 }; 278 279 class DeviceRTLTy { 280 int NumberOfDevices; 281 // OpenMP environment properties 282 int EnvNumTeams; 283 int EnvTeamLimit; 284 // OpenMP requires flags 285 int64_t RequiresFlags; 286 287 static constexpr const int HardTeamLimit = 1U << 16U; // 64k 288 static constexpr const int HardThreadLimit = 1024; 289 static constexpr const int DefaultNumTeams = 128; 290 static constexpr const int DefaultNumThreads = 128; 291 292 std::unique_ptr<StreamManagerTy> StreamManager; 293 std::vector<DeviceDataTy> DeviceData; 294 std::vector<CUmodule> Modules; 295 296 /// A class responsible for interacting with device native runtime library to 297 /// allocate and free memory. 298 class CUDADeviceAllocatorTy : public DeviceAllocatorTy { 299 const int DeviceId; 300 const std::vector<DeviceDataTy> &DeviceData; 301 std::unordered_map<void *, TargetAllocTy> HostPinnedAllocs; 302 303 public: 304 CUDADeviceAllocatorTy(int DeviceId, std::vector<DeviceDataTy> &DeviceData) 305 : DeviceId(DeviceId), DeviceData(DeviceData) {} 306 307 void *allocate(size_t Size, void *, TargetAllocTy Kind) override { 308 if (Size == 0) 309 return nullptr; 310 311 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 312 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 313 return nullptr; 314 315 void *MemAlloc = nullptr; 316 switch (Kind) { 317 case TARGET_ALLOC_DEFAULT: 318 case TARGET_ALLOC_DEVICE: 319 CUdeviceptr DevicePtr; 320 Err = cuMemAlloc(&DevicePtr, Size); 321 MemAlloc = (void *)DevicePtr; 322 if (!checkResult(Err, "Error returned from cuMemAlloc\n")) 323 return nullptr; 324 break; 325 case TARGET_ALLOC_HOST: 326 void *HostPtr; 327 Err = cuMemAllocHost(&HostPtr, Size); 328 MemAlloc = HostPtr; 329 if (!checkResult(Err, "Error returned from cuMemAllocHost\n")) 330 return nullptr; 331 HostPinnedAllocs[MemAlloc] = Kind; 332 break; 333 case TARGET_ALLOC_SHARED: 334 CUdeviceptr SharedPtr; 335 Err = cuMemAllocManaged(&SharedPtr, Size, CU_MEM_ATTACH_GLOBAL); 336 MemAlloc = (void *)SharedPtr; 337 if (!checkResult(Err, "Error returned from cuMemAllocManaged\n")) 338 return nullptr; 339 break; 340 } 341 342 return MemAlloc; 343 } 344 345 int free(void *TgtPtr) override { 346 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 347 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 348 return OFFLOAD_FAIL; 349 350 // Host pinned memory must be freed differently. 351 TargetAllocTy Kind = 352 (HostPinnedAllocs.find(TgtPtr) == HostPinnedAllocs.end()) 353 ? TARGET_ALLOC_DEFAULT 354 : TARGET_ALLOC_HOST; 355 switch (Kind) { 356 case TARGET_ALLOC_DEFAULT: 357 case TARGET_ALLOC_DEVICE: 358 case TARGET_ALLOC_SHARED: 359 Err = cuMemFree((CUdeviceptr)TgtPtr); 360 if (!checkResult(Err, "Error returned from cuMemFree\n")) 361 return OFFLOAD_FAIL; 362 break; 363 case TARGET_ALLOC_HOST: 364 Err = cuMemFreeHost(TgtPtr); 365 if (!checkResult(Err, "Error returned from cuMemFreeHost\n")) 366 return OFFLOAD_FAIL; 367 break; 368 } 369 370 return OFFLOAD_SUCCESS; 371 } 372 }; 373 374 /// A vector of device allocators 375 std::vector<CUDADeviceAllocatorTy> DeviceAllocators; 376 377 /// A vector of memory managers. Since the memory manager is non-copyable and 378 // non-removable, we wrap them into std::unique_ptr. 379 std::vector<std::unique_ptr<MemoryManagerTy>> MemoryManagers; 380 381 /// Whether use memory manager 382 bool UseMemoryManager = true; 383 384 // Record entry point associated with device 385 void addOffloadEntry(const int DeviceId, const __tgt_offload_entry entry) { 386 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 387 E.Entries.push_back(entry); 388 } 389 390 // Return a pointer to the entry associated with the pointer 391 const __tgt_offload_entry *getOffloadEntry(const int DeviceId, 392 const void *Addr) const { 393 for (const __tgt_offload_entry &Itr : 394 DeviceData[DeviceId].FuncGblEntries.back().Entries) 395 if (Itr.addr == Addr) 396 return &Itr; 397 398 return nullptr; 399 } 400 401 // Return the pointer to the target entries table 402 __tgt_target_table *getOffloadEntriesTable(const int DeviceId) { 403 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 404 405 if (E.Entries.empty()) 406 return nullptr; 407 408 // Update table info according to the entries and return the pointer 409 E.Table.EntriesBegin = E.Entries.data(); 410 E.Table.EntriesEnd = E.Entries.data() + E.Entries.size(); 411 412 return &E.Table; 413 } 414 415 // Clear entries table for a device 416 void clearOffloadEntriesTable(const int DeviceId) { 417 DeviceData[DeviceId].FuncGblEntries.emplace_back(); 418 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 419 E.Entries.clear(); 420 E.Table.EntriesBegin = E.Table.EntriesEnd = nullptr; 421 } 422 423 CUstream getStream(const int DeviceId, __tgt_async_info *AsyncInfo) const { 424 assert(AsyncInfo && "AsyncInfo is nullptr"); 425 426 if (!AsyncInfo->Queue) 427 AsyncInfo->Queue = StreamManager->getStream(DeviceId); 428 429 return reinterpret_cast<CUstream>(AsyncInfo->Queue); 430 } 431 432 public: 433 // This class should not be copied 434 DeviceRTLTy(const DeviceRTLTy &) = delete; 435 DeviceRTLTy(DeviceRTLTy &&) = delete; 436 437 DeviceRTLTy() 438 : NumberOfDevices(0), EnvNumTeams(-1), EnvTeamLimit(-1), 439 RequiresFlags(OMP_REQ_UNDEFINED) { 440 441 DP("Start initializing CUDA\n"); 442 443 CUresult Err = cuInit(0); 444 if (Err == CUDA_ERROR_INVALID_HANDLE) { 445 // Can't call cuGetErrorString if dlsym failed 446 DP("Failed to load CUDA shared library\n"); 447 return; 448 } 449 if (!checkResult(Err, "Error returned from cuInit\n")) { 450 return; 451 } 452 453 Err = cuDeviceGetCount(&NumberOfDevices); 454 if (!checkResult(Err, "Error returned from cuDeviceGetCount\n")) 455 return; 456 457 if (NumberOfDevices == 0) { 458 DP("There are no devices supporting CUDA.\n"); 459 return; 460 } 461 462 DeviceData.resize(NumberOfDevices); 463 464 // Get environment variables regarding teams 465 if (const char *EnvStr = getenv("OMP_TEAM_LIMIT")) { 466 // OMP_TEAM_LIMIT has been set 467 EnvTeamLimit = std::stoi(EnvStr); 468 DP("Parsed OMP_TEAM_LIMIT=%d\n", EnvTeamLimit); 469 } 470 if (const char *EnvStr = getenv("OMP_NUM_TEAMS")) { 471 // OMP_NUM_TEAMS has been set 472 EnvNumTeams = std::stoi(EnvStr); 473 DP("Parsed OMP_NUM_TEAMS=%d\n", EnvNumTeams); 474 } 475 476 StreamManager = 477 std::make_unique<StreamManagerTy>(NumberOfDevices, DeviceData); 478 479 for (int I = 0; I < NumberOfDevices; ++I) 480 DeviceAllocators.emplace_back(I, DeviceData); 481 482 // Get the size threshold from environment variable 483 std::pair<size_t, bool> Res = MemoryManagerTy::getSizeThresholdFromEnv(); 484 UseMemoryManager = Res.second; 485 size_t MemoryManagerThreshold = Res.first; 486 487 if (UseMemoryManager) 488 for (int I = 0; I < NumberOfDevices; ++I) 489 MemoryManagers.emplace_back(std::make_unique<MemoryManagerTy>( 490 DeviceAllocators[I], MemoryManagerThreshold)); 491 } 492 493 ~DeviceRTLTy() { 494 // We first destruct memory managers in case that its dependent data are 495 // destroyed before it. 496 for (auto &M : MemoryManagers) 497 M.release(); 498 499 StreamManager = nullptr; 500 501 for (CUmodule &M : Modules) 502 // Close module 503 if (M) 504 checkResult(cuModuleUnload(M), "Error returned from cuModuleUnload\n"); 505 506 for (DeviceDataTy &D : DeviceData) { 507 // Destroy context 508 if (D.Context) { 509 checkResult(cuCtxSetCurrent(D.Context), 510 "Error returned from cuCtxSetCurrent\n"); 511 CUdevice Device; 512 checkResult(cuCtxGetDevice(&Device), 513 "Error returned from cuCtxGetDevice\n"); 514 checkResult(cuDevicePrimaryCtxRelease(Device), 515 "Error returned from cuDevicePrimaryCtxRelease\n"); 516 } 517 } 518 } 519 520 // Check whether a given DeviceId is valid 521 bool isValidDeviceId(const int DeviceId) const { 522 return DeviceId >= 0 && DeviceId < NumberOfDevices; 523 } 524 525 int getNumOfDevices() const { return NumberOfDevices; } 526 527 void setRequiresFlag(const int64_t Flags) { this->RequiresFlags = Flags; } 528 529 int initDevice(const int DeviceId) { 530 CUdevice Device; 531 532 DP("Getting device %d\n", DeviceId); 533 CUresult Err = cuDeviceGet(&Device, DeviceId); 534 if (!checkResult(Err, "Error returned from cuDeviceGet\n")) 535 return OFFLOAD_FAIL; 536 537 // Query the current flags of the primary context and set its flags if 538 // it is inactive 539 unsigned int FormerPrimaryCtxFlags = 0; 540 int FormerPrimaryCtxIsActive = 0; 541 Err = cuDevicePrimaryCtxGetState(Device, &FormerPrimaryCtxFlags, 542 &FormerPrimaryCtxIsActive); 543 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxGetState\n")) 544 return OFFLOAD_FAIL; 545 546 if (FormerPrimaryCtxIsActive) { 547 DP("The primary context is active, no change to its flags\n"); 548 if ((FormerPrimaryCtxFlags & CU_CTX_SCHED_MASK) != 549 CU_CTX_SCHED_BLOCKING_SYNC) 550 DP("Warning the current flags are not CU_CTX_SCHED_BLOCKING_SYNC\n"); 551 } else { 552 DP("The primary context is inactive, set its flags to " 553 "CU_CTX_SCHED_BLOCKING_SYNC\n"); 554 Err = cuDevicePrimaryCtxSetFlags(Device, CU_CTX_SCHED_BLOCKING_SYNC); 555 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxSetFlags\n")) 556 return OFFLOAD_FAIL; 557 } 558 559 // Retain the per device primary context and save it to use whenever this 560 // device is selected. 561 Err = cuDevicePrimaryCtxRetain(&DeviceData[DeviceId].Context, Device); 562 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxRetain\n")) 563 return OFFLOAD_FAIL; 564 565 Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 566 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 567 return OFFLOAD_FAIL; 568 569 // Initialize stream pool 570 if (!StreamManager->initializeDeviceStreamPool(DeviceId)) 571 return OFFLOAD_FAIL; 572 573 // Query attributes to determine number of threads/block and blocks/grid. 574 int MaxGridDimX; 575 Err = cuDeviceGetAttribute(&MaxGridDimX, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X, 576 Device); 577 if (Err != CUDA_SUCCESS) { 578 DP("Error getting max grid dimension, use default value %d\n", 579 DeviceRTLTy::DefaultNumTeams); 580 DeviceData[DeviceId].BlocksPerGrid = DeviceRTLTy::DefaultNumTeams; 581 } else if (MaxGridDimX <= DeviceRTLTy::HardTeamLimit) { 582 DP("Using %d CUDA blocks per grid\n", MaxGridDimX); 583 DeviceData[DeviceId].BlocksPerGrid = MaxGridDimX; 584 } else { 585 DP("Max CUDA blocks per grid %d exceeds the hard team limit %d, capping " 586 "at the hard limit\n", 587 MaxGridDimX, DeviceRTLTy::HardTeamLimit); 588 DeviceData[DeviceId].BlocksPerGrid = DeviceRTLTy::HardTeamLimit; 589 } 590 591 // We are only exploiting threads along the x axis. 592 int MaxBlockDimX; 593 Err = cuDeviceGetAttribute(&MaxBlockDimX, 594 CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, Device); 595 if (Err != CUDA_SUCCESS) { 596 DP("Error getting max block dimension, use default value %d\n", 597 DeviceRTLTy::DefaultNumThreads); 598 DeviceData[DeviceId].ThreadsPerBlock = DeviceRTLTy::DefaultNumThreads; 599 } else if (MaxBlockDimX <= DeviceRTLTy::HardThreadLimit) { 600 DP("Using %d CUDA threads per block\n", MaxBlockDimX); 601 DeviceData[DeviceId].ThreadsPerBlock = MaxBlockDimX; 602 } else { 603 DP("Max CUDA threads per block %d exceeds the hard thread limit %d, " 604 "capping at the hard limit\n", 605 MaxBlockDimX, DeviceRTLTy::HardThreadLimit); 606 DeviceData[DeviceId].ThreadsPerBlock = DeviceRTLTy::HardThreadLimit; 607 } 608 609 // Get and set warp size 610 int WarpSize; 611 Err = 612 cuDeviceGetAttribute(&WarpSize, CU_DEVICE_ATTRIBUTE_WARP_SIZE, Device); 613 if (Err != CUDA_SUCCESS) { 614 DP("Error getting warp size, assume default value 32\n"); 615 DeviceData[DeviceId].WarpSize = 32; 616 } else { 617 DP("Using warp size %d\n", WarpSize); 618 DeviceData[DeviceId].WarpSize = WarpSize; 619 } 620 621 // Adjust teams to the env variables 622 if (EnvTeamLimit > 0 && DeviceData[DeviceId].BlocksPerGrid > EnvTeamLimit) { 623 DP("Capping max CUDA blocks per grid to OMP_TEAM_LIMIT=%d\n", 624 EnvTeamLimit); 625 DeviceData[DeviceId].BlocksPerGrid = EnvTeamLimit; 626 } 627 628 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 629 "Device supports up to %d CUDA blocks and %d threads with a " 630 "warp size of %d\n", 631 DeviceData[DeviceId].BlocksPerGrid, 632 DeviceData[DeviceId].ThreadsPerBlock, DeviceData[DeviceId].WarpSize); 633 634 // Set default number of teams 635 if (EnvNumTeams > 0) { 636 DP("Default number of teams set according to environment %d\n", 637 EnvNumTeams); 638 DeviceData[DeviceId].NumTeams = EnvNumTeams; 639 } else { 640 DeviceData[DeviceId].NumTeams = DeviceRTLTy::DefaultNumTeams; 641 DP("Default number of teams set according to library's default %d\n", 642 DeviceRTLTy::DefaultNumTeams); 643 } 644 645 if (DeviceData[DeviceId].NumTeams > DeviceData[DeviceId].BlocksPerGrid) { 646 DP("Default number of teams exceeds device limit, capping at %d\n", 647 DeviceData[DeviceId].BlocksPerGrid); 648 DeviceData[DeviceId].NumTeams = DeviceData[DeviceId].BlocksPerGrid; 649 } 650 651 // Set default number of threads 652 DeviceData[DeviceId].NumThreads = DeviceRTLTy::DefaultNumThreads; 653 DP("Default number of threads set according to library's default %d\n", 654 DeviceRTLTy::DefaultNumThreads); 655 if (DeviceData[DeviceId].NumThreads > 656 DeviceData[DeviceId].ThreadsPerBlock) { 657 DP("Default number of threads exceeds device limit, capping at %d\n", 658 DeviceData[DeviceId].ThreadsPerBlock); 659 DeviceData[DeviceId].NumTeams = DeviceData[DeviceId].ThreadsPerBlock; 660 } 661 662 return OFFLOAD_SUCCESS; 663 } 664 665 __tgt_target_table *loadBinary(const int DeviceId, 666 const __tgt_device_image *Image) { 667 // Set the context we are using 668 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 669 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 670 return nullptr; 671 672 // Clear the offload table as we are going to create a new one. 673 clearOffloadEntriesTable(DeviceId); 674 675 // Create the module and extract the function pointers. 676 CUmodule Module; 677 DP("Load data from image " DPxMOD "\n", DPxPTR(Image->ImageStart)); 678 Err = cuModuleLoadDataEx(&Module, Image->ImageStart, 0, nullptr, nullptr); 679 if (!checkResult(Err, "Error returned from cuModuleLoadDataEx\n")) 680 return nullptr; 681 682 DP("CUDA module successfully loaded!\n"); 683 684 Modules.push_back(Module); 685 686 // Find the symbols in the module by name. 687 const __tgt_offload_entry *HostBegin = Image->EntriesBegin; 688 const __tgt_offload_entry *HostEnd = Image->EntriesEnd; 689 690 std::list<KernelTy> &KernelsList = DeviceData[DeviceId].KernelsList; 691 for (const __tgt_offload_entry *E = HostBegin; E != HostEnd; ++E) { 692 if (!E->addr) { 693 // We return nullptr when something like this happens, the host should 694 // have always something in the address to uniquely identify the target 695 // region. 696 DP("Invalid binary: host entry '<null>' (size = %zd)...\n", E->size); 697 return nullptr; 698 } 699 700 if (E->size) { 701 __tgt_offload_entry Entry = *E; 702 CUdeviceptr CUPtr; 703 size_t CUSize; 704 Err = cuModuleGetGlobal(&CUPtr, &CUSize, Module, E->name); 705 // We keep this style here because we need the name 706 if (Err != CUDA_SUCCESS) { 707 REPORT("Loading global '%s' Failed\n", E->name); 708 CUDA_ERR_STRING(Err); 709 return nullptr; 710 } 711 712 if (CUSize != E->size) { 713 DP("Loading global '%s' - size mismatch (%zd != %zd)\n", E->name, 714 CUSize, E->size); 715 return nullptr; 716 } 717 718 DP("Entry point " DPxMOD " maps to global %s (" DPxMOD ")\n", 719 DPxPTR(E - HostBegin), E->name, DPxPTR(CUPtr)); 720 721 Entry.addr = (void *)(CUPtr); 722 723 // Note: In the current implementation declare target variables 724 // can either be link or to. This means that once unified 725 // memory is activated via the requires directive, the variable 726 // can be used directly from the host in both cases. 727 // TODO: when variables types other than to or link are added, 728 // the below condition should be changed to explicitly 729 // check for to and link variables types: 730 // (RequiresFlags & OMP_REQ_UNIFIED_SHARED_MEMORY && (e->flags & 731 // OMP_DECLARE_TARGET_LINK || e->flags == OMP_DECLARE_TARGET_TO)) 732 if (RequiresFlags & OMP_REQ_UNIFIED_SHARED_MEMORY) { 733 // If unified memory is present any target link or to variables 734 // can access host addresses directly. There is no longer a 735 // need for device copies. 736 cuMemcpyHtoD(CUPtr, E->addr, sizeof(void *)); 737 DP("Copy linked variable host address (" DPxMOD 738 ") to device address (" DPxMOD ")\n", 739 DPxPTR(*((void **)E->addr)), DPxPTR(CUPtr)); 740 } 741 742 addOffloadEntry(DeviceId, Entry); 743 744 continue; 745 } 746 747 CUfunction Func; 748 Err = cuModuleGetFunction(&Func, Module, E->name); 749 // We keep this style here because we need the name 750 if (Err != CUDA_SUCCESS) { 751 REPORT("Loading '%s' Failed\n", E->name); 752 CUDA_ERR_STRING(Err); 753 return nullptr; 754 } 755 756 DP("Entry point " DPxMOD " maps to %s (" DPxMOD ")\n", 757 DPxPTR(E - HostBegin), E->name, DPxPTR(Func)); 758 759 // default value GENERIC (in case symbol is missing from cubin file) 760 int8_t ExecModeVal = ExecutionModeType::GENERIC; 761 std::string ExecModeNameStr(E->name); 762 ExecModeNameStr += "_exec_mode"; 763 const char *ExecModeName = ExecModeNameStr.c_str(); 764 765 CUdeviceptr ExecModePtr; 766 size_t CUSize; 767 Err = cuModuleGetGlobal(&ExecModePtr, &CUSize, Module, ExecModeName); 768 if (Err == CUDA_SUCCESS) { 769 if (CUSize != sizeof(int8_t)) { 770 DP("Loading global exec_mode '%s' - size mismatch (%zd != %zd)\n", 771 ExecModeName, CUSize, sizeof(int8_t)); 772 return nullptr; 773 } 774 775 Err = cuMemcpyDtoH(&ExecModeVal, ExecModePtr, CUSize); 776 if (Err != CUDA_SUCCESS) { 777 REPORT("Error when copying data from device to host. Pointers: " 778 "host = " DPxMOD ", device = " DPxMOD ", size = %zd\n", 779 DPxPTR(&ExecModeVal), DPxPTR(ExecModePtr), CUSize); 780 CUDA_ERR_STRING(Err); 781 return nullptr; 782 } 783 784 if (ExecModeVal < 0 || ExecModeVal > 1) { 785 DP("Error wrong exec_mode value specified in cubin file: %d\n", 786 ExecModeVal); 787 return nullptr; 788 } 789 } else { 790 REPORT("Loading global exec_mode '%s' - symbol missing, using default " 791 "value GENERIC (1)\n", 792 ExecModeName); 793 CUDA_ERR_STRING(Err); 794 } 795 796 KernelsList.emplace_back(Func, ExecModeVal); 797 798 __tgt_offload_entry Entry = *E; 799 Entry.addr = &KernelsList.back(); 800 addOffloadEntry(DeviceId, Entry); 801 } 802 803 // send device environment data to the device 804 { 805 omptarget_device_environmentTy DeviceEnv{0}; 806 807 #ifdef OMPTARGET_DEBUG 808 if (const char *EnvStr = getenv("LIBOMPTARGET_DEVICE_RTL_DEBUG")) 809 DeviceEnv.debug_level = std::stoi(EnvStr); 810 #endif 811 812 const char *DeviceEnvName = "omptarget_device_environment"; 813 CUdeviceptr DeviceEnvPtr; 814 size_t CUSize; 815 816 Err = cuModuleGetGlobal(&DeviceEnvPtr, &CUSize, Module, DeviceEnvName); 817 if (Err == CUDA_SUCCESS) { 818 if (CUSize != sizeof(DeviceEnv)) { 819 REPORT( 820 "Global device_environment '%s' - size mismatch (%zu != %zu)\n", 821 DeviceEnvName, CUSize, sizeof(int32_t)); 822 CUDA_ERR_STRING(Err); 823 return nullptr; 824 } 825 826 Err = cuMemcpyHtoD(DeviceEnvPtr, &DeviceEnv, CUSize); 827 if (Err != CUDA_SUCCESS) { 828 REPORT("Error when copying data from host to device. Pointers: " 829 "host = " DPxMOD ", device = " DPxMOD ", size = %zu\n", 830 DPxPTR(&DeviceEnv), DPxPTR(DeviceEnvPtr), CUSize); 831 CUDA_ERR_STRING(Err); 832 return nullptr; 833 } 834 835 DP("Sending global device environment data %zu bytes\n", CUSize); 836 } else { 837 DP("Finding global device environment '%s' - symbol missing.\n", 838 DeviceEnvName); 839 DP("Continue, considering this is a device RTL which does not accept " 840 "environment setting.\n"); 841 } 842 } 843 844 return getOffloadEntriesTable(DeviceId); 845 } 846 847 void *dataAlloc(const int DeviceId, const int64_t Size, 848 const TargetAllocTy Kind) { 849 switch (Kind) { 850 case TARGET_ALLOC_DEFAULT: 851 case TARGET_ALLOC_DEVICE: 852 if (UseMemoryManager) 853 return MemoryManagers[DeviceId]->allocate(Size, nullptr); 854 else 855 return DeviceAllocators[DeviceId].allocate(Size, nullptr, Kind); 856 case TARGET_ALLOC_HOST: 857 case TARGET_ALLOC_SHARED: 858 return DeviceAllocators[DeviceId].allocate(Size, nullptr, Kind); 859 } 860 861 REPORT("Invalid target data allocation kind or requested allocator not " 862 "implemented yet\n"); 863 864 return nullptr; 865 } 866 867 int dataSubmit(const int DeviceId, const void *TgtPtr, const void *HstPtr, 868 const int64_t Size, __tgt_async_info *AsyncInfo) const { 869 assert(AsyncInfo && "AsyncInfo is nullptr"); 870 871 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 872 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 873 return OFFLOAD_FAIL; 874 875 CUstream Stream = getStream(DeviceId, AsyncInfo); 876 877 Err = cuMemcpyHtoDAsync((CUdeviceptr)TgtPtr, HstPtr, Size, Stream); 878 if (Err != CUDA_SUCCESS) { 879 DP("Error when copying data from host to device. Pointers: host " 880 "= " DPxMOD ", device = " DPxMOD ", size = %" PRId64 "\n", 881 DPxPTR(HstPtr), DPxPTR(TgtPtr), Size); 882 CUDA_ERR_STRING(Err); 883 return OFFLOAD_FAIL; 884 } 885 886 return OFFLOAD_SUCCESS; 887 } 888 889 int dataRetrieve(const int DeviceId, void *HstPtr, const void *TgtPtr, 890 const int64_t Size, __tgt_async_info *AsyncInfo) const { 891 assert(AsyncInfo && "AsyncInfo is nullptr"); 892 893 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 894 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 895 return OFFLOAD_FAIL; 896 897 CUstream Stream = getStream(DeviceId, AsyncInfo); 898 899 Err = cuMemcpyDtoHAsync(HstPtr, (CUdeviceptr)TgtPtr, Size, Stream); 900 if (Err != CUDA_SUCCESS) { 901 DP("Error when copying data from device to host. Pointers: host " 902 "= " DPxMOD ", device = " DPxMOD ", size = %" PRId64 "\n", 903 DPxPTR(HstPtr), DPxPTR(TgtPtr), Size); 904 CUDA_ERR_STRING(Err); 905 return OFFLOAD_FAIL; 906 } 907 908 return OFFLOAD_SUCCESS; 909 } 910 911 int dataExchange(int SrcDevId, const void *SrcPtr, int DstDevId, void *DstPtr, 912 int64_t Size, __tgt_async_info *AsyncInfo) const { 913 assert(AsyncInfo && "AsyncInfo is nullptr"); 914 915 CUresult Err = cuCtxSetCurrent(DeviceData[SrcDevId].Context); 916 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 917 return OFFLOAD_FAIL; 918 919 CUstream Stream = getStream(SrcDevId, AsyncInfo); 920 921 // If they are two devices, we try peer to peer copy first 922 if (SrcDevId != DstDevId) { 923 int CanAccessPeer = 0; 924 Err = cuDeviceCanAccessPeer(&CanAccessPeer, SrcDevId, DstDevId); 925 if (Err != CUDA_SUCCESS) { 926 REPORT("Error returned from cuDeviceCanAccessPeer. src = %" PRId32 927 ", dst = %" PRId32 "\n", 928 SrcDevId, DstDevId); 929 CUDA_ERR_STRING(Err); 930 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 931 } 932 933 if (!CanAccessPeer) { 934 DP("P2P memcpy not supported so fall back to D2D memcpy"); 935 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 936 } 937 938 Err = cuCtxEnablePeerAccess(DeviceData[DstDevId].Context, 0); 939 if (Err != CUDA_SUCCESS) { 940 REPORT("Error returned from cuCtxEnablePeerAccess. src = %" PRId32 941 ", dst = %" PRId32 "\n", 942 SrcDevId, DstDevId); 943 CUDA_ERR_STRING(Err); 944 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 945 } 946 947 Err = cuMemcpyPeerAsync((CUdeviceptr)DstPtr, DeviceData[DstDevId].Context, 948 (CUdeviceptr)SrcPtr, DeviceData[SrcDevId].Context, 949 Size, Stream); 950 if (Err == CUDA_SUCCESS) 951 return OFFLOAD_SUCCESS; 952 953 DP("Error returned from cuMemcpyPeerAsync. src_ptr = " DPxMOD 954 ", src_id =%" PRId32 ", dst_ptr = " DPxMOD ", dst_id =%" PRId32 "\n", 955 DPxPTR(SrcPtr), SrcDevId, DPxPTR(DstPtr), DstDevId); 956 CUDA_ERR_STRING(Err); 957 } 958 959 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 960 } 961 962 int dataDelete(const int DeviceId, void *TgtPtr) { 963 if (UseMemoryManager) 964 return MemoryManagers[DeviceId]->free(TgtPtr); 965 966 return DeviceAllocators[DeviceId].free(TgtPtr); 967 } 968 969 int runTargetTeamRegion(const int DeviceId, void *TgtEntryPtr, void **TgtArgs, 970 ptrdiff_t *TgtOffsets, const int ArgNum, 971 const int TeamNum, const int ThreadLimit, 972 const unsigned int LoopTripCount, 973 __tgt_async_info *AsyncInfo) const { 974 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 975 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 976 return OFFLOAD_FAIL; 977 978 // All args are references. 979 std::vector<void *> Args(ArgNum); 980 std::vector<void *> Ptrs(ArgNum); 981 982 for (int I = 0; I < ArgNum; ++I) { 983 Ptrs[I] = (void *)((intptr_t)TgtArgs[I] + TgtOffsets[I]); 984 Args[I] = &Ptrs[I]; 985 } 986 987 KernelTy *KernelInfo = reinterpret_cast<KernelTy *>(TgtEntryPtr); 988 989 int CudaThreadsPerBlock; 990 if (ThreadLimit > 0) { 991 DP("Setting CUDA threads per block to requested %d\n", ThreadLimit); 992 CudaThreadsPerBlock = ThreadLimit; 993 // Add master warp if necessary 994 if (KernelInfo->ExecutionMode == GENERIC) { 995 DP("Adding master warp: +%d threads\n", DeviceData[DeviceId].WarpSize); 996 CudaThreadsPerBlock += DeviceData[DeviceId].WarpSize; 997 } 998 } else { 999 DP("Setting CUDA threads per block to default %d\n", 1000 DeviceData[DeviceId].NumThreads); 1001 CudaThreadsPerBlock = DeviceData[DeviceId].NumThreads; 1002 } 1003 1004 if (CudaThreadsPerBlock > DeviceData[DeviceId].ThreadsPerBlock) { 1005 DP("Threads per block capped at device limit %d\n", 1006 DeviceData[DeviceId].ThreadsPerBlock); 1007 CudaThreadsPerBlock = DeviceData[DeviceId].ThreadsPerBlock; 1008 } 1009 1010 if (!KernelInfo->MaxThreadsPerBlock) { 1011 Err = cuFuncGetAttribute(&KernelInfo->MaxThreadsPerBlock, 1012 CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, 1013 KernelInfo->Func); 1014 if (!checkResult(Err, "Error returned from cuFuncGetAttribute\n")) 1015 return OFFLOAD_FAIL; 1016 } 1017 1018 if (KernelInfo->MaxThreadsPerBlock < CudaThreadsPerBlock) { 1019 DP("Threads per block capped at kernel limit %d\n", 1020 KernelInfo->MaxThreadsPerBlock); 1021 CudaThreadsPerBlock = KernelInfo->MaxThreadsPerBlock; 1022 } 1023 1024 unsigned int CudaBlocksPerGrid; 1025 if (TeamNum <= 0) { 1026 if (LoopTripCount > 0 && EnvNumTeams < 0) { 1027 if (KernelInfo->ExecutionMode == SPMD) { 1028 // We have a combined construct, i.e. `target teams distribute 1029 // parallel for [simd]`. We launch so many teams so that each thread 1030 // will execute one iteration of the loop. round up to the nearest 1031 // integer 1032 CudaBlocksPerGrid = ((LoopTripCount - 1) / CudaThreadsPerBlock) + 1; 1033 } else { 1034 // If we reach this point, then we have a non-combined construct, i.e. 1035 // `teams distribute` with a nested `parallel for` and each team is 1036 // assigned one iteration of the `distribute` loop. E.g.: 1037 // 1038 // #pragma omp target teams distribute 1039 // for(...loop_tripcount...) { 1040 // #pragma omp parallel for 1041 // for(...) {} 1042 // } 1043 // 1044 // Threads within a team will execute the iterations of the `parallel` 1045 // loop. 1046 CudaBlocksPerGrid = LoopTripCount; 1047 } 1048 DP("Using %d teams due to loop trip count %" PRIu32 1049 " and number of threads per block %d\n", 1050 CudaBlocksPerGrid, LoopTripCount, CudaThreadsPerBlock); 1051 } else { 1052 DP("Using default number of teams %d\n", DeviceData[DeviceId].NumTeams); 1053 CudaBlocksPerGrid = DeviceData[DeviceId].NumTeams; 1054 } 1055 } else if (TeamNum > DeviceData[DeviceId].BlocksPerGrid) { 1056 DP("Capping number of teams to team limit %d\n", 1057 DeviceData[DeviceId].BlocksPerGrid); 1058 CudaBlocksPerGrid = DeviceData[DeviceId].BlocksPerGrid; 1059 } else { 1060 DP("Using requested number of teams %d\n", TeamNum); 1061 CudaBlocksPerGrid = TeamNum; 1062 } 1063 1064 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 1065 "Launching kernel %s with %d blocks and %d threads in %s " 1066 "mode\n", 1067 (getOffloadEntry(DeviceId, TgtEntryPtr)) 1068 ? getOffloadEntry(DeviceId, TgtEntryPtr)->name 1069 : "(null)", 1070 CudaBlocksPerGrid, CudaThreadsPerBlock, 1071 (KernelInfo->ExecutionMode == SPMD) ? "SPMD" : "Generic"); 1072 1073 CUstream Stream = getStream(DeviceId, AsyncInfo); 1074 Err = cuLaunchKernel(KernelInfo->Func, CudaBlocksPerGrid, /* gridDimY */ 1, 1075 /* gridDimZ */ 1, CudaThreadsPerBlock, 1076 /* blockDimY */ 1, /* blockDimZ */ 1, 1077 /* sharedMemBytes */ 0, Stream, &Args[0], nullptr); 1078 if (!checkResult(Err, "Error returned from cuLaunchKernel\n")) 1079 return OFFLOAD_FAIL; 1080 1081 DP("Launch of entry point at " DPxMOD " successful!\n", 1082 DPxPTR(TgtEntryPtr)); 1083 1084 return OFFLOAD_SUCCESS; 1085 } 1086 1087 int synchronize(const int DeviceId, __tgt_async_info *AsyncInfo) const { 1088 CUstream Stream = reinterpret_cast<CUstream>(AsyncInfo->Queue); 1089 CUresult Err = cuStreamSynchronize(Stream); 1090 1091 // Once the stream is synchronized, return it to stream pool and reset 1092 // AsyncInfo. This is to make sure the synchronization only works for its 1093 // own tasks. 1094 StreamManager->returnStream(DeviceId, 1095 reinterpret_cast<CUstream>(AsyncInfo->Queue)); 1096 AsyncInfo->Queue = nullptr; 1097 1098 if (Err != CUDA_SUCCESS) { 1099 DP("Error when synchronizing stream. stream = " DPxMOD 1100 ", async info ptr = " DPxMOD "\n", 1101 DPxPTR(Stream), DPxPTR(AsyncInfo)); 1102 CUDA_ERR_STRING(Err); 1103 } 1104 return (Err == CUDA_SUCCESS) ? OFFLOAD_SUCCESS : OFFLOAD_FAIL; 1105 } 1106 }; 1107 1108 DeviceRTLTy DeviceRTL; 1109 } // namespace 1110 1111 // Exposed library API function 1112 #ifdef __cplusplus 1113 extern "C" { 1114 #endif 1115 1116 int32_t __tgt_rtl_is_valid_binary(__tgt_device_image *image) { 1117 return elf_check_machine(image, /* EM_CUDA */ 190); 1118 } 1119 1120 int32_t __tgt_rtl_number_of_devices() { return DeviceRTL.getNumOfDevices(); } 1121 1122 int64_t __tgt_rtl_init_requires(int64_t RequiresFlags) { 1123 DP("Init requires flags to %" PRId64 "\n", RequiresFlags); 1124 DeviceRTL.setRequiresFlag(RequiresFlags); 1125 return RequiresFlags; 1126 } 1127 1128 int32_t __tgt_rtl_is_data_exchangable(int32_t src_dev_id, int dst_dev_id) { 1129 if (DeviceRTL.isValidDeviceId(src_dev_id) && 1130 DeviceRTL.isValidDeviceId(dst_dev_id)) 1131 return 1; 1132 1133 return 0; 1134 } 1135 1136 int32_t __tgt_rtl_init_device(int32_t device_id) { 1137 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1138 1139 return DeviceRTL.initDevice(device_id); 1140 } 1141 1142 __tgt_target_table *__tgt_rtl_load_binary(int32_t device_id, 1143 __tgt_device_image *image) { 1144 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1145 1146 return DeviceRTL.loadBinary(device_id, image); 1147 } 1148 1149 void *__tgt_rtl_data_alloc(int32_t device_id, int64_t size, void *, 1150 int32_t kind) { 1151 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1152 1153 return DeviceRTL.dataAlloc(device_id, size, (TargetAllocTy)kind); 1154 } 1155 1156 int32_t __tgt_rtl_data_submit(int32_t device_id, void *tgt_ptr, void *hst_ptr, 1157 int64_t size) { 1158 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1159 1160 __tgt_async_info AsyncInfo; 1161 const int32_t rc = __tgt_rtl_data_submit_async(device_id, tgt_ptr, hst_ptr, 1162 size, &AsyncInfo); 1163 if (rc != OFFLOAD_SUCCESS) 1164 return OFFLOAD_FAIL; 1165 1166 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1167 } 1168 1169 int32_t __tgt_rtl_data_submit_async(int32_t device_id, void *tgt_ptr, 1170 void *hst_ptr, int64_t size, 1171 __tgt_async_info *async_info_ptr) { 1172 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1173 assert(async_info_ptr && "async_info_ptr is nullptr"); 1174 1175 return DeviceRTL.dataSubmit(device_id, tgt_ptr, hst_ptr, size, 1176 async_info_ptr); 1177 } 1178 1179 int32_t __tgt_rtl_data_retrieve(int32_t device_id, void *hst_ptr, void *tgt_ptr, 1180 int64_t size) { 1181 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1182 1183 __tgt_async_info AsyncInfo; 1184 const int32_t rc = __tgt_rtl_data_retrieve_async(device_id, hst_ptr, tgt_ptr, 1185 size, &AsyncInfo); 1186 if (rc != OFFLOAD_SUCCESS) 1187 return OFFLOAD_FAIL; 1188 1189 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1190 } 1191 1192 int32_t __tgt_rtl_data_retrieve_async(int32_t device_id, void *hst_ptr, 1193 void *tgt_ptr, int64_t size, 1194 __tgt_async_info *async_info_ptr) { 1195 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1196 assert(async_info_ptr && "async_info_ptr is nullptr"); 1197 1198 return DeviceRTL.dataRetrieve(device_id, hst_ptr, tgt_ptr, size, 1199 async_info_ptr); 1200 } 1201 1202 int32_t __tgt_rtl_data_exchange_async(int32_t src_dev_id, void *src_ptr, 1203 int dst_dev_id, void *dst_ptr, 1204 int64_t size, 1205 __tgt_async_info *AsyncInfo) { 1206 assert(DeviceRTL.isValidDeviceId(src_dev_id) && "src_dev_id is invalid"); 1207 assert(DeviceRTL.isValidDeviceId(dst_dev_id) && "dst_dev_id is invalid"); 1208 assert(AsyncInfo && "AsyncInfo is nullptr"); 1209 1210 return DeviceRTL.dataExchange(src_dev_id, src_ptr, dst_dev_id, dst_ptr, size, 1211 AsyncInfo); 1212 } 1213 1214 int32_t __tgt_rtl_data_exchange(int32_t src_dev_id, void *src_ptr, 1215 int32_t dst_dev_id, void *dst_ptr, 1216 int64_t size) { 1217 assert(DeviceRTL.isValidDeviceId(src_dev_id) && "src_dev_id is invalid"); 1218 assert(DeviceRTL.isValidDeviceId(dst_dev_id) && "dst_dev_id is invalid"); 1219 1220 __tgt_async_info AsyncInfo; 1221 const int32_t rc = __tgt_rtl_data_exchange_async( 1222 src_dev_id, src_ptr, dst_dev_id, dst_ptr, size, &AsyncInfo); 1223 if (rc != OFFLOAD_SUCCESS) 1224 return OFFLOAD_FAIL; 1225 1226 return __tgt_rtl_synchronize(src_dev_id, &AsyncInfo); 1227 } 1228 1229 int32_t __tgt_rtl_data_delete(int32_t device_id, void *tgt_ptr) { 1230 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1231 1232 return DeviceRTL.dataDelete(device_id, tgt_ptr); 1233 } 1234 1235 int32_t __tgt_rtl_run_target_team_region(int32_t device_id, void *tgt_entry_ptr, 1236 void **tgt_args, 1237 ptrdiff_t *tgt_offsets, 1238 int32_t arg_num, int32_t team_num, 1239 int32_t thread_limit, 1240 uint64_t loop_tripcount) { 1241 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1242 1243 __tgt_async_info AsyncInfo; 1244 const int32_t rc = __tgt_rtl_run_target_team_region_async( 1245 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, team_num, 1246 thread_limit, loop_tripcount, &AsyncInfo); 1247 if (rc != OFFLOAD_SUCCESS) 1248 return OFFLOAD_FAIL; 1249 1250 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1251 } 1252 1253 int32_t __tgt_rtl_run_target_team_region_async( 1254 int32_t device_id, void *tgt_entry_ptr, void **tgt_args, 1255 ptrdiff_t *tgt_offsets, int32_t arg_num, int32_t team_num, 1256 int32_t thread_limit, uint64_t loop_tripcount, 1257 __tgt_async_info *async_info_ptr) { 1258 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1259 1260 return DeviceRTL.runTargetTeamRegion( 1261 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, team_num, 1262 thread_limit, loop_tripcount, async_info_ptr); 1263 } 1264 1265 int32_t __tgt_rtl_run_target_region(int32_t device_id, void *tgt_entry_ptr, 1266 void **tgt_args, ptrdiff_t *tgt_offsets, 1267 int32_t arg_num) { 1268 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1269 1270 __tgt_async_info AsyncInfo; 1271 const int32_t rc = __tgt_rtl_run_target_region_async( 1272 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, &AsyncInfo); 1273 if (rc != OFFLOAD_SUCCESS) 1274 return OFFLOAD_FAIL; 1275 1276 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1277 } 1278 1279 int32_t __tgt_rtl_run_target_region_async(int32_t device_id, 1280 void *tgt_entry_ptr, void **tgt_args, 1281 ptrdiff_t *tgt_offsets, 1282 int32_t arg_num, 1283 __tgt_async_info *async_info_ptr) { 1284 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1285 1286 return __tgt_rtl_run_target_team_region_async( 1287 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, 1288 /* team num*/ 1, /* thread_limit */ 1, /* loop_tripcount */ 0, 1289 async_info_ptr); 1290 } 1291 1292 int32_t __tgt_rtl_synchronize(int32_t device_id, 1293 __tgt_async_info *async_info_ptr) { 1294 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1295 assert(async_info_ptr && "async_info_ptr is nullptr"); 1296 assert(async_info_ptr->Queue && "async_info_ptr->Queue is nullptr"); 1297 1298 return DeviceRTL.synchronize(device_id, async_info_ptr); 1299 } 1300 1301 void __tgt_rtl_set_info_flag(uint32_t NewInfoLevel) { 1302 std::atomic<uint32_t> &InfoLevel = getInfoLevelInternal(); 1303 InfoLevel.store(NewInfoLevel); 1304 } 1305 1306 #ifdef __cplusplus 1307 } 1308 #endif 1309