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 "DeviceEnvironment.h" 25 #include "omptargetplugin.h" 26 27 #define TARGET_NAME CUDA 28 #define DEBUG_PREFIX "Target " GETNAME(TARGET_NAME) " RTL" 29 30 #include "MemoryManager.h" 31 32 #include "llvm/Frontend/OpenMP/OMPConstants.h" 33 34 // Utility for retrieving and printing CUDA error string. 35 #ifdef OMPTARGET_DEBUG 36 #define CUDA_ERR_STRING(err) \ 37 do { \ 38 if (getDebugLevel() > 0) { \ 39 const char *errStr = nullptr; \ 40 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 41 if (errStr_status == CUDA_ERROR_INVALID_VALUE) \ 42 REPORT("Unrecognized CUDA error code: %d\n", err); \ 43 else if (errStr_status == CUDA_SUCCESS) \ 44 REPORT("CUDA error is: %s\n", errStr); \ 45 else { \ 46 REPORT("Unresolved CUDA error code: %d\n", err); \ 47 REPORT("Unsuccessful cuGetErrorString return status: %d\n", \ 48 errStr_status); \ 49 } \ 50 } else { \ 51 const char *errStr = nullptr; \ 52 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 53 if (errStr_status == CUDA_SUCCESS) \ 54 REPORT("%s \n", errStr); \ 55 } \ 56 } while (false) 57 #else // OMPTARGET_DEBUG 58 #define CUDA_ERR_STRING(err) \ 59 do { \ 60 const char *errStr = nullptr; \ 61 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 62 if (errStr_status == CUDA_SUCCESS) \ 63 REPORT("%s \n", errStr); \ 64 } while (false) 65 #endif // OMPTARGET_DEBUG 66 67 #define BOOL2TEXT(b) ((b) ? "Yes" : "No") 68 69 #include "elf_common.h" 70 71 /// Keep entries table per device. 72 struct FuncOrGblEntryTy { 73 __tgt_target_table Table; 74 std::vector<__tgt_offload_entry> Entries; 75 }; 76 77 /// Use a single entity to encode a kernel and a set of flags. 78 struct KernelTy { 79 CUfunction Func; 80 81 // execution mode of kernel 82 llvm::omp::OMPTgtExecModeFlags ExecutionMode; 83 84 /// Maximal number of threads per block for this kernel. 85 int MaxThreadsPerBlock = 0; 86 87 KernelTy(CUfunction _Func, llvm::omp::OMPTgtExecModeFlags _ExecutionMode) 88 : Func(_Func), ExecutionMode(_ExecutionMode) {} 89 }; 90 91 namespace { 92 bool checkResult(CUresult Err, const char *ErrMsg) { 93 if (Err == CUDA_SUCCESS) 94 return true; 95 96 REPORT("%s", ErrMsg); 97 CUDA_ERR_STRING(Err); 98 return false; 99 } 100 101 int memcpyDtoD(const void *SrcPtr, void *DstPtr, int64_t Size, 102 CUstream Stream) { 103 CUresult Err = 104 cuMemcpyDtoDAsync((CUdeviceptr)DstPtr, (CUdeviceptr)SrcPtr, Size, Stream); 105 106 if (Err != CUDA_SUCCESS) { 107 DP("Error when copying data from device to device. Pointers: src " 108 "= " DPxMOD ", dst = " DPxMOD ", size = %" PRId64 "\n", 109 DPxPTR(SrcPtr), DPxPTR(DstPtr), Size); 110 CUDA_ERR_STRING(Err); 111 return OFFLOAD_FAIL; 112 } 113 114 return OFFLOAD_SUCCESS; 115 } 116 117 int recordEvent(void *EventPtr, __tgt_async_info *AsyncInfo) { 118 CUstream Stream = reinterpret_cast<CUstream>(AsyncInfo->Queue); 119 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 120 121 CUresult Err = cuEventRecord(Event, Stream); 122 if (Err != CUDA_SUCCESS) { 123 DP("Error when recording event. stream = " DPxMOD ", event = " DPxMOD "\n", 124 DPxPTR(Stream), DPxPTR(Event)); 125 CUDA_ERR_STRING(Err); 126 return OFFLOAD_FAIL; 127 } 128 129 return OFFLOAD_SUCCESS; 130 } 131 132 int syncEvent(void *EventPtr) { 133 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 134 135 CUresult Err = cuEventSynchronize(Event); 136 if (Err != CUDA_SUCCESS) { 137 DP("Error when syncing event = " DPxMOD "\n", DPxPTR(Event)); 138 CUDA_ERR_STRING(Err); 139 return OFFLOAD_FAIL; 140 } 141 142 return OFFLOAD_SUCCESS; 143 } 144 145 // Structure contains per-device data 146 struct DeviceDataTy { 147 /// List that contains all the kernels. 148 std::list<KernelTy> KernelsList; 149 150 std::list<FuncOrGblEntryTy> FuncGblEntries; 151 152 CUcontext Context = nullptr; 153 // Device properties 154 int ThreadsPerBlock = 0; 155 int BlocksPerGrid = 0; 156 int WarpSize = 0; 157 // OpenMP properties 158 int NumTeams = 0; 159 int NumThreads = 0; 160 }; 161 162 /// Resource allocator where \p T is the resource type. 163 /// Functions \p create and \p destroy return OFFLOAD_SUCCESS and OFFLOAD_FAIL 164 /// accordingly. The implementation should not raise any exception. 165 template <typename T> class AllocatorTy { 166 public: 167 /// Create a resource and assign to R. 168 int create(T &R) noexcept; 169 /// Destroy the resource. 170 int destroy(T) noexcept; 171 }; 172 173 /// Allocator for CUstream. 174 template <> class AllocatorTy<CUstream> { 175 CUcontext Context; 176 177 public: 178 AllocatorTy(CUcontext C) noexcept : Context(C) {} 179 180 /// See AllocatorTy<T>::create. 181 int create(CUstream &Stream) noexcept { 182 if (!checkResult(cuCtxSetCurrent(Context), 183 "Error returned from cuCtxSetCurrent\n")) 184 return OFFLOAD_FAIL; 185 186 if (!checkResult(cuStreamCreate(&Stream, CU_STREAM_NON_BLOCKING), 187 "Error returned from cuStreamCreate\n")) 188 return OFFLOAD_FAIL; 189 190 return OFFLOAD_SUCCESS; 191 } 192 193 /// See AllocatorTy<T>::destroy. 194 int destroy(CUstream Stream) noexcept { 195 if (!checkResult(cuCtxSetCurrent(Context), 196 "Error returned from cuCtxSetCurrent\n")) 197 return OFFLOAD_FAIL; 198 if (!checkResult(cuStreamDestroy(Stream), 199 "Error returned from cuStreamDestroy\n")) 200 return OFFLOAD_FAIL; 201 202 return OFFLOAD_SUCCESS; 203 } 204 }; 205 206 /// Allocator for CUevent. 207 template <> class AllocatorTy<CUevent> { 208 public: 209 /// See AllocatorTy<T>::create. 210 int create(CUevent &Event) noexcept { 211 if (!checkResult(cuEventCreate(&Event, CU_EVENT_DEFAULT), 212 "Error returned from cuEventCreate\n")) 213 return OFFLOAD_FAIL; 214 215 return OFFLOAD_SUCCESS; 216 } 217 218 /// See AllocatorTy<T>::destroy. 219 int destroy(CUevent Event) noexcept { 220 if (!checkResult(cuEventDestroy(Event), 221 "Error returned from cuEventDestroy\n")) 222 return OFFLOAD_FAIL; 223 224 return OFFLOAD_SUCCESS; 225 } 226 }; 227 228 /// A generic pool of resources where \p T is the resource type. 229 /// \p T should be copyable as the object is stored in \p std::vector . 230 template <typename T> class ResourcePoolTy { 231 /// Index of the next available resource. 232 size_t Next = 0; 233 /// Mutex to guard the pool. 234 std::mutex Mutex; 235 /// Pool of resources. 236 std::vector<T> Resources; 237 /// A reference to the corresponding allocator. 238 AllocatorTy<T> Allocator; 239 240 /// If `Resources` is used up, we will fill in more resources. It assumes that 241 /// the new size `Size` should be always larger than the current size. 242 bool resize(size_t Size) { 243 auto CurSize = Resources.size(); 244 assert(Size > CurSize && "Unexpected smaller size"); 245 Resources.reserve(Size); 246 for (auto I = CurSize; I < Size; ++I) { 247 T NewItem; 248 int Ret = Allocator.create(NewItem); 249 if (Ret != OFFLOAD_SUCCESS) 250 return false; 251 Resources.push_back(NewItem); 252 } 253 return true; 254 } 255 256 public: 257 ResourcePoolTy(AllocatorTy<T> &&A, size_t Size = 0) noexcept 258 : Allocator(std::move(A)) { 259 if (Size) 260 (void)resize(Size); 261 } 262 263 ~ResourcePoolTy() noexcept { clear(); } 264 265 /// Get a resource from pool. `Next` always points to the next available 266 /// resource. That means, `[0, next-1]` have been assigned, and `[id,]` are 267 /// still available. If there is no resource left, we will ask for more. Each 268 /// time a resource is assigned, the id will increase one. 269 /// xxxxxs+++++++++ 270 /// ^ 271 /// Next 272 /// After assignment, the pool becomes the following and s is assigned. 273 /// xxxxxs+++++++++ 274 /// ^ 275 /// Next 276 int acquire(T &R) noexcept { 277 std::lock_guard<std::mutex> LG(Mutex); 278 if (Next == Resources.size()) { 279 auto NewSize = Resources.size() ? Resources.size() * 2 : 1; 280 if (!resize(NewSize)) 281 return OFFLOAD_FAIL; 282 } 283 284 assert(Next < Resources.size()); 285 286 R = Resources[Next++]; 287 288 return OFFLOAD_SUCCESS; 289 } 290 291 /// Return the resource back to the pool. When we return a resource, we need 292 /// to first decrease `Next`, and then copy the resource back. It is worth 293 /// noting that, the order of resources return might be different from that 294 /// they're assigned, that saying, at some point, there might be two identical 295 /// resources. 296 /// xxax+a+++++ 297 /// ^ 298 /// Next 299 /// However, it doesn't matter, because they're always on the two sides of 300 /// `Next`. The left one will in the end be overwritten by another resource. 301 /// Therefore, after several execution, the order of pool might be different 302 /// from its initial state. 303 void release(T R) noexcept { 304 std::lock_guard<std::mutex> LG(Mutex); 305 Resources[--Next] = R; 306 } 307 308 /// Released all stored resources and clear the pool. 309 /// Note: This function is not thread safe. Be sure to guard it if necessary. 310 void clear() noexcept { 311 for (auto &R : Resources) 312 (void)Allocator.destroy(R); 313 Resources.clear(); 314 } 315 }; 316 317 class DeviceRTLTy { 318 int NumberOfDevices; 319 // OpenMP environment properties 320 int EnvNumTeams; 321 int EnvTeamLimit; 322 int EnvTeamThreadLimit; 323 // OpenMP requires flags 324 int64_t RequiresFlags; 325 // Amount of dynamic shared memory to use at launch. 326 uint64_t DynamicMemorySize; 327 // Number of initial streams for each device. 328 int NumInitialStreams = 32; 329 330 static constexpr const int32_t HardThreadLimit = 1024; 331 static constexpr const int32_t DefaultNumTeams = 128; 332 static constexpr const int32_t DefaultNumThreads = 128; 333 334 using StreamPoolTy = ResourcePoolTy<CUstream>; 335 std::vector<std::unique_ptr<StreamPoolTy>> StreamPool; 336 337 ResourcePoolTy<CUevent> EventPool; 338 339 std::vector<DeviceDataTy> DeviceData; 340 std::vector<CUmodule> Modules; 341 342 /// A class responsible for interacting with device native runtime library to 343 /// allocate and free memory. 344 class CUDADeviceAllocatorTy : public DeviceAllocatorTy { 345 const int DeviceId; 346 const std::vector<DeviceDataTy> &DeviceData; 347 std::unordered_map<void *, TargetAllocTy> HostPinnedAllocs; 348 349 public: 350 CUDADeviceAllocatorTy(int DeviceId, std::vector<DeviceDataTy> &DeviceData) 351 : DeviceId(DeviceId), DeviceData(DeviceData) {} 352 353 void *allocate(size_t Size, void *, TargetAllocTy Kind) override { 354 if (Size == 0) 355 return nullptr; 356 357 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 358 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 359 return nullptr; 360 361 void *MemAlloc = nullptr; 362 switch (Kind) { 363 case TARGET_ALLOC_DEFAULT: 364 case TARGET_ALLOC_DEVICE: 365 CUdeviceptr DevicePtr; 366 Err = cuMemAlloc(&DevicePtr, Size); 367 MemAlloc = (void *)DevicePtr; 368 if (!checkResult(Err, "Error returned from cuMemAlloc\n")) 369 return nullptr; 370 break; 371 case TARGET_ALLOC_HOST: 372 void *HostPtr; 373 Err = cuMemAllocHost(&HostPtr, Size); 374 MemAlloc = HostPtr; 375 if (!checkResult(Err, "Error returned from cuMemAllocHost\n")) 376 return nullptr; 377 HostPinnedAllocs[MemAlloc] = Kind; 378 break; 379 case TARGET_ALLOC_SHARED: 380 CUdeviceptr SharedPtr; 381 Err = cuMemAllocManaged(&SharedPtr, Size, CU_MEM_ATTACH_GLOBAL); 382 MemAlloc = (void *)SharedPtr; 383 if (!checkResult(Err, "Error returned from cuMemAllocManaged\n")) 384 return nullptr; 385 break; 386 } 387 388 return MemAlloc; 389 } 390 391 int free(void *TgtPtr) override { 392 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 393 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 394 return OFFLOAD_FAIL; 395 396 // Host pinned memory must be freed differently. 397 TargetAllocTy Kind = 398 (HostPinnedAllocs.find(TgtPtr) == HostPinnedAllocs.end()) 399 ? TARGET_ALLOC_DEFAULT 400 : TARGET_ALLOC_HOST; 401 switch (Kind) { 402 case TARGET_ALLOC_DEFAULT: 403 case TARGET_ALLOC_DEVICE: 404 case TARGET_ALLOC_SHARED: 405 Err = cuMemFree((CUdeviceptr)TgtPtr); 406 if (!checkResult(Err, "Error returned from cuMemFree\n")) 407 return OFFLOAD_FAIL; 408 break; 409 case TARGET_ALLOC_HOST: 410 Err = cuMemFreeHost(TgtPtr); 411 if (!checkResult(Err, "Error returned from cuMemFreeHost\n")) 412 return OFFLOAD_FAIL; 413 break; 414 } 415 416 return OFFLOAD_SUCCESS; 417 } 418 }; 419 420 /// A vector of device allocators 421 std::vector<CUDADeviceAllocatorTy> DeviceAllocators; 422 423 /// A vector of memory managers. Since the memory manager is non-copyable and 424 // non-removable, we wrap them into std::unique_ptr. 425 std::vector<std::unique_ptr<MemoryManagerTy>> MemoryManagers; 426 427 /// Whether use memory manager 428 bool UseMemoryManager = true; 429 430 // Record entry point associated with device 431 void addOffloadEntry(const int DeviceId, const __tgt_offload_entry entry) { 432 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 433 E.Entries.push_back(entry); 434 } 435 436 // Return a pointer to the entry associated with the pointer 437 const __tgt_offload_entry *getOffloadEntry(const int DeviceId, 438 const void *Addr) const { 439 for (const __tgt_offload_entry &Itr : 440 DeviceData[DeviceId].FuncGblEntries.back().Entries) 441 if (Itr.addr == Addr) 442 return &Itr; 443 444 return nullptr; 445 } 446 447 // Return the pointer to the target entries table 448 __tgt_target_table *getOffloadEntriesTable(const int DeviceId) { 449 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 450 451 if (E.Entries.empty()) 452 return nullptr; 453 454 // Update table info according to the entries and return the pointer 455 E.Table.EntriesBegin = E.Entries.data(); 456 E.Table.EntriesEnd = E.Entries.data() + E.Entries.size(); 457 458 return &E.Table; 459 } 460 461 // Clear entries table for a device 462 void clearOffloadEntriesTable(const int DeviceId) { 463 DeviceData[DeviceId].FuncGblEntries.emplace_back(); 464 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 465 E.Entries.clear(); 466 E.Table.EntriesBegin = E.Table.EntriesEnd = nullptr; 467 } 468 469 public: 470 471 CUstream getStream(const int DeviceId, __tgt_async_info *AsyncInfo) const { 472 assert(AsyncInfo && "AsyncInfo is nullptr"); 473 474 if (!AsyncInfo->Queue) { 475 CUstream S; 476 if (StreamPool[DeviceId]->acquire(S) != OFFLOAD_SUCCESS) 477 return nullptr; 478 479 AsyncInfo->Queue = S; 480 } 481 482 return reinterpret_cast<CUstream>(AsyncInfo->Queue); 483 } 484 485 // This class should not be copied 486 DeviceRTLTy(const DeviceRTLTy &) = delete; 487 DeviceRTLTy(DeviceRTLTy &&) = delete; 488 489 DeviceRTLTy() 490 : NumberOfDevices(0), EnvNumTeams(-1), EnvTeamLimit(-1), 491 EnvTeamThreadLimit(-1), RequiresFlags(OMP_REQ_UNDEFINED), 492 DynamicMemorySize(0), EventPool(AllocatorTy<CUevent>()) { 493 494 DP("Start initializing CUDA\n"); 495 496 CUresult Err = cuInit(0); 497 if (Err == CUDA_ERROR_INVALID_HANDLE) { 498 // Can't call cuGetErrorString if dlsym failed 499 DP("Failed to load CUDA shared library\n"); 500 return; 501 } 502 if (!checkResult(Err, "Error returned from cuInit\n")) { 503 return; 504 } 505 506 Err = cuDeviceGetCount(&NumberOfDevices); 507 if (!checkResult(Err, "Error returned from cuDeviceGetCount\n")) 508 return; 509 510 if (NumberOfDevices == 0) { 511 DP("There are no devices supporting CUDA.\n"); 512 return; 513 } 514 515 DeviceData.resize(NumberOfDevices); 516 StreamPool.resize(NumberOfDevices); 517 518 // Get environment variables regarding teams 519 if (const char *EnvStr = getenv("OMP_TEAM_LIMIT")) { 520 // OMP_TEAM_LIMIT has been set 521 EnvTeamLimit = std::stoi(EnvStr); 522 DP("Parsed OMP_TEAM_LIMIT=%d\n", EnvTeamLimit); 523 } 524 if (const char *EnvStr = getenv("OMP_TEAMS_THREAD_LIMIT")) { 525 // OMP_TEAMS_THREAD_LIMIT has been set 526 EnvTeamThreadLimit = std::stoi(EnvStr); 527 DP("Parsed OMP_TEAMS_THREAD_LIMIT=%d\n", EnvTeamThreadLimit); 528 } 529 if (const char *EnvStr = getenv("OMP_NUM_TEAMS")) { 530 // OMP_NUM_TEAMS has been set 531 EnvNumTeams = std::stoi(EnvStr); 532 DP("Parsed OMP_NUM_TEAMS=%d\n", EnvNumTeams); 533 } 534 if (const char *EnvStr = getenv("LIBOMPTARGET_SHARED_MEMORY_SIZE")) { 535 // LIBOMPTARGET_SHARED_MEMORY_SIZE has been set 536 DynamicMemorySize = std::stoi(EnvStr); 537 DP("Parsed LIBOMPTARGET_SHARED_MEMORY_SIZE = %" PRIu64 "\n", 538 DynamicMemorySize); 539 } 540 if (const char *EnvStr = getenv("LIBOMPTARGET_NUM_INITIAL_STREAMS")) { 541 // LIBOMPTARGET_NUM_INITIAL_STREAMS has been set 542 NumInitialStreams = std::stoi(EnvStr); 543 DP("Parsed LIBOMPTARGET_NUM_INITIAL_STREAMS=%d\n", NumInitialStreams); 544 } 545 546 for (int I = 0; I < NumberOfDevices; ++I) 547 DeviceAllocators.emplace_back(I, DeviceData); 548 549 // Get the size threshold from environment variable 550 std::pair<size_t, bool> Res = MemoryManagerTy::getSizeThresholdFromEnv(); 551 UseMemoryManager = Res.second; 552 size_t MemoryManagerThreshold = Res.first; 553 554 if (UseMemoryManager) 555 for (int I = 0; I < NumberOfDevices; ++I) 556 MemoryManagers.emplace_back(std::make_unique<MemoryManagerTy>( 557 DeviceAllocators[I], MemoryManagerThreshold)); 558 } 559 560 ~DeviceRTLTy() { 561 // We first destruct memory managers in case that its dependent data are 562 // destroyed before it. 563 for (auto &M : MemoryManagers) 564 M.release(); 565 566 for (CUmodule &M : Modules) 567 // Close module 568 if (M) 569 checkResult(cuModuleUnload(M), "Error returned from cuModuleUnload\n"); 570 571 for (auto &S : StreamPool) 572 S.reset(); 573 574 EventPool.clear(); 575 576 for (DeviceDataTy &D : DeviceData) { 577 // Destroy context 578 if (D.Context) { 579 checkResult(cuCtxSetCurrent(D.Context), 580 "Error returned from cuCtxSetCurrent\n"); 581 CUdevice Device; 582 checkResult(cuCtxGetDevice(&Device), 583 "Error returned from cuCtxGetDevice\n"); 584 checkResult(cuDevicePrimaryCtxRelease(Device), 585 "Error returned from cuDevicePrimaryCtxRelease\n"); 586 } 587 } 588 } 589 590 // Check whether a given DeviceId is valid 591 bool isValidDeviceId(const int DeviceId) const { 592 return DeviceId >= 0 && DeviceId < NumberOfDevices; 593 } 594 595 int getNumOfDevices() const { return NumberOfDevices; } 596 597 void setRequiresFlag(const int64_t Flags) { this->RequiresFlags = Flags; } 598 599 int initDevice(const int DeviceId) { 600 CUdevice Device; 601 602 DP("Getting device %d\n", DeviceId); 603 CUresult Err = cuDeviceGet(&Device, DeviceId); 604 if (!checkResult(Err, "Error returned from cuDeviceGet\n")) 605 return OFFLOAD_FAIL; 606 607 // Query the current flags of the primary context and set its flags if 608 // it is inactive 609 unsigned int FormerPrimaryCtxFlags = 0; 610 int FormerPrimaryCtxIsActive = 0; 611 Err = cuDevicePrimaryCtxGetState(Device, &FormerPrimaryCtxFlags, 612 &FormerPrimaryCtxIsActive); 613 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxGetState\n")) 614 return OFFLOAD_FAIL; 615 616 if (FormerPrimaryCtxIsActive) { 617 DP("The primary context is active, no change to its flags\n"); 618 if ((FormerPrimaryCtxFlags & CU_CTX_SCHED_MASK) != 619 CU_CTX_SCHED_BLOCKING_SYNC) 620 DP("Warning the current flags are not CU_CTX_SCHED_BLOCKING_SYNC\n"); 621 } else { 622 DP("The primary context is inactive, set its flags to " 623 "CU_CTX_SCHED_BLOCKING_SYNC\n"); 624 Err = cuDevicePrimaryCtxSetFlags(Device, CU_CTX_SCHED_BLOCKING_SYNC); 625 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxSetFlags\n")) 626 return OFFLOAD_FAIL; 627 } 628 629 // Retain the per device primary context and save it to use whenever this 630 // device is selected. 631 Err = cuDevicePrimaryCtxRetain(&DeviceData[DeviceId].Context, Device); 632 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxRetain\n")) 633 return OFFLOAD_FAIL; 634 635 Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 636 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 637 return OFFLOAD_FAIL; 638 639 // Initialize stream pool 640 if (!StreamPool[DeviceId]) 641 StreamPool[DeviceId] = std::make_unique<StreamPoolTy>( 642 AllocatorTy<CUstream>(DeviceData[DeviceId].Context), 643 NumInitialStreams); 644 645 // Query attributes to determine number of threads/block and blocks/grid. 646 int MaxGridDimX; 647 Err = cuDeviceGetAttribute(&MaxGridDimX, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X, 648 Device); 649 if (Err != CUDA_SUCCESS) { 650 DP("Error getting max grid dimension, use default value %d\n", 651 DeviceRTLTy::DefaultNumTeams); 652 DeviceData[DeviceId].BlocksPerGrid = DeviceRTLTy::DefaultNumTeams; 653 } else { 654 DP("Using %d CUDA blocks per grid\n", MaxGridDimX); 655 DeviceData[DeviceId].BlocksPerGrid = MaxGridDimX; 656 } 657 658 // We are only exploiting threads along the x axis. 659 int MaxBlockDimX; 660 Err = cuDeviceGetAttribute(&MaxBlockDimX, 661 CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, Device); 662 if (Err != CUDA_SUCCESS) { 663 DP("Error getting max block dimension, use default value %d\n", 664 DeviceRTLTy::DefaultNumThreads); 665 DeviceData[DeviceId].ThreadsPerBlock = DeviceRTLTy::DefaultNumThreads; 666 } else { 667 DP("Using %d CUDA threads per block\n", MaxBlockDimX); 668 DeviceData[DeviceId].ThreadsPerBlock = MaxBlockDimX; 669 670 if (EnvTeamThreadLimit > 0 && 671 DeviceData[DeviceId].ThreadsPerBlock > EnvTeamThreadLimit) { 672 DP("Max CUDA threads per block %d exceeds the thread limit %d set by " 673 "OMP_TEAMS_THREAD_LIMIT, capping at the limit\n", 674 DeviceData[DeviceId].ThreadsPerBlock, EnvTeamThreadLimit); 675 DeviceData[DeviceId].ThreadsPerBlock = EnvTeamThreadLimit; 676 } 677 if (DeviceData[DeviceId].ThreadsPerBlock > DeviceRTLTy::HardThreadLimit) { 678 DP("Max CUDA threads per block %d exceeds the hard thread limit %d, " 679 "capping at the hard limit\n", 680 DeviceData[DeviceId].ThreadsPerBlock, DeviceRTLTy::HardThreadLimit); 681 DeviceData[DeviceId].ThreadsPerBlock = DeviceRTLTy::HardThreadLimit; 682 } 683 } 684 685 // Get and set warp size 686 int WarpSize; 687 Err = 688 cuDeviceGetAttribute(&WarpSize, CU_DEVICE_ATTRIBUTE_WARP_SIZE, Device); 689 if (Err != CUDA_SUCCESS) { 690 DP("Error getting warp size, assume default value 32\n"); 691 DeviceData[DeviceId].WarpSize = 32; 692 } else { 693 DP("Using warp size %d\n", WarpSize); 694 DeviceData[DeviceId].WarpSize = WarpSize; 695 } 696 697 // Adjust teams to the env variables 698 if (EnvTeamLimit > 0 && DeviceData[DeviceId].BlocksPerGrid > EnvTeamLimit) { 699 DP("Capping max CUDA blocks per grid to OMP_TEAM_LIMIT=%d\n", 700 EnvTeamLimit); 701 DeviceData[DeviceId].BlocksPerGrid = EnvTeamLimit; 702 } 703 704 size_t StackLimit; 705 size_t HeapLimit; 706 if (const char *EnvStr = getenv("LIBOMPTARGET_STACK_SIZE")) { 707 StackLimit = std::stol(EnvStr); 708 if (cuCtxSetLimit(CU_LIMIT_STACK_SIZE, StackLimit) != CUDA_SUCCESS) 709 return OFFLOAD_FAIL; 710 } else { 711 if (cuCtxGetLimit(&StackLimit, CU_LIMIT_STACK_SIZE) != CUDA_SUCCESS) 712 return OFFLOAD_FAIL; 713 } 714 if (const char *EnvStr = getenv("LIBOMPTARGET_HEAP_SIZE")) { 715 HeapLimit = std::stol(EnvStr); 716 if (cuCtxSetLimit(CU_LIMIT_MALLOC_HEAP_SIZE, HeapLimit) != CUDA_SUCCESS) 717 return OFFLOAD_FAIL; 718 } else { 719 if (cuCtxGetLimit(&HeapLimit, CU_LIMIT_MALLOC_HEAP_SIZE) != CUDA_SUCCESS) 720 return OFFLOAD_FAIL; 721 } 722 723 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 724 "Device supports up to %d CUDA blocks and %d threads with a " 725 "warp size of %d\n", 726 DeviceData[DeviceId].BlocksPerGrid, 727 DeviceData[DeviceId].ThreadsPerBlock, DeviceData[DeviceId].WarpSize); 728 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 729 "Device heap size is %d Bytes, device stack size is %d Bytes per " 730 "thread\n", 731 (int)HeapLimit, (int)StackLimit); 732 733 // Set default number of teams 734 if (EnvNumTeams > 0) { 735 DP("Default number of teams set according to environment %d\n", 736 EnvNumTeams); 737 DeviceData[DeviceId].NumTeams = EnvNumTeams; 738 } else { 739 DeviceData[DeviceId].NumTeams = DeviceRTLTy::DefaultNumTeams; 740 DP("Default number of teams set according to library's default %d\n", 741 DeviceRTLTy::DefaultNumTeams); 742 } 743 744 if (DeviceData[DeviceId].NumTeams > DeviceData[DeviceId].BlocksPerGrid) { 745 DP("Default number of teams exceeds device limit, capping at %d\n", 746 DeviceData[DeviceId].BlocksPerGrid); 747 DeviceData[DeviceId].NumTeams = DeviceData[DeviceId].BlocksPerGrid; 748 } 749 750 // Set default number of threads 751 DeviceData[DeviceId].NumThreads = DeviceRTLTy::DefaultNumThreads; 752 DP("Default number of threads set according to library's default %d\n", 753 DeviceRTLTy::DefaultNumThreads); 754 if (DeviceData[DeviceId].NumThreads > 755 DeviceData[DeviceId].ThreadsPerBlock) { 756 DP("Default number of threads exceeds device limit, capping at %d\n", 757 DeviceData[DeviceId].ThreadsPerBlock); 758 DeviceData[DeviceId].NumThreads = DeviceData[DeviceId].ThreadsPerBlock; 759 } 760 761 return OFFLOAD_SUCCESS; 762 } 763 764 __tgt_target_table *loadBinary(const int DeviceId, 765 const __tgt_device_image *Image) { 766 // Set the context we are using 767 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 768 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 769 return nullptr; 770 771 // Clear the offload table as we are going to create a new one. 772 clearOffloadEntriesTable(DeviceId); 773 774 // Create the module and extract the function pointers. 775 CUmodule Module; 776 DP("Load data from image " DPxMOD "\n", DPxPTR(Image->ImageStart)); 777 Err = cuModuleLoadDataEx(&Module, Image->ImageStart, 0, nullptr, nullptr); 778 if (!checkResult(Err, "Error returned from cuModuleLoadDataEx\n")) 779 return nullptr; 780 781 DP("CUDA module successfully loaded!\n"); 782 783 Modules.push_back(Module); 784 785 // Find the symbols in the module by name. 786 const __tgt_offload_entry *HostBegin = Image->EntriesBegin; 787 const __tgt_offload_entry *HostEnd = Image->EntriesEnd; 788 789 std::list<KernelTy> &KernelsList = DeviceData[DeviceId].KernelsList; 790 for (const __tgt_offload_entry *E = HostBegin; E != HostEnd; ++E) { 791 if (!E->addr) { 792 // We return nullptr when something like this happens, the host should 793 // have always something in the address to uniquely identify the target 794 // region. 795 DP("Invalid binary: host entry '<null>' (size = %zd)...\n", E->size); 796 return nullptr; 797 } 798 799 if (E->size) { 800 __tgt_offload_entry Entry = *E; 801 CUdeviceptr CUPtr; 802 size_t CUSize; 803 Err = cuModuleGetGlobal(&CUPtr, &CUSize, Module, E->name); 804 // We keep this style here because we need the name 805 if (Err != CUDA_SUCCESS) { 806 REPORT("Loading global '%s' Failed\n", E->name); 807 CUDA_ERR_STRING(Err); 808 return nullptr; 809 } 810 811 if (CUSize != E->size) { 812 DP("Loading global '%s' - size mismatch (%zd != %zd)\n", E->name, 813 CUSize, E->size); 814 return nullptr; 815 } 816 817 DP("Entry point " DPxMOD " maps to global %s (" DPxMOD ")\n", 818 DPxPTR(E - HostBegin), E->name, DPxPTR(CUPtr)); 819 820 Entry.addr = (void *)(CUPtr); 821 822 // Note: In the current implementation declare target variables 823 // can either be link or to. This means that once unified 824 // memory is activated via the requires directive, the variable 825 // can be used directly from the host in both cases. 826 // TODO: when variables types other than to or link are added, 827 // the below condition should be changed to explicitly 828 // check for to and link variables types: 829 // (RequiresFlags & OMP_REQ_UNIFIED_SHARED_MEMORY && (e->flags & 830 // OMP_DECLARE_TARGET_LINK || e->flags == OMP_DECLARE_TARGET_TO)) 831 if (RequiresFlags & OMP_REQ_UNIFIED_SHARED_MEMORY) { 832 // If unified memory is present any target link or to variables 833 // can access host addresses directly. There is no longer a 834 // need for device copies. 835 cuMemcpyHtoD(CUPtr, E->addr, sizeof(void *)); 836 DP("Copy linked variable host address (" DPxMOD 837 ") to device address (" DPxMOD ")\n", 838 DPxPTR(*((void **)E->addr)), DPxPTR(CUPtr)); 839 } 840 841 addOffloadEntry(DeviceId, Entry); 842 843 continue; 844 } 845 846 CUfunction Func; 847 Err = cuModuleGetFunction(&Func, Module, E->name); 848 // We keep this style here because we need the name 849 if (Err != CUDA_SUCCESS) { 850 REPORT("Loading '%s' Failed\n", E->name); 851 CUDA_ERR_STRING(Err); 852 return nullptr; 853 } 854 855 DP("Entry point " DPxMOD " maps to %s (" DPxMOD ")\n", 856 DPxPTR(E - HostBegin), E->name, DPxPTR(Func)); 857 858 // default value GENERIC (in case symbol is missing from cubin file) 859 llvm::omp::OMPTgtExecModeFlags ExecModeVal; 860 std::string ExecModeNameStr(E->name); 861 ExecModeNameStr += "_exec_mode"; 862 const char *ExecModeName = ExecModeNameStr.c_str(); 863 864 CUdeviceptr ExecModePtr; 865 size_t CUSize; 866 Err = cuModuleGetGlobal(&ExecModePtr, &CUSize, Module, ExecModeName); 867 if (Err == CUDA_SUCCESS) { 868 if (CUSize != sizeof(llvm::omp::OMPTgtExecModeFlags)) { 869 DP("Loading global exec_mode '%s' - size mismatch (%zd != %zd)\n", 870 ExecModeName, CUSize, sizeof(llvm::omp::OMPTgtExecModeFlags)); 871 return nullptr; 872 } 873 874 Err = cuMemcpyDtoH(&ExecModeVal, ExecModePtr, CUSize); 875 if (Err != CUDA_SUCCESS) { 876 REPORT("Error when copying data from device to host. Pointers: " 877 "host = " DPxMOD ", device = " DPxMOD ", size = %zd\n", 878 DPxPTR(&ExecModeVal), DPxPTR(ExecModePtr), CUSize); 879 CUDA_ERR_STRING(Err); 880 return nullptr; 881 } 882 } else { 883 DP("Loading global exec_mode '%s' - symbol missing, using default " 884 "value GENERIC (1)\n", 885 ExecModeName); 886 } 887 888 KernelsList.emplace_back(Func, ExecModeVal); 889 890 __tgt_offload_entry Entry = *E; 891 Entry.addr = &KernelsList.back(); 892 addOffloadEntry(DeviceId, Entry); 893 } 894 895 // send device environment data to the device 896 { 897 // TODO: The device ID used here is not the real device ID used by OpenMP. 898 DeviceEnvironmentTy DeviceEnv{0, static_cast<uint32_t>(NumberOfDevices), 899 static_cast<uint32_t>(DeviceId), 900 static_cast<uint32_t>(DynamicMemorySize)}; 901 902 if (const char *EnvStr = getenv("LIBOMPTARGET_DEVICE_RTL_DEBUG")) 903 DeviceEnv.DebugKind = std::stoi(EnvStr); 904 905 const char *DeviceEnvName = "omptarget_device_environment"; 906 CUdeviceptr DeviceEnvPtr; 907 size_t CUSize; 908 909 Err = cuModuleGetGlobal(&DeviceEnvPtr, &CUSize, Module, DeviceEnvName); 910 if (Err == CUDA_SUCCESS) { 911 if (CUSize != sizeof(DeviceEnv)) { 912 REPORT( 913 "Global device_environment '%s' - size mismatch (%zu != %zu)\n", 914 DeviceEnvName, CUSize, sizeof(int32_t)); 915 CUDA_ERR_STRING(Err); 916 return nullptr; 917 } 918 919 Err = cuMemcpyHtoD(DeviceEnvPtr, &DeviceEnv, CUSize); 920 if (Err != CUDA_SUCCESS) { 921 REPORT("Error when copying data from host to device. Pointers: " 922 "host = " DPxMOD ", device = " DPxMOD ", size = %zu\n", 923 DPxPTR(&DeviceEnv), DPxPTR(DeviceEnvPtr), CUSize); 924 CUDA_ERR_STRING(Err); 925 return nullptr; 926 } 927 928 DP("Sending global device environment data %zu bytes\n", CUSize); 929 } else { 930 DP("Finding global device environment '%s' - symbol missing.\n", 931 DeviceEnvName); 932 DP("Continue, considering this is a device RTL which does not accept " 933 "environment setting.\n"); 934 } 935 } 936 937 return getOffloadEntriesTable(DeviceId); 938 } 939 940 void *dataAlloc(const int DeviceId, const int64_t Size, 941 const TargetAllocTy Kind) { 942 switch (Kind) { 943 case TARGET_ALLOC_DEFAULT: 944 case TARGET_ALLOC_DEVICE: 945 if (UseMemoryManager) 946 return MemoryManagers[DeviceId]->allocate(Size, nullptr); 947 else 948 return DeviceAllocators[DeviceId].allocate(Size, nullptr, Kind); 949 case TARGET_ALLOC_HOST: 950 case TARGET_ALLOC_SHARED: 951 return DeviceAllocators[DeviceId].allocate(Size, nullptr, Kind); 952 } 953 954 REPORT("Invalid target data allocation kind or requested allocator not " 955 "implemented yet\n"); 956 957 return nullptr; 958 } 959 960 int dataSubmit(const int DeviceId, const void *TgtPtr, const void *HstPtr, 961 const int64_t Size, __tgt_async_info *AsyncInfo) const { 962 assert(AsyncInfo && "AsyncInfo is nullptr"); 963 964 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 965 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 966 return OFFLOAD_FAIL; 967 968 CUstream Stream = getStream(DeviceId, AsyncInfo); 969 970 Err = cuMemcpyHtoDAsync((CUdeviceptr)TgtPtr, HstPtr, Size, Stream); 971 if (Err != CUDA_SUCCESS) { 972 DP("Error when copying data from host to device. Pointers: host " 973 "= " DPxMOD ", device = " DPxMOD ", size = %" PRId64 "\n", 974 DPxPTR(HstPtr), DPxPTR(TgtPtr), Size); 975 CUDA_ERR_STRING(Err); 976 return OFFLOAD_FAIL; 977 } 978 979 return OFFLOAD_SUCCESS; 980 } 981 982 int dataRetrieve(const int DeviceId, void *HstPtr, const void *TgtPtr, 983 const int64_t Size, __tgt_async_info *AsyncInfo) const { 984 assert(AsyncInfo && "AsyncInfo is nullptr"); 985 986 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 987 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 988 return OFFLOAD_FAIL; 989 990 CUstream Stream = getStream(DeviceId, AsyncInfo); 991 992 Err = cuMemcpyDtoHAsync(HstPtr, (CUdeviceptr)TgtPtr, Size, Stream); 993 if (Err != CUDA_SUCCESS) { 994 DP("Error when copying data from device to host. Pointers: host " 995 "= " DPxMOD ", device = " DPxMOD ", size = %" PRId64 "\n", 996 DPxPTR(HstPtr), DPxPTR(TgtPtr), Size); 997 CUDA_ERR_STRING(Err); 998 return OFFLOAD_FAIL; 999 } 1000 1001 return OFFLOAD_SUCCESS; 1002 } 1003 1004 int dataExchange(int SrcDevId, const void *SrcPtr, int DstDevId, void *DstPtr, 1005 int64_t Size, __tgt_async_info *AsyncInfo) const { 1006 assert(AsyncInfo && "AsyncInfo is nullptr"); 1007 1008 CUresult Err = cuCtxSetCurrent(DeviceData[SrcDevId].Context); 1009 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 1010 return OFFLOAD_FAIL; 1011 1012 CUstream Stream = getStream(SrcDevId, AsyncInfo); 1013 1014 // If they are two devices, we try peer to peer copy first 1015 if (SrcDevId != DstDevId) { 1016 int CanAccessPeer = 0; 1017 Err = cuDeviceCanAccessPeer(&CanAccessPeer, SrcDevId, DstDevId); 1018 if (Err != CUDA_SUCCESS) { 1019 REPORT("Error returned from cuDeviceCanAccessPeer. src = %" PRId32 1020 ", dst = %" PRId32 "\n", 1021 SrcDevId, DstDevId); 1022 CUDA_ERR_STRING(Err); 1023 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1024 } 1025 1026 if (!CanAccessPeer) { 1027 DP("P2P memcpy not supported so fall back to D2D memcpy"); 1028 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1029 } 1030 1031 Err = cuCtxEnablePeerAccess(DeviceData[DstDevId].Context, 0); 1032 if (Err != CUDA_SUCCESS) { 1033 REPORT("Error returned from cuCtxEnablePeerAccess. src = %" PRId32 1034 ", dst = %" PRId32 "\n", 1035 SrcDevId, DstDevId); 1036 CUDA_ERR_STRING(Err); 1037 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1038 } 1039 1040 Err = cuMemcpyPeerAsync((CUdeviceptr)DstPtr, DeviceData[DstDevId].Context, 1041 (CUdeviceptr)SrcPtr, DeviceData[SrcDevId].Context, 1042 Size, Stream); 1043 if (Err == CUDA_SUCCESS) 1044 return OFFLOAD_SUCCESS; 1045 1046 DP("Error returned from cuMemcpyPeerAsync. src_ptr = " DPxMOD 1047 ", src_id =%" PRId32 ", dst_ptr = " DPxMOD ", dst_id =%" PRId32 "\n", 1048 DPxPTR(SrcPtr), SrcDevId, DPxPTR(DstPtr), DstDevId); 1049 CUDA_ERR_STRING(Err); 1050 } 1051 1052 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1053 } 1054 1055 int dataDelete(const int DeviceId, void *TgtPtr) { 1056 if (UseMemoryManager) 1057 return MemoryManagers[DeviceId]->free(TgtPtr); 1058 1059 return DeviceAllocators[DeviceId].free(TgtPtr); 1060 } 1061 1062 int runTargetTeamRegion(const int DeviceId, void *TgtEntryPtr, void **TgtArgs, 1063 ptrdiff_t *TgtOffsets, const int ArgNum, 1064 const int TeamNum, const int ThreadLimit, 1065 const unsigned int LoopTripCount, 1066 __tgt_async_info *AsyncInfo) const { 1067 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 1068 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 1069 return OFFLOAD_FAIL; 1070 1071 // All args are references. 1072 std::vector<void *> Args(ArgNum); 1073 std::vector<void *> Ptrs(ArgNum); 1074 1075 for (int I = 0; I < ArgNum; ++I) { 1076 Ptrs[I] = (void *)((intptr_t)TgtArgs[I] + TgtOffsets[I]); 1077 Args[I] = &Ptrs[I]; 1078 } 1079 1080 KernelTy *KernelInfo = reinterpret_cast<KernelTy *>(TgtEntryPtr); 1081 1082 const bool IsSPMDGenericMode = 1083 KernelInfo->ExecutionMode == llvm::omp::OMP_TGT_EXEC_MODE_GENERIC_SPMD; 1084 const bool IsSPMDMode = 1085 KernelInfo->ExecutionMode == llvm::omp::OMP_TGT_EXEC_MODE_SPMD; 1086 const bool IsGenericMode = 1087 KernelInfo->ExecutionMode == llvm::omp::OMP_TGT_EXEC_MODE_GENERIC; 1088 1089 int CudaThreadsPerBlock; 1090 if (ThreadLimit > 0) { 1091 DP("Setting CUDA threads per block to requested %d\n", ThreadLimit); 1092 CudaThreadsPerBlock = ThreadLimit; 1093 // Add master warp if necessary 1094 if (IsGenericMode) { 1095 DP("Adding master warp: +%d threads\n", DeviceData[DeviceId].WarpSize); 1096 CudaThreadsPerBlock += DeviceData[DeviceId].WarpSize; 1097 } 1098 } else { 1099 DP("Setting CUDA threads per block to default %d\n", 1100 DeviceData[DeviceId].NumThreads); 1101 CudaThreadsPerBlock = DeviceData[DeviceId].NumThreads; 1102 } 1103 1104 if (CudaThreadsPerBlock > DeviceData[DeviceId].ThreadsPerBlock) { 1105 DP("Threads per block capped at device limit %d\n", 1106 DeviceData[DeviceId].ThreadsPerBlock); 1107 CudaThreadsPerBlock = DeviceData[DeviceId].ThreadsPerBlock; 1108 } 1109 1110 if (!KernelInfo->MaxThreadsPerBlock) { 1111 Err = cuFuncGetAttribute(&KernelInfo->MaxThreadsPerBlock, 1112 CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, 1113 KernelInfo->Func); 1114 if (!checkResult(Err, "Error returned from cuFuncGetAttribute\n")) 1115 return OFFLOAD_FAIL; 1116 } 1117 1118 if (KernelInfo->MaxThreadsPerBlock < CudaThreadsPerBlock) { 1119 DP("Threads per block capped at kernel limit %d\n", 1120 KernelInfo->MaxThreadsPerBlock); 1121 CudaThreadsPerBlock = KernelInfo->MaxThreadsPerBlock; 1122 } 1123 1124 unsigned int CudaBlocksPerGrid; 1125 if (TeamNum <= 0) { 1126 if (LoopTripCount > 0 && EnvNumTeams < 0) { 1127 if (IsSPMDGenericMode) { 1128 // If we reach this point, then we are executing a kernel that was 1129 // transformed from Generic-mode to SPMD-mode. This kernel has 1130 // SPMD-mode execution, but needs its blocks to be scheduled 1131 // differently because the current loop trip count only applies to the 1132 // `teams distribute` region and will create var too few blocks using 1133 // the regular SPMD-mode method. 1134 CudaBlocksPerGrid = LoopTripCount; 1135 } else if (IsSPMDMode) { 1136 // We have a combined construct, i.e. `target teams distribute 1137 // parallel for [simd]`. We launch so many teams so that each thread 1138 // will execute one iteration of the loop. round up to the nearest 1139 // integer 1140 CudaBlocksPerGrid = ((LoopTripCount - 1) / CudaThreadsPerBlock) + 1; 1141 } else if (IsGenericMode) { 1142 // If we reach this point, then we have a non-combined construct, i.e. 1143 // `teams distribute` with a nested `parallel for` and each team is 1144 // assigned one iteration of the `distribute` loop. E.g.: 1145 // 1146 // #pragma omp target teams distribute 1147 // for(...loop_tripcount...) { 1148 // #pragma omp parallel for 1149 // for(...) {} 1150 // } 1151 // 1152 // Threads within a team will execute the iterations of the `parallel` 1153 // loop. 1154 CudaBlocksPerGrid = LoopTripCount; 1155 } else { 1156 REPORT("Unknown execution mode: %d\n", 1157 static_cast<int8_t>(KernelInfo->ExecutionMode)); 1158 return OFFLOAD_FAIL; 1159 } 1160 DP("Using %d teams due to loop trip count %" PRIu32 1161 " and number of threads per block %d\n", 1162 CudaBlocksPerGrid, LoopTripCount, CudaThreadsPerBlock); 1163 } else { 1164 DP("Using default number of teams %d\n", DeviceData[DeviceId].NumTeams); 1165 CudaBlocksPerGrid = DeviceData[DeviceId].NumTeams; 1166 } 1167 } else { 1168 DP("Using requested number of teams %d\n", TeamNum); 1169 CudaBlocksPerGrid = TeamNum; 1170 } 1171 1172 if (CudaBlocksPerGrid > DeviceData[DeviceId].BlocksPerGrid) { 1173 DP("Capping number of teams to team limit %d\n", 1174 DeviceData[DeviceId].BlocksPerGrid); 1175 CudaBlocksPerGrid = DeviceData[DeviceId].BlocksPerGrid; 1176 } 1177 1178 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 1179 "Launching kernel %s with %d blocks and %d threads in %s mode\n", 1180 (getOffloadEntry(DeviceId, TgtEntryPtr)) 1181 ? getOffloadEntry(DeviceId, TgtEntryPtr)->name 1182 : "(null)", 1183 CudaBlocksPerGrid, CudaThreadsPerBlock, 1184 (!IsSPMDMode ? (IsGenericMode ? "Generic" : "SPMD-Generic") : "SPMD")); 1185 1186 CUstream Stream = getStream(DeviceId, AsyncInfo); 1187 Err = cuLaunchKernel(KernelInfo->Func, CudaBlocksPerGrid, /* gridDimY */ 1, 1188 /* gridDimZ */ 1, CudaThreadsPerBlock, 1189 /* blockDimY */ 1, /* blockDimZ */ 1, 1190 DynamicMemorySize, Stream, &Args[0], nullptr); 1191 if (!checkResult(Err, "Error returned from cuLaunchKernel\n")) 1192 return OFFLOAD_FAIL; 1193 1194 DP("Launch of entry point at " DPxMOD " successful!\n", 1195 DPxPTR(TgtEntryPtr)); 1196 1197 return OFFLOAD_SUCCESS; 1198 } 1199 1200 int synchronize(const int DeviceId, __tgt_async_info *AsyncInfo) const { 1201 CUstream Stream = reinterpret_cast<CUstream>(AsyncInfo->Queue); 1202 CUresult Err = cuStreamSynchronize(Stream); 1203 1204 // Once the stream is synchronized, return it to stream pool and reset 1205 // AsyncInfo. This is to make sure the synchronization only works for its 1206 // own tasks. 1207 StreamPool[DeviceId]->release(reinterpret_cast<CUstream>(AsyncInfo->Queue)); 1208 AsyncInfo->Queue = nullptr; 1209 1210 if (Err != CUDA_SUCCESS) { 1211 DP("Error when synchronizing stream. stream = " DPxMOD 1212 ", async info ptr = " DPxMOD "\n", 1213 DPxPTR(Stream), DPxPTR(AsyncInfo)); 1214 CUDA_ERR_STRING(Err); 1215 } 1216 return (Err == CUDA_SUCCESS) ? OFFLOAD_SUCCESS : OFFLOAD_FAIL; 1217 } 1218 1219 void printDeviceInfo(int32_t device_id) { 1220 char TmpChar[1000]; 1221 std::string TmpStr; 1222 size_t TmpSt; 1223 int TmpInt, TmpInt2, TmpInt3; 1224 1225 CUdevice Device; 1226 checkResult(cuDeviceGet(&Device, device_id), 1227 "Error returned from cuCtxGetDevice\n"); 1228 1229 cuDriverGetVersion(&TmpInt); 1230 printf(" CUDA Driver Version: \t\t%d \n", TmpInt); 1231 printf(" CUDA Device Number: \t\t%d \n", device_id); 1232 checkResult(cuDeviceGetName(TmpChar, 1000, Device), 1233 "Error returned from cuDeviceGetName\n"); 1234 printf(" Device Name: \t\t\t%s \n", TmpChar); 1235 checkResult(cuDeviceTotalMem(&TmpSt, Device), 1236 "Error returned from cuDeviceTotalMem\n"); 1237 printf(" Global Memory Size: \t\t%zu bytes \n", TmpSt); 1238 checkResult(cuDeviceGetAttribute( 1239 &TmpInt, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, Device), 1240 "Error returned from cuDeviceGetAttribute\n"); 1241 printf(" Number of Multiprocessors: \t\t%d \n", TmpInt); 1242 checkResult( 1243 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_GPU_OVERLAP, Device), 1244 "Error returned from cuDeviceGetAttribute\n"); 1245 printf(" Concurrent Copy and Execution: \t%s \n", BOOL2TEXT(TmpInt)); 1246 checkResult(cuDeviceGetAttribute( 1247 &TmpInt, CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY, Device), 1248 "Error returned from cuDeviceGetAttribute\n"); 1249 printf(" Total Constant Memory: \t\t%d bytes\n", TmpInt); 1250 checkResult( 1251 cuDeviceGetAttribute( 1252 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK, Device), 1253 "Error returned from cuDeviceGetAttribute\n"); 1254 printf(" Max Shared Memory per Block: \t%d bytes \n", TmpInt); 1255 checkResult( 1256 cuDeviceGetAttribute( 1257 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK, Device), 1258 "Error returned from cuDeviceGetAttribute\n"); 1259 printf(" Registers per Block: \t\t%d \n", TmpInt); 1260 checkResult( 1261 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_WARP_SIZE, Device), 1262 "Error returned from cuDeviceGetAttribute\n"); 1263 printf(" Warp Size: \t\t\t\t%d Threads \n", TmpInt); 1264 checkResult(cuDeviceGetAttribute( 1265 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK, Device), 1266 "Error returned from cuDeviceGetAttribute\n"); 1267 printf(" Maximum Threads per Block: \t\t%d \n", TmpInt); 1268 checkResult(cuDeviceGetAttribute( 1269 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, Device), 1270 "Error returned from cuDeviceGetAttribute\n"); 1271 checkResult(cuDeviceGetAttribute( 1272 &TmpInt2, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y, Device), 1273 "Error returned from cuDeviceGetAttribute\n"); 1274 checkResult(cuDeviceGetAttribute( 1275 &TmpInt3, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z, Device), 1276 "Error returned from cuDeviceGetAttribute\n"); 1277 printf(" Maximum Block Dimensions: \t\t%d, %d, %d \n", TmpInt, TmpInt2, 1278 TmpInt3); 1279 checkResult(cuDeviceGetAttribute( 1280 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X, Device), 1281 "Error returned from cuDeviceGetAttribute\n"); 1282 checkResult(cuDeviceGetAttribute( 1283 &TmpInt2, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y, Device), 1284 "Error returned from cuDeviceGetAttribute\n"); 1285 checkResult(cuDeviceGetAttribute( 1286 &TmpInt3, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z, Device), 1287 "Error returned from cuDeviceGetAttribute\n"); 1288 printf(" Maximum Grid Dimensions: \t\t%d x %d x %d \n", TmpInt, TmpInt2, 1289 TmpInt3); 1290 checkResult( 1291 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_MAX_PITCH, Device), 1292 "Error returned from cuDeviceGetAttribute\n"); 1293 printf(" Maximum Memory Pitch: \t\t%d bytes \n", TmpInt); 1294 checkResult(cuDeviceGetAttribute( 1295 &TmpInt, CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT, Device), 1296 "Error returned from cuDeviceGetAttribute\n"); 1297 printf(" Texture Alignment: \t\t\t%d bytes \n", TmpInt); 1298 checkResult( 1299 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, Device), 1300 "Error returned from cuDeviceGetAttribute\n"); 1301 printf(" Clock Rate: \t\t\t%d kHz\n", TmpInt); 1302 checkResult(cuDeviceGetAttribute( 1303 &TmpInt, CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT, Device), 1304 "Error returned from cuDeviceGetAttribute\n"); 1305 printf(" Execution Timeout: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1306 checkResult( 1307 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_INTEGRATED, Device), 1308 "Error returned from cuDeviceGetAttribute\n"); 1309 printf(" Integrated Device: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1310 checkResult(cuDeviceGetAttribute( 1311 &TmpInt, CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY, Device), 1312 "Error returned from cuDeviceGetAttribute\n"); 1313 printf(" Can Map Host Memory: \t\t%s \n", BOOL2TEXT(TmpInt)); 1314 checkResult( 1315 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_COMPUTE_MODE, Device), 1316 "Error returned from cuDeviceGetAttribute\n"); 1317 if (TmpInt == CU_COMPUTEMODE_DEFAULT) 1318 TmpStr = "DEFAULT"; 1319 else if (TmpInt == CU_COMPUTEMODE_PROHIBITED) 1320 TmpStr = "PROHIBITED"; 1321 else if (TmpInt == CU_COMPUTEMODE_EXCLUSIVE_PROCESS) 1322 TmpStr = "EXCLUSIVE PROCESS"; 1323 else 1324 TmpStr = "unknown"; 1325 printf(" Compute Mode: \t\t\t%s \n", TmpStr.c_str()); 1326 checkResult(cuDeviceGetAttribute( 1327 &TmpInt, CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS, Device), 1328 "Error returned from cuDeviceGetAttribute\n"); 1329 printf(" Concurrent Kernels: \t\t%s \n", BOOL2TEXT(TmpInt)); 1330 checkResult( 1331 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_ECC_ENABLED, Device), 1332 "Error returned from cuDeviceGetAttribute\n"); 1333 printf(" ECC Enabled: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1334 checkResult(cuDeviceGetAttribute( 1335 &TmpInt, CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE, Device), 1336 "Error returned from cuDeviceGetAttribute\n"); 1337 printf(" Memory Clock Rate: \t\t\t%d kHz\n", TmpInt); 1338 checkResult( 1339 cuDeviceGetAttribute( 1340 &TmpInt, CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH, Device), 1341 "Error returned from cuDeviceGetAttribute\n"); 1342 printf(" Memory Bus Width: \t\t\t%d bits\n", TmpInt); 1343 checkResult(cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE, 1344 Device), 1345 "Error returned from cuDeviceGetAttribute\n"); 1346 printf(" L2 Cache Size: \t\t\t%d bytes \n", TmpInt); 1347 checkResult(cuDeviceGetAttribute( 1348 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_MULTIPROCESSOR, 1349 Device), 1350 "Error returned from cuDeviceGetAttribute\n"); 1351 printf(" Max Threads Per SMP: \t\t%d \n", TmpInt); 1352 checkResult(cuDeviceGetAttribute( 1353 &TmpInt, CU_DEVICE_ATTRIBUTE_ASYNC_ENGINE_COUNT, Device), 1354 "Error returned from cuDeviceGetAttribute\n"); 1355 printf(" Async Engines: \t\t\t%s (%d) \n", BOOL2TEXT(TmpInt), TmpInt); 1356 checkResult(cuDeviceGetAttribute( 1357 &TmpInt, CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING, Device), 1358 "Error returned from cuDeviceGetAttribute\n"); 1359 printf(" Unified Addressing: \t\t%s \n", BOOL2TEXT(TmpInt)); 1360 checkResult(cuDeviceGetAttribute( 1361 &TmpInt, CU_DEVICE_ATTRIBUTE_MANAGED_MEMORY, Device), 1362 "Error returned from cuDeviceGetAttribute\n"); 1363 printf(" Managed Memory: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1364 checkResult( 1365 cuDeviceGetAttribute( 1366 &TmpInt, CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS, Device), 1367 "Error returned from cuDeviceGetAttribute\n"); 1368 printf(" Concurrent Managed Memory: \t\t%s \n", BOOL2TEXT(TmpInt)); 1369 checkResult( 1370 cuDeviceGetAttribute( 1371 &TmpInt, CU_DEVICE_ATTRIBUTE_COMPUTE_PREEMPTION_SUPPORTED, Device), 1372 "Error returned from cuDeviceGetAttribute\n"); 1373 printf(" Preemption Supported: \t\t%s \n", BOOL2TEXT(TmpInt)); 1374 checkResult(cuDeviceGetAttribute( 1375 &TmpInt, CU_DEVICE_ATTRIBUTE_COOPERATIVE_LAUNCH, Device), 1376 "Error returned from cuDeviceGetAttribute\n"); 1377 printf(" Cooperative Launch: \t\t%s \n", BOOL2TEXT(TmpInt)); 1378 checkResult(cuDeviceGetAttribute( 1379 &TmpInt, CU_DEVICE_ATTRIBUTE_MULTI_GPU_BOARD, Device), 1380 "Error returned from cuDeviceGetAttribute\n"); 1381 printf(" Multi-Device Boars: \t\t%s \n", BOOL2TEXT(TmpInt)); 1382 checkResult( 1383 cuDeviceGetAttribute( 1384 &TmpInt, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, Device), 1385 "Error returned from cuDeviceGetAttribute\n"); 1386 checkResult( 1387 cuDeviceGetAttribute( 1388 &TmpInt2, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, Device), 1389 "Error returned from cuDeviceGetAttribute\n"); 1390 printf(" Compute Capabilities: \t\t%d%d \n", TmpInt, TmpInt2); 1391 } 1392 1393 int createEvent(void **P) { 1394 CUevent Event = nullptr; 1395 if (EventPool.acquire(Event) != OFFLOAD_SUCCESS) 1396 return OFFLOAD_FAIL; 1397 *P = Event; 1398 return OFFLOAD_SUCCESS; 1399 } 1400 1401 int destroyEvent(void *EventPtr) { 1402 EventPool.release(reinterpret_cast<CUevent>(EventPtr)); 1403 return OFFLOAD_SUCCESS; 1404 } 1405 1406 int waitEvent(const int DeviceId, __tgt_async_info *AsyncInfo, 1407 void *EventPtr) const { 1408 CUstream Stream = getStream(DeviceId, AsyncInfo); 1409 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 1410 1411 // We don't use CU_EVENT_WAIT_DEFAULT here as it is only available from 1412 // specific CUDA version, and defined as 0x0. In previous version, per CUDA 1413 // API document, that argument has to be 0x0. 1414 CUresult Err = cuStreamWaitEvent(Stream, Event, 0); 1415 if (Err != CUDA_SUCCESS) { 1416 DP("Error when waiting event. stream = " DPxMOD ", event = " DPxMOD "\n", 1417 DPxPTR(Stream), DPxPTR(Event)); 1418 CUDA_ERR_STRING(Err); 1419 return OFFLOAD_FAIL; 1420 } 1421 1422 return OFFLOAD_SUCCESS; 1423 } 1424 1425 int releaseAsyncInfo(int DeviceId, __tgt_async_info *AsyncInfo) const { 1426 if (AsyncInfo->Queue) { 1427 StreamPool[DeviceId]->release( 1428 reinterpret_cast<CUstream>(AsyncInfo->Queue)); 1429 AsyncInfo->Queue = nullptr; 1430 } 1431 1432 return OFFLOAD_SUCCESS; 1433 } 1434 1435 int initAsyncInfo(int DeviceId, __tgt_async_info **AsyncInfo) const { 1436 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 1437 if (!checkResult(Err, "error returned from cuCtxSetCurrent")) 1438 return OFFLOAD_FAIL; 1439 1440 *AsyncInfo = new __tgt_async_info; 1441 getStream(DeviceId, *AsyncInfo); 1442 return OFFLOAD_SUCCESS; 1443 } 1444 1445 int initDeviceInfo(int DeviceId, __tgt_device_info *DeviceInfo, 1446 const char **ErrStr) const { 1447 assert(DeviceInfo && "DeviceInfo is nullptr"); 1448 1449 if (!DeviceInfo->Context) 1450 DeviceInfo->Context = DeviceData[DeviceId].Context; 1451 if (!DeviceInfo->Device) { 1452 CUdevice Dev; 1453 CUresult Err = cuDeviceGet(&Dev, DeviceId); 1454 if (Err == CUDA_SUCCESS) { 1455 DeviceInfo->Device = reinterpret_cast<void *>(Dev); 1456 } else { 1457 cuGetErrorString(Err, ErrStr); 1458 return OFFLOAD_FAIL; 1459 } 1460 } 1461 return OFFLOAD_SUCCESS; 1462 } 1463 }; 1464 1465 DeviceRTLTy DeviceRTL; 1466 } // namespace 1467 1468 // Exposed library API function 1469 #ifdef __cplusplus 1470 extern "C" { 1471 #endif 1472 1473 int32_t __tgt_rtl_is_valid_binary(__tgt_device_image *image) { 1474 return elf_check_machine(image, /* EM_CUDA */ 190); 1475 } 1476 1477 int32_t __tgt_rtl_number_of_devices() { return DeviceRTL.getNumOfDevices(); } 1478 1479 int64_t __tgt_rtl_init_requires(int64_t RequiresFlags) { 1480 DP("Init requires flags to %" PRId64 "\n", RequiresFlags); 1481 DeviceRTL.setRequiresFlag(RequiresFlags); 1482 return RequiresFlags; 1483 } 1484 1485 int32_t __tgt_rtl_is_data_exchangable(int32_t src_dev_id, int dst_dev_id) { 1486 if (DeviceRTL.isValidDeviceId(src_dev_id) && 1487 DeviceRTL.isValidDeviceId(dst_dev_id)) 1488 return 1; 1489 1490 return 0; 1491 } 1492 1493 int32_t __tgt_rtl_init_device(int32_t device_id) { 1494 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1495 1496 return DeviceRTL.initDevice(device_id); 1497 } 1498 1499 __tgt_target_table *__tgt_rtl_load_binary(int32_t device_id, 1500 __tgt_device_image *image) { 1501 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1502 1503 return DeviceRTL.loadBinary(device_id, image); 1504 } 1505 1506 void *__tgt_rtl_data_alloc(int32_t device_id, int64_t size, void *, 1507 int32_t kind) { 1508 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1509 1510 return DeviceRTL.dataAlloc(device_id, size, (TargetAllocTy)kind); 1511 } 1512 1513 int32_t __tgt_rtl_data_submit(int32_t device_id, void *tgt_ptr, void *hst_ptr, 1514 int64_t size) { 1515 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1516 1517 __tgt_async_info AsyncInfo; 1518 const int32_t rc = __tgt_rtl_data_submit_async(device_id, tgt_ptr, hst_ptr, 1519 size, &AsyncInfo); 1520 if (rc != OFFLOAD_SUCCESS) 1521 return OFFLOAD_FAIL; 1522 1523 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1524 } 1525 1526 int32_t __tgt_rtl_data_submit_async(int32_t device_id, void *tgt_ptr, 1527 void *hst_ptr, int64_t size, 1528 __tgt_async_info *async_info_ptr) { 1529 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1530 assert(async_info_ptr && "async_info_ptr is nullptr"); 1531 1532 return DeviceRTL.dataSubmit(device_id, tgt_ptr, hst_ptr, size, 1533 async_info_ptr); 1534 } 1535 1536 int32_t __tgt_rtl_data_retrieve(int32_t device_id, void *hst_ptr, void *tgt_ptr, 1537 int64_t size) { 1538 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1539 1540 __tgt_async_info AsyncInfo; 1541 const int32_t rc = __tgt_rtl_data_retrieve_async(device_id, hst_ptr, tgt_ptr, 1542 size, &AsyncInfo); 1543 if (rc != OFFLOAD_SUCCESS) 1544 return OFFLOAD_FAIL; 1545 1546 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1547 } 1548 1549 int32_t __tgt_rtl_data_retrieve_async(int32_t device_id, void *hst_ptr, 1550 void *tgt_ptr, int64_t size, 1551 __tgt_async_info *async_info_ptr) { 1552 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1553 assert(async_info_ptr && "async_info_ptr is nullptr"); 1554 1555 return DeviceRTL.dataRetrieve(device_id, hst_ptr, tgt_ptr, size, 1556 async_info_ptr); 1557 } 1558 1559 int32_t __tgt_rtl_data_exchange_async(int32_t src_dev_id, void *src_ptr, 1560 int dst_dev_id, void *dst_ptr, 1561 int64_t size, 1562 __tgt_async_info *AsyncInfo) { 1563 assert(DeviceRTL.isValidDeviceId(src_dev_id) && "src_dev_id is invalid"); 1564 assert(DeviceRTL.isValidDeviceId(dst_dev_id) && "dst_dev_id is invalid"); 1565 assert(AsyncInfo && "AsyncInfo is nullptr"); 1566 1567 return DeviceRTL.dataExchange(src_dev_id, src_ptr, dst_dev_id, dst_ptr, size, 1568 AsyncInfo); 1569 } 1570 1571 int32_t __tgt_rtl_data_exchange(int32_t src_dev_id, void *src_ptr, 1572 int32_t dst_dev_id, void *dst_ptr, 1573 int64_t size) { 1574 assert(DeviceRTL.isValidDeviceId(src_dev_id) && "src_dev_id is invalid"); 1575 assert(DeviceRTL.isValidDeviceId(dst_dev_id) && "dst_dev_id is invalid"); 1576 1577 __tgt_async_info AsyncInfo; 1578 const int32_t rc = __tgt_rtl_data_exchange_async( 1579 src_dev_id, src_ptr, dst_dev_id, dst_ptr, size, &AsyncInfo); 1580 if (rc != OFFLOAD_SUCCESS) 1581 return OFFLOAD_FAIL; 1582 1583 return __tgt_rtl_synchronize(src_dev_id, &AsyncInfo); 1584 } 1585 1586 int32_t __tgt_rtl_data_delete(int32_t device_id, void *tgt_ptr) { 1587 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1588 1589 return DeviceRTL.dataDelete(device_id, tgt_ptr); 1590 } 1591 1592 int32_t __tgt_rtl_run_target_team_region(int32_t device_id, void *tgt_entry_ptr, 1593 void **tgt_args, 1594 ptrdiff_t *tgt_offsets, 1595 int32_t arg_num, int32_t team_num, 1596 int32_t thread_limit, 1597 uint64_t loop_tripcount) { 1598 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1599 1600 __tgt_async_info AsyncInfo; 1601 const int32_t rc = __tgt_rtl_run_target_team_region_async( 1602 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, team_num, 1603 thread_limit, loop_tripcount, &AsyncInfo); 1604 if (rc != OFFLOAD_SUCCESS) 1605 return OFFLOAD_FAIL; 1606 1607 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1608 } 1609 1610 int32_t __tgt_rtl_run_target_team_region_async( 1611 int32_t device_id, void *tgt_entry_ptr, void **tgt_args, 1612 ptrdiff_t *tgt_offsets, int32_t arg_num, int32_t team_num, 1613 int32_t thread_limit, uint64_t loop_tripcount, 1614 __tgt_async_info *async_info_ptr) { 1615 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1616 1617 return DeviceRTL.runTargetTeamRegion( 1618 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, team_num, 1619 thread_limit, loop_tripcount, async_info_ptr); 1620 } 1621 1622 int32_t __tgt_rtl_run_target_region(int32_t device_id, void *tgt_entry_ptr, 1623 void **tgt_args, ptrdiff_t *tgt_offsets, 1624 int32_t arg_num) { 1625 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1626 1627 __tgt_async_info AsyncInfo; 1628 const int32_t rc = __tgt_rtl_run_target_region_async( 1629 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, &AsyncInfo); 1630 if (rc != OFFLOAD_SUCCESS) 1631 return OFFLOAD_FAIL; 1632 1633 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1634 } 1635 1636 int32_t __tgt_rtl_run_target_region_async(int32_t device_id, 1637 void *tgt_entry_ptr, void **tgt_args, 1638 ptrdiff_t *tgt_offsets, 1639 int32_t arg_num, 1640 __tgt_async_info *async_info_ptr) { 1641 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1642 1643 return __tgt_rtl_run_target_team_region_async( 1644 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, 1645 /* team num*/ 1, /* thread_limit */ 1, /* loop_tripcount */ 0, 1646 async_info_ptr); 1647 } 1648 1649 int32_t __tgt_rtl_synchronize(int32_t device_id, 1650 __tgt_async_info *async_info_ptr) { 1651 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1652 assert(async_info_ptr && "async_info_ptr is nullptr"); 1653 assert(async_info_ptr->Queue && "async_info_ptr->Queue is nullptr"); 1654 1655 return DeviceRTL.synchronize(device_id, async_info_ptr); 1656 } 1657 1658 void __tgt_rtl_set_info_flag(uint32_t NewInfoLevel) { 1659 std::atomic<uint32_t> &InfoLevel = getInfoLevelInternal(); 1660 InfoLevel.store(NewInfoLevel); 1661 } 1662 1663 void __tgt_rtl_print_device_info(int32_t device_id) { 1664 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1665 DeviceRTL.printDeviceInfo(device_id); 1666 } 1667 1668 int32_t __tgt_rtl_create_event(int32_t device_id, void **event) { 1669 assert(event && "event is nullptr"); 1670 return DeviceRTL.createEvent(event); 1671 } 1672 1673 int32_t __tgt_rtl_record_event(int32_t device_id, void *event_ptr, 1674 __tgt_async_info *async_info_ptr) { 1675 assert(async_info_ptr && "async_info_ptr is nullptr"); 1676 assert(async_info_ptr->Queue && "async_info_ptr->Queue is nullptr"); 1677 assert(event_ptr && "event_ptr is nullptr"); 1678 1679 return recordEvent(event_ptr, async_info_ptr); 1680 } 1681 1682 int32_t __tgt_rtl_wait_event(int32_t device_id, void *event_ptr, 1683 __tgt_async_info *async_info_ptr) { 1684 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1685 assert(async_info_ptr && "async_info_ptr is nullptr"); 1686 assert(event_ptr && "event is nullptr"); 1687 1688 return DeviceRTL.waitEvent(device_id, async_info_ptr, event_ptr); 1689 } 1690 1691 int32_t __tgt_rtl_sync_event(int32_t device_id, void *event_ptr) { 1692 assert(event_ptr && "event is nullptr"); 1693 1694 return syncEvent(event_ptr); 1695 } 1696 1697 int32_t __tgt_rtl_destroy_event(int32_t device_id, void *event_ptr) { 1698 assert(event_ptr && "event is nullptr"); 1699 1700 return DeviceRTL.destroyEvent(event_ptr); 1701 } 1702 1703 int32_t __tgt_rtl_release_async_info(int32_t device_id, 1704 __tgt_async_info *async_info) { 1705 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1706 assert(async_info && "async_info is nullptr"); 1707 1708 return DeviceRTL.releaseAsyncInfo(device_id, async_info); 1709 } 1710 1711 int32_t __tgt_rtl_init_async_info(int32_t device_id, 1712 __tgt_async_info **async_info) { 1713 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1714 assert(async_info && "async_info is nullptr"); 1715 1716 return DeviceRTL.initAsyncInfo(device_id, async_info); 1717 } 1718 1719 int32_t __tgt_rtl_init_device_info(int32_t device_id, 1720 __tgt_device_info *device_info_ptr, 1721 const char **err_str) { 1722 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1723 assert(device_info_ptr && "device_info_ptr is nullptr"); 1724 1725 return DeviceRTL.initDeviceInfo(device_id, device_info_ptr, err_str); 1726 } 1727 1728 #ifdef __cplusplus 1729 } 1730 #endif 1731