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 createEvent(void **P) { 118 CUevent Event = nullptr; 119 120 CUresult Err = cuEventCreate(&Event, CU_EVENT_DEFAULT); 121 if (Err != CUDA_SUCCESS) { 122 DP("Error when creating event event = " DPxMOD "\n", DPxPTR(Event)); 123 CUDA_ERR_STRING(Err); 124 return OFFLOAD_FAIL; 125 } 126 127 *P = Event; 128 129 return OFFLOAD_SUCCESS; 130 } 131 132 int recordEvent(void *EventPtr, __tgt_async_info *AsyncInfo) { 133 CUstream Stream = reinterpret_cast<CUstream>(AsyncInfo->Queue); 134 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 135 136 CUresult Err = cuEventRecord(Event, Stream); 137 if (Err != CUDA_SUCCESS) { 138 DP("Error when recording event. stream = " DPxMOD ", event = " DPxMOD "\n", 139 DPxPTR(Stream), DPxPTR(Event)); 140 CUDA_ERR_STRING(Err); 141 return OFFLOAD_FAIL; 142 } 143 144 return OFFLOAD_SUCCESS; 145 } 146 147 int syncEvent(void *EventPtr) { 148 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 149 150 CUresult Err = cuEventSynchronize(Event); 151 if (Err != CUDA_SUCCESS) { 152 DP("Error when syncing event = " DPxMOD "\n", DPxPTR(Event)); 153 CUDA_ERR_STRING(Err); 154 return OFFLOAD_FAIL; 155 } 156 157 return OFFLOAD_SUCCESS; 158 } 159 160 int destroyEvent(void *EventPtr) { 161 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 162 163 CUresult Err = cuEventDestroy(Event); 164 if (Err != CUDA_SUCCESS) { 165 DP("Error when destroying event = " DPxMOD "\n", DPxPTR(Event)); 166 CUDA_ERR_STRING(Err); 167 return OFFLOAD_FAIL; 168 } 169 170 return OFFLOAD_SUCCESS; 171 } 172 173 // Structure contains per-device data 174 struct DeviceDataTy { 175 /// List that contains all the kernels. 176 std::list<KernelTy> KernelsList; 177 178 std::list<FuncOrGblEntryTy> FuncGblEntries; 179 180 CUcontext Context = nullptr; 181 // Device properties 182 int ThreadsPerBlock = 0; 183 int BlocksPerGrid = 0; 184 int WarpSize = 0; 185 // OpenMP properties 186 int NumTeams = 0; 187 int NumThreads = 0; 188 }; 189 190 /// Resource allocator where \p T is the resource type. 191 /// Functions \p create and \p destroy return OFFLOAD_SUCCESS and OFFLOAD_FAIL 192 /// accordingly. The implementation should not raise any exception. 193 template <typename T> class AllocatorTy { 194 public: 195 /// Create a resource and assign to R. 196 int create(T &R) noexcept; 197 /// Destroy the resource. 198 int destroy(T) noexcept; 199 }; 200 201 /// Allocator for CUstream. 202 template <> class AllocatorTy<CUstream> { 203 CUcontext Context; 204 205 public: 206 AllocatorTy(CUcontext C) noexcept : Context(C) {} 207 208 /// See AllocatorTy<T>::create. 209 int create(CUstream &Stream) noexcept { 210 if (!checkResult(cuCtxSetCurrent(Context), 211 "Error returned from cuCtxSetCurrent\n")) 212 return OFFLOAD_FAIL; 213 214 if (!checkResult(cuStreamCreate(&Stream, CU_STREAM_NON_BLOCKING), 215 "Error returned from cuStreamCreate\n")) 216 return OFFLOAD_FAIL; 217 218 return OFFLOAD_SUCCESS; 219 } 220 221 /// See AllocatorTy<T>::destroy. 222 int destroy(CUstream Stream) noexcept { 223 if (!checkResult(cuCtxSetCurrent(Context), 224 "Error returned from cuCtxSetCurrent\n")) 225 return OFFLOAD_FAIL; 226 if (!checkResult(cuStreamDestroy(Stream), 227 "Error returned from cuStreamDestroy\n")) 228 return OFFLOAD_FAIL; 229 230 return OFFLOAD_SUCCESS; 231 } 232 }; 233 234 /// A generic pool of resources where \p T is the resource type. 235 /// \p T should be copyable as the object is stored in \p std::vector . 236 template <typename T> class ResourcePoolTy { 237 /// Index of the next available resource. 238 size_t Next = 0; 239 /// Mutex to guard the pool. 240 std::mutex Mutex; 241 /// Pool of resources. 242 std::vector<T> Resources; 243 /// A reference to the corresponding allocator. 244 AllocatorTy<T> Allocator; 245 246 /// If `Resources` is used up, we will fill in more resources. It assumes that 247 /// the new size `Size` should be always larger than the current size. 248 bool resize(size_t Size) { 249 auto CurSize = Resources.size(); 250 assert(Size > CurSize && "Unexpected smaller size"); 251 Resources.reserve(Size); 252 for (auto I = CurSize; I < Size; ++I) { 253 T NewItem; 254 int Ret = Allocator.create(NewItem); 255 if (Ret != OFFLOAD_SUCCESS) 256 return false; 257 Resources.push_back(NewItem); 258 } 259 return true; 260 } 261 262 public: 263 ResourcePoolTy(AllocatorTy<T> &&A, size_t Size = 0) noexcept 264 : Allocator(std::move(A)) { 265 (void)resize(Size); 266 } 267 268 ~ResourcePoolTy() noexcept { 269 for (auto &R : Resources) 270 (void)Allocator.destroy(R); 271 } 272 273 /// Get a resource from pool. `Next` always points to the next available 274 /// resource. That means, `[0, next-1]` have been assigned, and `[id,]` are 275 /// still available. If there is no resource left, we will ask for more. Each 276 /// time a resource is assigned, the id will increase one. 277 /// xxxxxs+++++++++ 278 /// ^ 279 /// Next 280 /// After assignment, the pool becomes the following and s is assigned. 281 /// xxxxxs+++++++++ 282 /// ^ 283 /// Next 284 int acquire(T &R) noexcept { 285 std::lock_guard<std::mutex> LG(Mutex); 286 if (Next == Resources.size() && !resize(Resources.size() * 2)) 287 return OFFLOAD_FAIL; 288 289 R = Resources[Next++]; 290 291 return OFFLOAD_SUCCESS; 292 } 293 294 /// Return the resource back to the pool. When we return a resource, we need 295 /// to first decrease `Next`, and then copy the resource back. It is worth 296 /// noting that, the order of resources return might be different from that 297 /// they're assigned, that saying, at some point, there might be two identical 298 /// resources. 299 /// xxax+a+++++ 300 /// ^ 301 /// Next 302 /// However, it doesn't matter, because they're always on the two sides of 303 /// `Next`. The left one will in the end be overwritten by another resource. 304 /// Therefore, after several execution, the order of pool might be different 305 /// from its initial state. 306 void release(T R) noexcept { 307 std::lock_guard<std::mutex> LG(Mutex); 308 Resources[--Next] = R; 309 } 310 }; 311 312 class DeviceRTLTy { 313 int NumberOfDevices; 314 // OpenMP environment properties 315 int EnvNumTeams; 316 int EnvTeamLimit; 317 int EnvTeamThreadLimit; 318 // OpenMP requires flags 319 int64_t RequiresFlags; 320 // Amount of dynamic shared memory to use at launch. 321 uint64_t DynamicMemorySize; 322 // Number of initial streams for each device. 323 int NumInitialStreams = 32; 324 325 static constexpr const int HardTeamLimit = 1U << 16U; // 64k 326 static constexpr const int HardThreadLimit = 1024; 327 static constexpr const int DefaultNumTeams = 128; 328 static constexpr const int DefaultNumThreads = 128; 329 330 using StreamPoolTy = ResourcePoolTy<CUstream>; 331 using StreamAllocatorTy = AllocatorTy<CUstream>; 332 std::vector<std::unique_ptr<StreamPoolTy>> StreamPool; 333 334 std::vector<DeviceDataTy> DeviceData; 335 std::vector<CUmodule> Modules; 336 337 /// A class responsible for interacting with device native runtime library to 338 /// allocate and free memory. 339 class CUDADeviceAllocatorTy : public DeviceAllocatorTy { 340 const int DeviceId; 341 const std::vector<DeviceDataTy> &DeviceData; 342 std::unordered_map<void *, TargetAllocTy> HostPinnedAllocs; 343 344 public: 345 CUDADeviceAllocatorTy(int DeviceId, std::vector<DeviceDataTy> &DeviceData) 346 : DeviceId(DeviceId), DeviceData(DeviceData) {} 347 348 void *allocate(size_t Size, void *, TargetAllocTy Kind) override { 349 if (Size == 0) 350 return nullptr; 351 352 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 353 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 354 return nullptr; 355 356 void *MemAlloc = nullptr; 357 switch (Kind) { 358 case TARGET_ALLOC_DEFAULT: 359 case TARGET_ALLOC_DEVICE: 360 CUdeviceptr DevicePtr; 361 Err = cuMemAlloc(&DevicePtr, Size); 362 MemAlloc = (void *)DevicePtr; 363 if (!checkResult(Err, "Error returned from cuMemAlloc\n")) 364 return nullptr; 365 break; 366 case TARGET_ALLOC_HOST: 367 void *HostPtr; 368 Err = cuMemAllocHost(&HostPtr, Size); 369 MemAlloc = HostPtr; 370 if (!checkResult(Err, "Error returned from cuMemAllocHost\n")) 371 return nullptr; 372 HostPinnedAllocs[MemAlloc] = Kind; 373 break; 374 case TARGET_ALLOC_SHARED: 375 CUdeviceptr SharedPtr; 376 Err = cuMemAllocManaged(&SharedPtr, Size, CU_MEM_ATTACH_GLOBAL); 377 MemAlloc = (void *)SharedPtr; 378 if (!checkResult(Err, "Error returned from cuMemAllocManaged\n")) 379 return nullptr; 380 break; 381 } 382 383 return MemAlloc; 384 } 385 386 int free(void *TgtPtr) override { 387 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 388 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 389 return OFFLOAD_FAIL; 390 391 // Host pinned memory must be freed differently. 392 TargetAllocTy Kind = 393 (HostPinnedAllocs.find(TgtPtr) == HostPinnedAllocs.end()) 394 ? TARGET_ALLOC_DEFAULT 395 : TARGET_ALLOC_HOST; 396 switch (Kind) { 397 case TARGET_ALLOC_DEFAULT: 398 case TARGET_ALLOC_DEVICE: 399 case TARGET_ALLOC_SHARED: 400 Err = cuMemFree((CUdeviceptr)TgtPtr); 401 if (!checkResult(Err, "Error returned from cuMemFree\n")) 402 return OFFLOAD_FAIL; 403 break; 404 case TARGET_ALLOC_HOST: 405 Err = cuMemFreeHost(TgtPtr); 406 if (!checkResult(Err, "Error returned from cuMemFreeHost\n")) 407 return OFFLOAD_FAIL; 408 break; 409 } 410 411 return OFFLOAD_SUCCESS; 412 } 413 }; 414 415 /// A vector of device allocators 416 std::vector<CUDADeviceAllocatorTy> DeviceAllocators; 417 418 /// A vector of memory managers. Since the memory manager is non-copyable and 419 // non-removable, we wrap them into std::unique_ptr. 420 std::vector<std::unique_ptr<MemoryManagerTy>> MemoryManagers; 421 422 /// Whether use memory manager 423 bool UseMemoryManager = true; 424 425 // Record entry point associated with device 426 void addOffloadEntry(const int DeviceId, const __tgt_offload_entry entry) { 427 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 428 E.Entries.push_back(entry); 429 } 430 431 // Return a pointer to the entry associated with the pointer 432 const __tgt_offload_entry *getOffloadEntry(const int DeviceId, 433 const void *Addr) const { 434 for (const __tgt_offload_entry &Itr : 435 DeviceData[DeviceId].FuncGblEntries.back().Entries) 436 if (Itr.addr == Addr) 437 return &Itr; 438 439 return nullptr; 440 } 441 442 // Return the pointer to the target entries table 443 __tgt_target_table *getOffloadEntriesTable(const int DeviceId) { 444 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 445 446 if (E.Entries.empty()) 447 return nullptr; 448 449 // Update table info according to the entries and return the pointer 450 E.Table.EntriesBegin = E.Entries.data(); 451 E.Table.EntriesEnd = E.Entries.data() + E.Entries.size(); 452 453 return &E.Table; 454 } 455 456 // Clear entries table for a device 457 void clearOffloadEntriesTable(const int DeviceId) { 458 DeviceData[DeviceId].FuncGblEntries.emplace_back(); 459 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 460 E.Entries.clear(); 461 E.Table.EntriesBegin = E.Table.EntriesEnd = nullptr; 462 } 463 464 CUstream getStream(const int DeviceId, __tgt_async_info *AsyncInfo) const { 465 assert(AsyncInfo && "AsyncInfo is nullptr"); 466 467 if (!AsyncInfo->Queue) { 468 CUstream S; 469 if (StreamPool[DeviceId]->acquire(S) != OFFLOAD_SUCCESS) 470 return nullptr; 471 472 AsyncInfo->Queue = S; 473 } 474 475 return reinterpret_cast<CUstream>(AsyncInfo->Queue); 476 } 477 478 public: 479 // This class should not be copied 480 DeviceRTLTy(const DeviceRTLTy &) = delete; 481 DeviceRTLTy(DeviceRTLTy &&) = delete; 482 483 DeviceRTLTy() 484 : NumberOfDevices(0), EnvNumTeams(-1), EnvTeamLimit(-1), 485 EnvTeamThreadLimit(-1), RequiresFlags(OMP_REQ_UNDEFINED), 486 DynamicMemorySize(0) { 487 488 DP("Start initializing CUDA\n"); 489 490 CUresult Err = cuInit(0); 491 if (Err == CUDA_ERROR_INVALID_HANDLE) { 492 // Can't call cuGetErrorString if dlsym failed 493 DP("Failed to load CUDA shared library\n"); 494 return; 495 } 496 if (!checkResult(Err, "Error returned from cuInit\n")) { 497 return; 498 } 499 500 Err = cuDeviceGetCount(&NumberOfDevices); 501 if (!checkResult(Err, "Error returned from cuDeviceGetCount\n")) 502 return; 503 504 if (NumberOfDevices == 0) { 505 DP("There are no devices supporting CUDA.\n"); 506 return; 507 } 508 509 DeviceData.resize(NumberOfDevices); 510 StreamPool.resize(NumberOfDevices); 511 512 // Get environment variables regarding teams 513 if (const char *EnvStr = getenv("OMP_TEAM_LIMIT")) { 514 // OMP_TEAM_LIMIT has been set 515 EnvTeamLimit = std::stoi(EnvStr); 516 DP("Parsed OMP_TEAM_LIMIT=%d\n", EnvTeamLimit); 517 } 518 if (const char *EnvStr = getenv("OMP_TEAMS_THREAD_LIMIT")) { 519 // OMP_TEAMS_THREAD_LIMIT has been set 520 EnvTeamThreadLimit = std::stoi(EnvStr); 521 DP("Parsed OMP_TEAMS_THREAD_LIMIT=%d\n", EnvTeamThreadLimit); 522 } 523 if (const char *EnvStr = getenv("OMP_NUM_TEAMS")) { 524 // OMP_NUM_TEAMS has been set 525 EnvNumTeams = std::stoi(EnvStr); 526 DP("Parsed OMP_NUM_TEAMS=%d\n", EnvNumTeams); 527 } 528 if (const char *EnvStr = getenv("LIBOMPTARGET_SHARED_MEMORY_SIZE")) { 529 // LIBOMPTARGET_SHARED_MEMORY_SIZE has been set 530 DynamicMemorySize = std::stoi(EnvStr); 531 DP("Parsed LIBOMPTARGET_SHARED_MEMORY_SIZE = %" PRIu64 "\n", 532 DynamicMemorySize); 533 } 534 if (const char *EnvStr = getenv("LIBOMPTARGET_NUM_INITIAL_STREAMS")) { 535 // LIBOMPTARGET_NUM_INITIAL_STREAMS has been set 536 NumInitialStreams = std::stoi(EnvStr); 537 DP("Parsed LIBOMPTARGET_NUM_INITIAL_STREAMS=%d\n", NumInitialStreams); 538 } 539 540 for (int I = 0; I < NumberOfDevices; ++I) 541 DeviceAllocators.emplace_back(I, DeviceData); 542 543 // Get the size threshold from environment variable 544 std::pair<size_t, bool> Res = MemoryManagerTy::getSizeThresholdFromEnv(); 545 UseMemoryManager = Res.second; 546 size_t MemoryManagerThreshold = Res.first; 547 548 if (UseMemoryManager) 549 for (int I = 0; I < NumberOfDevices; ++I) 550 MemoryManagers.emplace_back(std::make_unique<MemoryManagerTy>( 551 DeviceAllocators[I], MemoryManagerThreshold)); 552 } 553 554 ~DeviceRTLTy() { 555 // We first destruct memory managers in case that its dependent data are 556 // destroyed before it. 557 for (auto &M : MemoryManagers) 558 M.release(); 559 560 for (CUmodule &M : Modules) 561 // Close module 562 if (M) 563 checkResult(cuModuleUnload(M), "Error returned from cuModuleUnload\n"); 564 565 for (auto &S : StreamPool) 566 S = nullptr; 567 568 for (DeviceDataTy &D : DeviceData) { 569 // Destroy context 570 if (D.Context) { 571 checkResult(cuCtxSetCurrent(D.Context), 572 "Error returned from cuCtxSetCurrent\n"); 573 CUdevice Device; 574 checkResult(cuCtxGetDevice(&Device), 575 "Error returned from cuCtxGetDevice\n"); 576 checkResult(cuDevicePrimaryCtxRelease(Device), 577 "Error returned from cuDevicePrimaryCtxRelease\n"); 578 } 579 } 580 } 581 582 // Check whether a given DeviceId is valid 583 bool isValidDeviceId(const int DeviceId) const { 584 return DeviceId >= 0 && DeviceId < NumberOfDevices; 585 } 586 587 int getNumOfDevices() const { return NumberOfDevices; } 588 589 void setRequiresFlag(const int64_t Flags) { this->RequiresFlags = Flags; } 590 591 int initDevice(const int DeviceId) { 592 CUdevice Device; 593 594 DP("Getting device %d\n", DeviceId); 595 CUresult Err = cuDeviceGet(&Device, DeviceId); 596 if (!checkResult(Err, "Error returned from cuDeviceGet\n")) 597 return OFFLOAD_FAIL; 598 599 // Query the current flags of the primary context and set its flags if 600 // it is inactive 601 unsigned int FormerPrimaryCtxFlags = 0; 602 int FormerPrimaryCtxIsActive = 0; 603 Err = cuDevicePrimaryCtxGetState(Device, &FormerPrimaryCtxFlags, 604 &FormerPrimaryCtxIsActive); 605 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxGetState\n")) 606 return OFFLOAD_FAIL; 607 608 if (FormerPrimaryCtxIsActive) { 609 DP("The primary context is active, no change to its flags\n"); 610 if ((FormerPrimaryCtxFlags & CU_CTX_SCHED_MASK) != 611 CU_CTX_SCHED_BLOCKING_SYNC) 612 DP("Warning the current flags are not CU_CTX_SCHED_BLOCKING_SYNC\n"); 613 } else { 614 DP("The primary context is inactive, set its flags to " 615 "CU_CTX_SCHED_BLOCKING_SYNC\n"); 616 Err = cuDevicePrimaryCtxSetFlags(Device, CU_CTX_SCHED_BLOCKING_SYNC); 617 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxSetFlags\n")) 618 return OFFLOAD_FAIL; 619 } 620 621 // Retain the per device primary context and save it to use whenever this 622 // device is selected. 623 Err = cuDevicePrimaryCtxRetain(&DeviceData[DeviceId].Context, Device); 624 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxRetain\n")) 625 return OFFLOAD_FAIL; 626 627 Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 628 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 629 return OFFLOAD_FAIL; 630 631 // Initialize stream pool 632 if (!StreamPool[DeviceId]) 633 StreamPool[DeviceId] = std::make_unique<StreamPoolTy>( 634 StreamAllocatorTy(DeviceData[DeviceId].Context), NumInitialStreams); 635 636 // Query attributes to determine number of threads/block and blocks/grid. 637 int MaxGridDimX; 638 Err = cuDeviceGetAttribute(&MaxGridDimX, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X, 639 Device); 640 if (Err != CUDA_SUCCESS) { 641 DP("Error getting max grid dimension, use default value %d\n", 642 DeviceRTLTy::DefaultNumTeams); 643 DeviceData[DeviceId].BlocksPerGrid = DeviceRTLTy::DefaultNumTeams; 644 } else if (MaxGridDimX <= DeviceRTLTy::HardTeamLimit) { 645 DP("Using %d CUDA blocks per grid\n", MaxGridDimX); 646 DeviceData[DeviceId].BlocksPerGrid = MaxGridDimX; 647 } else { 648 DP("Max CUDA blocks per grid %d exceeds the hard team limit %d, capping " 649 "at the hard limit\n", 650 MaxGridDimX, DeviceRTLTy::HardTeamLimit); 651 DeviceData[DeviceId].BlocksPerGrid = DeviceRTLTy::HardTeamLimit; 652 } 653 654 // We are only exploiting threads along the x axis. 655 int MaxBlockDimX; 656 Err = cuDeviceGetAttribute(&MaxBlockDimX, 657 CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, Device); 658 if (Err != CUDA_SUCCESS) { 659 DP("Error getting max block dimension, use default value %d\n", 660 DeviceRTLTy::DefaultNumThreads); 661 DeviceData[DeviceId].ThreadsPerBlock = DeviceRTLTy::DefaultNumThreads; 662 } else { 663 DP("Using %d CUDA threads per block\n", MaxBlockDimX); 664 DeviceData[DeviceId].ThreadsPerBlock = MaxBlockDimX; 665 666 if (EnvTeamThreadLimit > 0 && 667 DeviceData[DeviceId].ThreadsPerBlock > EnvTeamThreadLimit) { 668 DP("Max CUDA threads per block %d exceeds the thread limit %d set by " 669 "OMP_TEAMS_THREAD_LIMIT, capping at the limit\n", 670 DeviceData[DeviceId].ThreadsPerBlock, EnvTeamThreadLimit); 671 DeviceData[DeviceId].ThreadsPerBlock = EnvTeamThreadLimit; 672 } 673 if (DeviceData[DeviceId].ThreadsPerBlock > DeviceRTLTy::HardThreadLimit) { 674 DP("Max CUDA threads per block %d exceeds the hard thread limit %d, " 675 "capping at the hard limit\n", 676 DeviceData[DeviceId].ThreadsPerBlock, DeviceRTLTy::HardThreadLimit); 677 DeviceData[DeviceId].ThreadsPerBlock = DeviceRTLTy::HardThreadLimit; 678 } 679 } 680 681 // Get and set warp size 682 int WarpSize; 683 Err = 684 cuDeviceGetAttribute(&WarpSize, CU_DEVICE_ATTRIBUTE_WARP_SIZE, Device); 685 if (Err != CUDA_SUCCESS) { 686 DP("Error getting warp size, assume default value 32\n"); 687 DeviceData[DeviceId].WarpSize = 32; 688 } else { 689 DP("Using warp size %d\n", WarpSize); 690 DeviceData[DeviceId].WarpSize = WarpSize; 691 } 692 693 // Adjust teams to the env variables 694 if (EnvTeamLimit > 0 && DeviceData[DeviceId].BlocksPerGrid > EnvTeamLimit) { 695 DP("Capping max CUDA blocks per grid to OMP_TEAM_LIMIT=%d\n", 696 EnvTeamLimit); 697 DeviceData[DeviceId].BlocksPerGrid = EnvTeamLimit; 698 } 699 700 size_t StackLimit; 701 size_t HeapLimit; 702 if (const char *EnvStr = getenv("LIBOMPTARGET_STACK_SIZE")) { 703 StackLimit = std::stol(EnvStr); 704 if (cuCtxSetLimit(CU_LIMIT_STACK_SIZE, StackLimit) != CUDA_SUCCESS) 705 return OFFLOAD_FAIL; 706 } else { 707 if (cuCtxGetLimit(&StackLimit, CU_LIMIT_STACK_SIZE) != CUDA_SUCCESS) 708 return OFFLOAD_FAIL; 709 } 710 if (const char *EnvStr = getenv("LIBOMPTARGET_HEAP_SIZE")) { 711 HeapLimit = std::stol(EnvStr); 712 if (cuCtxSetLimit(CU_LIMIT_MALLOC_HEAP_SIZE, HeapLimit) != CUDA_SUCCESS) 713 return OFFLOAD_FAIL; 714 } else { 715 if (cuCtxGetLimit(&HeapLimit, CU_LIMIT_MALLOC_HEAP_SIZE) != CUDA_SUCCESS) 716 return OFFLOAD_FAIL; 717 } 718 719 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 720 "Device supports up to %d CUDA blocks and %d threads with a " 721 "warp size of %d\n", 722 DeviceData[DeviceId].BlocksPerGrid, 723 DeviceData[DeviceId].ThreadsPerBlock, DeviceData[DeviceId].WarpSize); 724 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 725 "Device heap size is %d Bytes, device stack size is %d Bytes per " 726 "thread\n", 727 (int)HeapLimit, (int)StackLimit); 728 729 // Set default number of teams 730 if (EnvNumTeams > 0) { 731 DP("Default number of teams set according to environment %d\n", 732 EnvNumTeams); 733 DeviceData[DeviceId].NumTeams = EnvNumTeams; 734 } else { 735 DeviceData[DeviceId].NumTeams = DeviceRTLTy::DefaultNumTeams; 736 DP("Default number of teams set according to library's default %d\n", 737 DeviceRTLTy::DefaultNumTeams); 738 } 739 740 if (DeviceData[DeviceId].NumTeams > DeviceData[DeviceId].BlocksPerGrid) { 741 DP("Default number of teams exceeds device limit, capping at %d\n", 742 DeviceData[DeviceId].BlocksPerGrid); 743 DeviceData[DeviceId].NumTeams = DeviceData[DeviceId].BlocksPerGrid; 744 } 745 746 // Set default number of threads 747 DeviceData[DeviceId].NumThreads = DeviceRTLTy::DefaultNumThreads; 748 DP("Default number of threads set according to library's default %d\n", 749 DeviceRTLTy::DefaultNumThreads); 750 if (DeviceData[DeviceId].NumThreads > 751 DeviceData[DeviceId].ThreadsPerBlock) { 752 DP("Default number of threads exceeds device limit, capping at %d\n", 753 DeviceData[DeviceId].ThreadsPerBlock); 754 DeviceData[DeviceId].NumThreads = DeviceData[DeviceId].ThreadsPerBlock; 755 } 756 757 return OFFLOAD_SUCCESS; 758 } 759 760 __tgt_target_table *loadBinary(const int DeviceId, 761 const __tgt_device_image *Image) { 762 // Set the context we are using 763 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 764 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 765 return nullptr; 766 767 // Clear the offload table as we are going to create a new one. 768 clearOffloadEntriesTable(DeviceId); 769 770 // Create the module and extract the function pointers. 771 CUmodule Module; 772 DP("Load data from image " DPxMOD "\n", DPxPTR(Image->ImageStart)); 773 Err = cuModuleLoadDataEx(&Module, Image->ImageStart, 0, nullptr, nullptr); 774 if (!checkResult(Err, "Error returned from cuModuleLoadDataEx\n")) 775 return nullptr; 776 777 DP("CUDA module successfully loaded!\n"); 778 779 Modules.push_back(Module); 780 781 // Find the symbols in the module by name. 782 const __tgt_offload_entry *HostBegin = Image->EntriesBegin; 783 const __tgt_offload_entry *HostEnd = Image->EntriesEnd; 784 785 std::list<KernelTy> &KernelsList = DeviceData[DeviceId].KernelsList; 786 for (const __tgt_offload_entry *E = HostBegin; E != HostEnd; ++E) { 787 if (!E->addr) { 788 // We return nullptr when something like this happens, the host should 789 // have always something in the address to uniquely identify the target 790 // region. 791 DP("Invalid binary: host entry '<null>' (size = %zd)...\n", E->size); 792 return nullptr; 793 } 794 795 if (E->size) { 796 __tgt_offload_entry Entry = *E; 797 CUdeviceptr CUPtr; 798 size_t CUSize; 799 Err = cuModuleGetGlobal(&CUPtr, &CUSize, Module, E->name); 800 // We keep this style here because we need the name 801 if (Err != CUDA_SUCCESS) { 802 REPORT("Loading global '%s' Failed\n", E->name); 803 CUDA_ERR_STRING(Err); 804 return nullptr; 805 } 806 807 if (CUSize != E->size) { 808 DP("Loading global '%s' - size mismatch (%zd != %zd)\n", E->name, 809 CUSize, E->size); 810 return nullptr; 811 } 812 813 DP("Entry point " DPxMOD " maps to global %s (" DPxMOD ")\n", 814 DPxPTR(E - HostBegin), E->name, DPxPTR(CUPtr)); 815 816 Entry.addr = (void *)(CUPtr); 817 818 // Note: In the current implementation declare target variables 819 // can either be link or to. This means that once unified 820 // memory is activated via the requires directive, the variable 821 // can be used directly from the host in both cases. 822 // TODO: when variables types other than to or link are added, 823 // the below condition should be changed to explicitly 824 // check for to and link variables types: 825 // (RequiresFlags & OMP_REQ_UNIFIED_SHARED_MEMORY && (e->flags & 826 // OMP_DECLARE_TARGET_LINK || e->flags == OMP_DECLARE_TARGET_TO)) 827 if (RequiresFlags & OMP_REQ_UNIFIED_SHARED_MEMORY) { 828 // If unified memory is present any target link or to variables 829 // can access host addresses directly. There is no longer a 830 // need for device copies. 831 cuMemcpyHtoD(CUPtr, E->addr, sizeof(void *)); 832 DP("Copy linked variable host address (" DPxMOD 833 ") to device address (" DPxMOD ")\n", 834 DPxPTR(*((void **)E->addr)), DPxPTR(CUPtr)); 835 } 836 837 addOffloadEntry(DeviceId, Entry); 838 839 continue; 840 } 841 842 CUfunction Func; 843 Err = cuModuleGetFunction(&Func, Module, E->name); 844 // We keep this style here because we need the name 845 if (Err != CUDA_SUCCESS) { 846 REPORT("Loading '%s' Failed\n", E->name); 847 CUDA_ERR_STRING(Err); 848 return nullptr; 849 } 850 851 DP("Entry point " DPxMOD " maps to %s (" DPxMOD ")\n", 852 DPxPTR(E - HostBegin), E->name, DPxPTR(Func)); 853 854 // default value GENERIC (in case symbol is missing from cubin file) 855 llvm::omp::OMPTgtExecModeFlags ExecModeVal; 856 std::string ExecModeNameStr(E->name); 857 ExecModeNameStr += "_exec_mode"; 858 const char *ExecModeName = ExecModeNameStr.c_str(); 859 860 CUdeviceptr ExecModePtr; 861 size_t CUSize; 862 Err = cuModuleGetGlobal(&ExecModePtr, &CUSize, Module, ExecModeName); 863 if (Err == CUDA_SUCCESS) { 864 if (CUSize != sizeof(llvm::omp::OMPTgtExecModeFlags)) { 865 DP("Loading global exec_mode '%s' - size mismatch (%zd != %zd)\n", 866 ExecModeName, CUSize, sizeof(llvm::omp::OMPTgtExecModeFlags)); 867 return nullptr; 868 } 869 870 Err = cuMemcpyDtoH(&ExecModeVal, ExecModePtr, CUSize); 871 if (Err != CUDA_SUCCESS) { 872 REPORT("Error when copying data from device to host. Pointers: " 873 "host = " DPxMOD ", device = " DPxMOD ", size = %zd\n", 874 DPxPTR(&ExecModeVal), DPxPTR(ExecModePtr), CUSize); 875 CUDA_ERR_STRING(Err); 876 return nullptr; 877 } 878 } else { 879 DP("Loading global exec_mode '%s' - symbol missing, using default " 880 "value GENERIC (1)\n", 881 ExecModeName); 882 } 883 884 KernelsList.emplace_back(Func, ExecModeVal); 885 886 __tgt_offload_entry Entry = *E; 887 Entry.addr = &KernelsList.back(); 888 addOffloadEntry(DeviceId, Entry); 889 } 890 891 // send device environment data to the device 892 { 893 // TODO: The device ID used here is not the real device ID used by OpenMP. 894 DeviceEnvironmentTy DeviceEnv{0, static_cast<uint32_t>(NumberOfDevices), 895 static_cast<uint32_t>(DeviceId), 896 static_cast<uint32_t>(DynamicMemorySize)}; 897 898 if (const char *EnvStr = getenv("LIBOMPTARGET_DEVICE_RTL_DEBUG")) 899 DeviceEnv.DebugKind = std::stoi(EnvStr); 900 901 const char *DeviceEnvName = "omptarget_device_environment"; 902 CUdeviceptr DeviceEnvPtr; 903 size_t CUSize; 904 905 Err = cuModuleGetGlobal(&DeviceEnvPtr, &CUSize, Module, DeviceEnvName); 906 if (Err == CUDA_SUCCESS) { 907 if (CUSize != sizeof(DeviceEnv)) { 908 REPORT( 909 "Global device_environment '%s' - size mismatch (%zu != %zu)\n", 910 DeviceEnvName, CUSize, sizeof(int32_t)); 911 CUDA_ERR_STRING(Err); 912 return nullptr; 913 } 914 915 Err = cuMemcpyHtoD(DeviceEnvPtr, &DeviceEnv, CUSize); 916 if (Err != CUDA_SUCCESS) { 917 REPORT("Error when copying data from host to device. Pointers: " 918 "host = " DPxMOD ", device = " DPxMOD ", size = %zu\n", 919 DPxPTR(&DeviceEnv), DPxPTR(DeviceEnvPtr), CUSize); 920 CUDA_ERR_STRING(Err); 921 return nullptr; 922 } 923 924 DP("Sending global device environment data %zu bytes\n", CUSize); 925 } else { 926 DP("Finding global device environment '%s' - symbol missing.\n", 927 DeviceEnvName); 928 DP("Continue, considering this is a device RTL which does not accept " 929 "environment setting.\n"); 930 } 931 } 932 933 return getOffloadEntriesTable(DeviceId); 934 } 935 936 void *dataAlloc(const int DeviceId, const int64_t Size, 937 const TargetAllocTy Kind) { 938 switch (Kind) { 939 case TARGET_ALLOC_DEFAULT: 940 case TARGET_ALLOC_DEVICE: 941 if (UseMemoryManager) 942 return MemoryManagers[DeviceId]->allocate(Size, nullptr); 943 else 944 return DeviceAllocators[DeviceId].allocate(Size, nullptr, Kind); 945 case TARGET_ALLOC_HOST: 946 case TARGET_ALLOC_SHARED: 947 return DeviceAllocators[DeviceId].allocate(Size, nullptr, Kind); 948 } 949 950 REPORT("Invalid target data allocation kind or requested allocator not " 951 "implemented yet\n"); 952 953 return nullptr; 954 } 955 956 int dataSubmit(const int DeviceId, const void *TgtPtr, const void *HstPtr, 957 const int64_t Size, __tgt_async_info *AsyncInfo) const { 958 assert(AsyncInfo && "AsyncInfo is nullptr"); 959 960 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 961 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 962 return OFFLOAD_FAIL; 963 964 CUstream Stream = getStream(DeviceId, AsyncInfo); 965 966 Err = cuMemcpyHtoDAsync((CUdeviceptr)TgtPtr, HstPtr, Size, Stream); 967 if (Err != CUDA_SUCCESS) { 968 DP("Error when copying data from host to device. Pointers: host " 969 "= " DPxMOD ", device = " DPxMOD ", size = %" PRId64 "\n", 970 DPxPTR(HstPtr), DPxPTR(TgtPtr), Size); 971 CUDA_ERR_STRING(Err); 972 return OFFLOAD_FAIL; 973 } 974 975 return OFFLOAD_SUCCESS; 976 } 977 978 int dataRetrieve(const int DeviceId, void *HstPtr, const void *TgtPtr, 979 const int64_t Size, __tgt_async_info *AsyncInfo) const { 980 assert(AsyncInfo && "AsyncInfo is nullptr"); 981 982 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 983 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 984 return OFFLOAD_FAIL; 985 986 CUstream Stream = getStream(DeviceId, AsyncInfo); 987 988 Err = cuMemcpyDtoHAsync(HstPtr, (CUdeviceptr)TgtPtr, Size, Stream); 989 if (Err != CUDA_SUCCESS) { 990 DP("Error when copying data from device to host. Pointers: host " 991 "= " DPxMOD ", device = " DPxMOD ", size = %" PRId64 "\n", 992 DPxPTR(HstPtr), DPxPTR(TgtPtr), Size); 993 CUDA_ERR_STRING(Err); 994 return OFFLOAD_FAIL; 995 } 996 997 return OFFLOAD_SUCCESS; 998 } 999 1000 int dataExchange(int SrcDevId, const void *SrcPtr, int DstDevId, void *DstPtr, 1001 int64_t Size, __tgt_async_info *AsyncInfo) const { 1002 assert(AsyncInfo && "AsyncInfo is nullptr"); 1003 1004 CUresult Err = cuCtxSetCurrent(DeviceData[SrcDevId].Context); 1005 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 1006 return OFFLOAD_FAIL; 1007 1008 CUstream Stream = getStream(SrcDevId, AsyncInfo); 1009 1010 // If they are two devices, we try peer to peer copy first 1011 if (SrcDevId != DstDevId) { 1012 int CanAccessPeer = 0; 1013 Err = cuDeviceCanAccessPeer(&CanAccessPeer, SrcDevId, DstDevId); 1014 if (Err != CUDA_SUCCESS) { 1015 REPORT("Error returned from cuDeviceCanAccessPeer. src = %" PRId32 1016 ", dst = %" PRId32 "\n", 1017 SrcDevId, DstDevId); 1018 CUDA_ERR_STRING(Err); 1019 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1020 } 1021 1022 if (!CanAccessPeer) { 1023 DP("P2P memcpy not supported so fall back to D2D memcpy"); 1024 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1025 } 1026 1027 Err = cuCtxEnablePeerAccess(DeviceData[DstDevId].Context, 0); 1028 if (Err != CUDA_SUCCESS) { 1029 REPORT("Error returned from cuCtxEnablePeerAccess. src = %" PRId32 1030 ", dst = %" PRId32 "\n", 1031 SrcDevId, DstDevId); 1032 CUDA_ERR_STRING(Err); 1033 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1034 } 1035 1036 Err = cuMemcpyPeerAsync((CUdeviceptr)DstPtr, DeviceData[DstDevId].Context, 1037 (CUdeviceptr)SrcPtr, DeviceData[SrcDevId].Context, 1038 Size, Stream); 1039 if (Err == CUDA_SUCCESS) 1040 return OFFLOAD_SUCCESS; 1041 1042 DP("Error returned from cuMemcpyPeerAsync. src_ptr = " DPxMOD 1043 ", src_id =%" PRId32 ", dst_ptr = " DPxMOD ", dst_id =%" PRId32 "\n", 1044 DPxPTR(SrcPtr), SrcDevId, DPxPTR(DstPtr), DstDevId); 1045 CUDA_ERR_STRING(Err); 1046 } 1047 1048 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1049 } 1050 1051 int dataDelete(const int DeviceId, void *TgtPtr) { 1052 if (UseMemoryManager) 1053 return MemoryManagers[DeviceId]->free(TgtPtr); 1054 1055 return DeviceAllocators[DeviceId].free(TgtPtr); 1056 } 1057 1058 int runTargetTeamRegion(const int DeviceId, void *TgtEntryPtr, void **TgtArgs, 1059 ptrdiff_t *TgtOffsets, const int ArgNum, 1060 const int TeamNum, const int ThreadLimit, 1061 const unsigned int LoopTripCount, 1062 __tgt_async_info *AsyncInfo) const { 1063 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 1064 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 1065 return OFFLOAD_FAIL; 1066 1067 // All args are references. 1068 std::vector<void *> Args(ArgNum); 1069 std::vector<void *> Ptrs(ArgNum); 1070 1071 for (int I = 0; I < ArgNum; ++I) { 1072 Ptrs[I] = (void *)((intptr_t)TgtArgs[I] + TgtOffsets[I]); 1073 Args[I] = &Ptrs[I]; 1074 } 1075 1076 KernelTy *KernelInfo = reinterpret_cast<KernelTy *>(TgtEntryPtr); 1077 1078 const bool IsSPMDGenericMode = 1079 KernelInfo->ExecutionMode == llvm::omp::OMP_TGT_EXEC_MODE_GENERIC_SPMD; 1080 const bool IsSPMDMode = 1081 KernelInfo->ExecutionMode == llvm::omp::OMP_TGT_EXEC_MODE_SPMD; 1082 const bool IsGenericMode = 1083 KernelInfo->ExecutionMode == llvm::omp::OMP_TGT_EXEC_MODE_GENERIC; 1084 1085 int CudaThreadsPerBlock; 1086 if (ThreadLimit > 0) { 1087 DP("Setting CUDA threads per block to requested %d\n", ThreadLimit); 1088 CudaThreadsPerBlock = ThreadLimit; 1089 // Add master warp if necessary 1090 if (IsGenericMode) { 1091 DP("Adding master warp: +%d threads\n", DeviceData[DeviceId].WarpSize); 1092 CudaThreadsPerBlock += DeviceData[DeviceId].WarpSize; 1093 } 1094 } else { 1095 DP("Setting CUDA threads per block to default %d\n", 1096 DeviceData[DeviceId].NumThreads); 1097 CudaThreadsPerBlock = DeviceData[DeviceId].NumThreads; 1098 } 1099 1100 if (CudaThreadsPerBlock > DeviceData[DeviceId].ThreadsPerBlock) { 1101 DP("Threads per block capped at device limit %d\n", 1102 DeviceData[DeviceId].ThreadsPerBlock); 1103 CudaThreadsPerBlock = DeviceData[DeviceId].ThreadsPerBlock; 1104 } 1105 1106 if (!KernelInfo->MaxThreadsPerBlock) { 1107 Err = cuFuncGetAttribute(&KernelInfo->MaxThreadsPerBlock, 1108 CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, 1109 KernelInfo->Func); 1110 if (!checkResult(Err, "Error returned from cuFuncGetAttribute\n")) 1111 return OFFLOAD_FAIL; 1112 } 1113 1114 if (KernelInfo->MaxThreadsPerBlock < CudaThreadsPerBlock) { 1115 DP("Threads per block capped at kernel limit %d\n", 1116 KernelInfo->MaxThreadsPerBlock); 1117 CudaThreadsPerBlock = KernelInfo->MaxThreadsPerBlock; 1118 } 1119 1120 unsigned int CudaBlocksPerGrid; 1121 if (TeamNum <= 0) { 1122 if (LoopTripCount > 0 && EnvNumTeams < 0) { 1123 if (IsSPMDGenericMode) { 1124 // If we reach this point, then we are executing a kernel that was 1125 // transformed from Generic-mode to SPMD-mode. This kernel has 1126 // SPMD-mode execution, but needs its blocks to be scheduled 1127 // differently because the current loop trip count only applies to the 1128 // `teams distribute` region and will create var too few blocks using 1129 // the regular SPMD-mode method. 1130 CudaBlocksPerGrid = LoopTripCount; 1131 } else if (IsSPMDMode) { 1132 // We have a combined construct, i.e. `target teams distribute 1133 // parallel for [simd]`. We launch so many teams so that each thread 1134 // will execute one iteration of the loop. round up to the nearest 1135 // integer 1136 CudaBlocksPerGrid = ((LoopTripCount - 1) / CudaThreadsPerBlock) + 1; 1137 } else if (IsGenericMode) { 1138 // If we reach this point, then we have a non-combined construct, i.e. 1139 // `teams distribute` with a nested `parallel for` and each team is 1140 // assigned one iteration of the `distribute` loop. E.g.: 1141 // 1142 // #pragma omp target teams distribute 1143 // for(...loop_tripcount...) { 1144 // #pragma omp parallel for 1145 // for(...) {} 1146 // } 1147 // 1148 // Threads within a team will execute the iterations of the `parallel` 1149 // loop. 1150 CudaBlocksPerGrid = LoopTripCount; 1151 } else { 1152 REPORT("Unknown execution mode: %d\n", 1153 static_cast<int8_t>(KernelInfo->ExecutionMode)); 1154 return OFFLOAD_FAIL; 1155 } 1156 DP("Using %d teams due to loop trip count %" PRIu32 1157 " and number of threads per block %d\n", 1158 CudaBlocksPerGrid, LoopTripCount, CudaThreadsPerBlock); 1159 } else { 1160 DP("Using default number of teams %d\n", DeviceData[DeviceId].NumTeams); 1161 CudaBlocksPerGrid = DeviceData[DeviceId].NumTeams; 1162 } 1163 } else if (TeamNum > DeviceData[DeviceId].BlocksPerGrid) { 1164 DP("Capping number of teams to team limit %d\n", 1165 DeviceData[DeviceId].BlocksPerGrid); 1166 CudaBlocksPerGrid = DeviceData[DeviceId].BlocksPerGrid; 1167 } else { 1168 DP("Using requested number of teams %d\n", TeamNum); 1169 CudaBlocksPerGrid = TeamNum; 1170 } 1171 1172 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 1173 "Launching kernel %s with %d blocks and %d threads in %s mode\n", 1174 (getOffloadEntry(DeviceId, TgtEntryPtr)) 1175 ? getOffloadEntry(DeviceId, TgtEntryPtr)->name 1176 : "(null)", 1177 CudaBlocksPerGrid, CudaThreadsPerBlock, 1178 (!IsSPMDMode ? (IsGenericMode ? "Generic" : "SPMD-Generic") : "SPMD")); 1179 1180 CUstream Stream = getStream(DeviceId, AsyncInfo); 1181 Err = cuLaunchKernel(KernelInfo->Func, CudaBlocksPerGrid, /* gridDimY */ 1, 1182 /* gridDimZ */ 1, CudaThreadsPerBlock, 1183 /* blockDimY */ 1, /* blockDimZ */ 1, 1184 DynamicMemorySize, Stream, &Args[0], nullptr); 1185 if (!checkResult(Err, "Error returned from cuLaunchKernel\n")) 1186 return OFFLOAD_FAIL; 1187 1188 DP("Launch of entry point at " DPxMOD " successful!\n", 1189 DPxPTR(TgtEntryPtr)); 1190 1191 return OFFLOAD_SUCCESS; 1192 } 1193 1194 int synchronize(const int DeviceId, __tgt_async_info *AsyncInfo) const { 1195 CUstream Stream = reinterpret_cast<CUstream>(AsyncInfo->Queue); 1196 CUresult Err = cuStreamSynchronize(Stream); 1197 1198 // Once the stream is synchronized, return it to stream pool and reset 1199 // AsyncInfo. This is to make sure the synchronization only works for its 1200 // own tasks. 1201 StreamPool[DeviceId]->release(reinterpret_cast<CUstream>(AsyncInfo->Queue)); 1202 AsyncInfo->Queue = nullptr; 1203 1204 if (Err != CUDA_SUCCESS) { 1205 DP("Error when synchronizing stream. stream = " DPxMOD 1206 ", async info ptr = " DPxMOD "\n", 1207 DPxPTR(Stream), DPxPTR(AsyncInfo)); 1208 CUDA_ERR_STRING(Err); 1209 } 1210 return (Err == CUDA_SUCCESS) ? OFFLOAD_SUCCESS : OFFLOAD_FAIL; 1211 } 1212 1213 void printDeviceInfo(int32_t device_id) { 1214 char TmpChar[1000]; 1215 std::string TmpStr; 1216 size_t TmpSt; 1217 int TmpInt, TmpInt2, TmpInt3; 1218 1219 CUdevice Device; 1220 checkResult(cuDeviceGet(&Device, device_id), 1221 "Error returned from cuCtxGetDevice\n"); 1222 1223 cuDriverGetVersion(&TmpInt); 1224 printf(" CUDA Driver Version: \t\t%d \n", TmpInt); 1225 printf(" CUDA Device Number: \t\t%d \n", device_id); 1226 checkResult(cuDeviceGetName(TmpChar, 1000, Device), 1227 "Error returned from cuDeviceGetName\n"); 1228 printf(" Device Name: \t\t\t%s \n", TmpChar); 1229 checkResult(cuDeviceTotalMem(&TmpSt, Device), 1230 "Error returned from cuDeviceTotalMem\n"); 1231 printf(" Global Memory Size: \t\t%zu bytes \n", TmpSt); 1232 checkResult(cuDeviceGetAttribute( 1233 &TmpInt, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, Device), 1234 "Error returned from cuDeviceGetAttribute\n"); 1235 printf(" Number of Multiprocessors: \t\t%d \n", TmpInt); 1236 checkResult( 1237 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_GPU_OVERLAP, Device), 1238 "Error returned from cuDeviceGetAttribute\n"); 1239 printf(" Concurrent Copy and Execution: \t%s \n", BOOL2TEXT(TmpInt)); 1240 checkResult(cuDeviceGetAttribute( 1241 &TmpInt, CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY, Device), 1242 "Error returned from cuDeviceGetAttribute\n"); 1243 printf(" Total Constant Memory: \t\t%d bytes\n", TmpInt); 1244 checkResult( 1245 cuDeviceGetAttribute( 1246 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK, Device), 1247 "Error returned from cuDeviceGetAttribute\n"); 1248 printf(" Max Shared Memory per Block: \t%d bytes \n", TmpInt); 1249 checkResult( 1250 cuDeviceGetAttribute( 1251 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK, Device), 1252 "Error returned from cuDeviceGetAttribute\n"); 1253 printf(" Registers per Block: \t\t%d \n", TmpInt); 1254 checkResult( 1255 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_WARP_SIZE, Device), 1256 "Error returned from cuDeviceGetAttribute\n"); 1257 printf(" Warp Size: \t\t\t\t%d Threads \n", TmpInt); 1258 checkResult(cuDeviceGetAttribute( 1259 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK, Device), 1260 "Error returned from cuDeviceGetAttribute\n"); 1261 printf(" Maximum Threads per Block: \t\t%d \n", TmpInt); 1262 checkResult(cuDeviceGetAttribute( 1263 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, Device), 1264 "Error returned from cuDeviceGetAttribute\n"); 1265 checkResult(cuDeviceGetAttribute( 1266 &TmpInt2, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y, Device), 1267 "Error returned from cuDeviceGetAttribute\n"); 1268 checkResult(cuDeviceGetAttribute( 1269 &TmpInt3, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z, Device), 1270 "Error returned from cuDeviceGetAttribute\n"); 1271 printf(" Maximum Block Dimensions: \t\t%d, %d, %d \n", TmpInt, TmpInt2, 1272 TmpInt3); 1273 checkResult(cuDeviceGetAttribute( 1274 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X, Device), 1275 "Error returned from cuDeviceGetAttribute\n"); 1276 checkResult(cuDeviceGetAttribute( 1277 &TmpInt2, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y, Device), 1278 "Error returned from cuDeviceGetAttribute\n"); 1279 checkResult(cuDeviceGetAttribute( 1280 &TmpInt3, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z, Device), 1281 "Error returned from cuDeviceGetAttribute\n"); 1282 printf(" Maximum Grid Dimensions: \t\t%d x %d x %d \n", TmpInt, TmpInt2, 1283 TmpInt3); 1284 checkResult( 1285 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_MAX_PITCH, Device), 1286 "Error returned from cuDeviceGetAttribute\n"); 1287 printf(" Maximum Memory Pitch: \t\t%d bytes \n", TmpInt); 1288 checkResult(cuDeviceGetAttribute( 1289 &TmpInt, CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT, Device), 1290 "Error returned from cuDeviceGetAttribute\n"); 1291 printf(" Texture Alignment: \t\t\t%d bytes \n", TmpInt); 1292 checkResult( 1293 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, Device), 1294 "Error returned from cuDeviceGetAttribute\n"); 1295 printf(" Clock Rate: \t\t\t%d kHz\n", TmpInt); 1296 checkResult(cuDeviceGetAttribute( 1297 &TmpInt, CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT, Device), 1298 "Error returned from cuDeviceGetAttribute\n"); 1299 printf(" Execution Timeout: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1300 checkResult( 1301 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_INTEGRATED, Device), 1302 "Error returned from cuDeviceGetAttribute\n"); 1303 printf(" Integrated Device: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1304 checkResult(cuDeviceGetAttribute( 1305 &TmpInt, CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY, Device), 1306 "Error returned from cuDeviceGetAttribute\n"); 1307 printf(" Can Map Host Memory: \t\t%s \n", BOOL2TEXT(TmpInt)); 1308 checkResult( 1309 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_COMPUTE_MODE, Device), 1310 "Error returned from cuDeviceGetAttribute\n"); 1311 if (TmpInt == CU_COMPUTEMODE_DEFAULT) 1312 TmpStr = "DEFAULT"; 1313 else if (TmpInt == CU_COMPUTEMODE_PROHIBITED) 1314 TmpStr = "PROHIBITED"; 1315 else if (TmpInt == CU_COMPUTEMODE_EXCLUSIVE_PROCESS) 1316 TmpStr = "EXCLUSIVE PROCESS"; 1317 else 1318 TmpStr = "unknown"; 1319 printf(" Compute Mode: \t\t\t%s \n", TmpStr.c_str()); 1320 checkResult(cuDeviceGetAttribute( 1321 &TmpInt, CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS, Device), 1322 "Error returned from cuDeviceGetAttribute\n"); 1323 printf(" Concurrent Kernels: \t\t%s \n", BOOL2TEXT(TmpInt)); 1324 checkResult( 1325 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_ECC_ENABLED, Device), 1326 "Error returned from cuDeviceGetAttribute\n"); 1327 printf(" ECC Enabled: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1328 checkResult(cuDeviceGetAttribute( 1329 &TmpInt, CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE, Device), 1330 "Error returned from cuDeviceGetAttribute\n"); 1331 printf(" Memory Clock Rate: \t\t\t%d kHz\n", TmpInt); 1332 checkResult( 1333 cuDeviceGetAttribute( 1334 &TmpInt, CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH, Device), 1335 "Error returned from cuDeviceGetAttribute\n"); 1336 printf(" Memory Bus Width: \t\t\t%d bits\n", TmpInt); 1337 checkResult(cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE, 1338 Device), 1339 "Error returned from cuDeviceGetAttribute\n"); 1340 printf(" L2 Cache Size: \t\t\t%d bytes \n", TmpInt); 1341 checkResult(cuDeviceGetAttribute( 1342 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_MULTIPROCESSOR, 1343 Device), 1344 "Error returned from cuDeviceGetAttribute\n"); 1345 printf(" Max Threads Per SMP: \t\t%d \n", TmpInt); 1346 checkResult(cuDeviceGetAttribute( 1347 &TmpInt, CU_DEVICE_ATTRIBUTE_ASYNC_ENGINE_COUNT, Device), 1348 "Error returned from cuDeviceGetAttribute\n"); 1349 printf(" Async Engines: \t\t\t%s (%d) \n", BOOL2TEXT(TmpInt), TmpInt); 1350 checkResult(cuDeviceGetAttribute( 1351 &TmpInt, CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING, Device), 1352 "Error returned from cuDeviceGetAttribute\n"); 1353 printf(" Unified Addressing: \t\t%s \n", BOOL2TEXT(TmpInt)); 1354 checkResult(cuDeviceGetAttribute( 1355 &TmpInt, CU_DEVICE_ATTRIBUTE_MANAGED_MEMORY, Device), 1356 "Error returned from cuDeviceGetAttribute\n"); 1357 printf(" Managed Memory: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1358 checkResult( 1359 cuDeviceGetAttribute( 1360 &TmpInt, CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS, Device), 1361 "Error returned from cuDeviceGetAttribute\n"); 1362 printf(" Concurrent Managed Memory: \t\t%s \n", BOOL2TEXT(TmpInt)); 1363 checkResult( 1364 cuDeviceGetAttribute( 1365 &TmpInt, CU_DEVICE_ATTRIBUTE_COMPUTE_PREEMPTION_SUPPORTED, Device), 1366 "Error returned from cuDeviceGetAttribute\n"); 1367 printf(" Preemption Supported: \t\t%s \n", BOOL2TEXT(TmpInt)); 1368 checkResult(cuDeviceGetAttribute( 1369 &TmpInt, CU_DEVICE_ATTRIBUTE_COOPERATIVE_LAUNCH, Device), 1370 "Error returned from cuDeviceGetAttribute\n"); 1371 printf(" Cooperative Launch: \t\t%s \n", BOOL2TEXT(TmpInt)); 1372 checkResult(cuDeviceGetAttribute( 1373 &TmpInt, CU_DEVICE_ATTRIBUTE_MULTI_GPU_BOARD, Device), 1374 "Error returned from cuDeviceGetAttribute\n"); 1375 printf(" Multi-Device Boars: \t\t%s \n", BOOL2TEXT(TmpInt)); 1376 checkResult( 1377 cuDeviceGetAttribute( 1378 &TmpInt, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, Device), 1379 "Error returned from cuDeviceGetAttribute\n"); 1380 checkResult( 1381 cuDeviceGetAttribute( 1382 &TmpInt2, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, Device), 1383 "Error returned from cuDeviceGetAttribute\n"); 1384 printf(" Compute Capabilities: \t\t%d%d \n", TmpInt, TmpInt2); 1385 } 1386 1387 int waitEvent(const int DeviceId, __tgt_async_info *AsyncInfo, 1388 void *EventPtr) const { 1389 CUstream Stream = getStream(DeviceId, AsyncInfo); 1390 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 1391 1392 // We don't use CU_EVENT_WAIT_DEFAULT here as it is only available from 1393 // specific CUDA version, and defined as 0x0. In previous version, per CUDA 1394 // API document, that argument has to be 0x0. 1395 CUresult Err = cuStreamWaitEvent(Stream, Event, 0); 1396 if (Err != CUDA_SUCCESS) { 1397 DP("Error when waiting event. stream = " DPxMOD ", event = " DPxMOD "\n", 1398 DPxPTR(Stream), DPxPTR(Event)); 1399 CUDA_ERR_STRING(Err); 1400 return OFFLOAD_FAIL; 1401 } 1402 1403 return OFFLOAD_SUCCESS; 1404 } 1405 }; 1406 1407 DeviceRTLTy DeviceRTL; 1408 } // namespace 1409 1410 // Exposed library API function 1411 #ifdef __cplusplus 1412 extern "C" { 1413 #endif 1414 1415 int32_t __tgt_rtl_is_valid_binary(__tgt_device_image *image) { 1416 return elf_check_machine(image, /* EM_CUDA */ 190); 1417 } 1418 1419 int32_t __tgt_rtl_number_of_devices() { return DeviceRTL.getNumOfDevices(); } 1420 1421 int64_t __tgt_rtl_init_requires(int64_t RequiresFlags) { 1422 DP("Init requires flags to %" PRId64 "\n", RequiresFlags); 1423 DeviceRTL.setRequiresFlag(RequiresFlags); 1424 return RequiresFlags; 1425 } 1426 1427 int32_t __tgt_rtl_is_data_exchangable(int32_t src_dev_id, int dst_dev_id) { 1428 if (DeviceRTL.isValidDeviceId(src_dev_id) && 1429 DeviceRTL.isValidDeviceId(dst_dev_id)) 1430 return 1; 1431 1432 return 0; 1433 } 1434 1435 int32_t __tgt_rtl_init_device(int32_t device_id) { 1436 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1437 1438 return DeviceRTL.initDevice(device_id); 1439 } 1440 1441 __tgt_target_table *__tgt_rtl_load_binary(int32_t device_id, 1442 __tgt_device_image *image) { 1443 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1444 1445 return DeviceRTL.loadBinary(device_id, image); 1446 } 1447 1448 void *__tgt_rtl_data_alloc(int32_t device_id, int64_t size, void *, 1449 int32_t kind) { 1450 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1451 1452 return DeviceRTL.dataAlloc(device_id, size, (TargetAllocTy)kind); 1453 } 1454 1455 int32_t __tgt_rtl_data_submit(int32_t device_id, void *tgt_ptr, void *hst_ptr, 1456 int64_t size) { 1457 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1458 1459 __tgt_async_info AsyncInfo; 1460 const int32_t rc = __tgt_rtl_data_submit_async(device_id, tgt_ptr, hst_ptr, 1461 size, &AsyncInfo); 1462 if (rc != OFFLOAD_SUCCESS) 1463 return OFFLOAD_FAIL; 1464 1465 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1466 } 1467 1468 int32_t __tgt_rtl_data_submit_async(int32_t device_id, void *tgt_ptr, 1469 void *hst_ptr, int64_t size, 1470 __tgt_async_info *async_info_ptr) { 1471 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1472 assert(async_info_ptr && "async_info_ptr is nullptr"); 1473 1474 return DeviceRTL.dataSubmit(device_id, tgt_ptr, hst_ptr, size, 1475 async_info_ptr); 1476 } 1477 1478 int32_t __tgt_rtl_data_retrieve(int32_t device_id, void *hst_ptr, void *tgt_ptr, 1479 int64_t size) { 1480 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1481 1482 __tgt_async_info AsyncInfo; 1483 const int32_t rc = __tgt_rtl_data_retrieve_async(device_id, hst_ptr, tgt_ptr, 1484 size, &AsyncInfo); 1485 if (rc != OFFLOAD_SUCCESS) 1486 return OFFLOAD_FAIL; 1487 1488 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1489 } 1490 1491 int32_t __tgt_rtl_data_retrieve_async(int32_t device_id, void *hst_ptr, 1492 void *tgt_ptr, int64_t size, 1493 __tgt_async_info *async_info_ptr) { 1494 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1495 assert(async_info_ptr && "async_info_ptr is nullptr"); 1496 1497 return DeviceRTL.dataRetrieve(device_id, hst_ptr, tgt_ptr, size, 1498 async_info_ptr); 1499 } 1500 1501 int32_t __tgt_rtl_data_exchange_async(int32_t src_dev_id, void *src_ptr, 1502 int dst_dev_id, void *dst_ptr, 1503 int64_t size, 1504 __tgt_async_info *AsyncInfo) { 1505 assert(DeviceRTL.isValidDeviceId(src_dev_id) && "src_dev_id is invalid"); 1506 assert(DeviceRTL.isValidDeviceId(dst_dev_id) && "dst_dev_id is invalid"); 1507 assert(AsyncInfo && "AsyncInfo is nullptr"); 1508 1509 return DeviceRTL.dataExchange(src_dev_id, src_ptr, dst_dev_id, dst_ptr, size, 1510 AsyncInfo); 1511 } 1512 1513 int32_t __tgt_rtl_data_exchange(int32_t src_dev_id, void *src_ptr, 1514 int32_t dst_dev_id, void *dst_ptr, 1515 int64_t size) { 1516 assert(DeviceRTL.isValidDeviceId(src_dev_id) && "src_dev_id is invalid"); 1517 assert(DeviceRTL.isValidDeviceId(dst_dev_id) && "dst_dev_id is invalid"); 1518 1519 __tgt_async_info AsyncInfo; 1520 const int32_t rc = __tgt_rtl_data_exchange_async( 1521 src_dev_id, src_ptr, dst_dev_id, dst_ptr, size, &AsyncInfo); 1522 if (rc != OFFLOAD_SUCCESS) 1523 return OFFLOAD_FAIL; 1524 1525 return __tgt_rtl_synchronize(src_dev_id, &AsyncInfo); 1526 } 1527 1528 int32_t __tgt_rtl_data_delete(int32_t device_id, void *tgt_ptr) { 1529 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1530 1531 return DeviceRTL.dataDelete(device_id, tgt_ptr); 1532 } 1533 1534 int32_t __tgt_rtl_run_target_team_region(int32_t device_id, void *tgt_entry_ptr, 1535 void **tgt_args, 1536 ptrdiff_t *tgt_offsets, 1537 int32_t arg_num, int32_t team_num, 1538 int32_t thread_limit, 1539 uint64_t loop_tripcount) { 1540 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1541 1542 __tgt_async_info AsyncInfo; 1543 const int32_t rc = __tgt_rtl_run_target_team_region_async( 1544 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, team_num, 1545 thread_limit, loop_tripcount, &AsyncInfo); 1546 if (rc != OFFLOAD_SUCCESS) 1547 return OFFLOAD_FAIL; 1548 1549 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1550 } 1551 1552 int32_t __tgt_rtl_run_target_team_region_async( 1553 int32_t device_id, void *tgt_entry_ptr, void **tgt_args, 1554 ptrdiff_t *tgt_offsets, int32_t arg_num, int32_t team_num, 1555 int32_t thread_limit, uint64_t loop_tripcount, 1556 __tgt_async_info *async_info_ptr) { 1557 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1558 1559 return DeviceRTL.runTargetTeamRegion( 1560 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, team_num, 1561 thread_limit, loop_tripcount, async_info_ptr); 1562 } 1563 1564 int32_t __tgt_rtl_run_target_region(int32_t device_id, void *tgt_entry_ptr, 1565 void **tgt_args, ptrdiff_t *tgt_offsets, 1566 int32_t arg_num) { 1567 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1568 1569 __tgt_async_info AsyncInfo; 1570 const int32_t rc = __tgt_rtl_run_target_region_async( 1571 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, &AsyncInfo); 1572 if (rc != OFFLOAD_SUCCESS) 1573 return OFFLOAD_FAIL; 1574 1575 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1576 } 1577 1578 int32_t __tgt_rtl_run_target_region_async(int32_t device_id, 1579 void *tgt_entry_ptr, void **tgt_args, 1580 ptrdiff_t *tgt_offsets, 1581 int32_t arg_num, 1582 __tgt_async_info *async_info_ptr) { 1583 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1584 1585 return __tgt_rtl_run_target_team_region_async( 1586 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, 1587 /* team num*/ 1, /* thread_limit */ 1, /* loop_tripcount */ 0, 1588 async_info_ptr); 1589 } 1590 1591 int32_t __tgt_rtl_synchronize(int32_t device_id, 1592 __tgt_async_info *async_info_ptr) { 1593 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1594 assert(async_info_ptr && "async_info_ptr is nullptr"); 1595 assert(async_info_ptr->Queue && "async_info_ptr->Queue is nullptr"); 1596 1597 return DeviceRTL.synchronize(device_id, async_info_ptr); 1598 } 1599 1600 void __tgt_rtl_set_info_flag(uint32_t NewInfoLevel) { 1601 std::atomic<uint32_t> &InfoLevel = getInfoLevelInternal(); 1602 InfoLevel.store(NewInfoLevel); 1603 } 1604 1605 void __tgt_rtl_print_device_info(int32_t device_id) { 1606 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1607 DeviceRTL.printDeviceInfo(device_id); 1608 } 1609 1610 int32_t __tgt_rtl_create_event(int32_t device_id, void **event) { 1611 assert(event && "event is nullptr"); 1612 return createEvent(event); 1613 } 1614 1615 int32_t __tgt_rtl_record_event(int32_t device_id, void *event_ptr, 1616 __tgt_async_info *async_info_ptr) { 1617 assert(async_info_ptr && "async_info_ptr is nullptr"); 1618 assert(async_info_ptr->Queue && "async_info_ptr->Queue is nullptr"); 1619 assert(event_ptr && "event_ptr is nullptr"); 1620 1621 return recordEvent(event_ptr, async_info_ptr); 1622 } 1623 1624 int32_t __tgt_rtl_wait_event(int32_t device_id, void *event_ptr, 1625 __tgt_async_info *async_info_ptr) { 1626 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1627 assert(async_info_ptr && "async_info_ptr is nullptr"); 1628 assert(event_ptr && "event is nullptr"); 1629 1630 return DeviceRTL.waitEvent(device_id, async_info_ptr, event_ptr); 1631 } 1632 1633 int32_t __tgt_rtl_sync_event(int32_t device_id, void *event_ptr) { 1634 assert(event_ptr && "event is nullptr"); 1635 1636 return syncEvent(event_ptr); 1637 } 1638 1639 int32_t __tgt_rtl_destroy_event(int32_t device_id, void *event_ptr) { 1640 assert(event_ptr && "event is nullptr"); 1641 1642 return destroyEvent(event_ptr); 1643 } 1644 1645 #ifdef __cplusplus 1646 } 1647 #endif 1648