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 <algorithm> 14 #include <cassert> 15 #include <cstddef> 16 #include <cuda.h> 17 #include <list> 18 #include <memory> 19 #include <mutex> 20 #include <string> 21 #include <unordered_map> 22 #include <vector> 23 24 #include "Debug.h" 25 #include "DeviceEnvironment.h" 26 #include "omptarget.h" 27 #include "omptargetplugin.h" 28 29 #define TARGET_NAME CUDA 30 #define DEBUG_PREFIX "Target " GETNAME(TARGET_NAME) " RTL" 31 32 #include "MemoryManager.h" 33 34 #include "llvm/Frontend/OpenMP/OMPConstants.h" 35 36 // Utility for retrieving and printing CUDA error string. 37 #ifdef OMPTARGET_DEBUG 38 #define CUDA_ERR_STRING(err) \ 39 do { \ 40 if (getDebugLevel() > 0) { \ 41 const char *errStr = nullptr; \ 42 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 43 if (errStr_status == CUDA_ERROR_INVALID_VALUE) \ 44 REPORT("Unrecognized CUDA error code: %d\n", err); \ 45 else if (errStr_status == CUDA_SUCCESS) \ 46 REPORT("CUDA error is: %s\n", errStr); \ 47 else { \ 48 REPORT("Unresolved CUDA error code: %d\n", err); \ 49 REPORT("Unsuccessful cuGetErrorString return status: %d\n", \ 50 errStr_status); \ 51 } \ 52 } else { \ 53 const char *errStr = nullptr; \ 54 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 55 if (errStr_status == CUDA_SUCCESS) \ 56 REPORT("%s \n", errStr); \ 57 } \ 58 } while (false) 59 #else // OMPTARGET_DEBUG 60 #define CUDA_ERR_STRING(err) \ 61 do { \ 62 const char *errStr = nullptr; \ 63 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 64 if (errStr_status == CUDA_SUCCESS) \ 65 REPORT("%s \n", errStr); \ 66 } while (false) 67 #endif // OMPTARGET_DEBUG 68 69 #define BOOL2TEXT(b) ((b) ? "Yes" : "No") 70 71 #include "elf_common.h" 72 73 /// Keep entries table per device. 74 struct FuncOrGblEntryTy { 75 __tgt_target_table Table; 76 std::vector<__tgt_offload_entry> Entries; 77 }; 78 79 /// Use a single entity to encode a kernel and a set of flags. 80 struct KernelTy { 81 CUfunction Func; 82 83 // execution mode of kernel 84 llvm::omp::OMPTgtExecModeFlags ExecutionMode; 85 86 /// Maximal number of threads per block for this kernel. 87 int MaxThreadsPerBlock = 0; 88 89 KernelTy(CUfunction _Func, llvm::omp::OMPTgtExecModeFlags _ExecutionMode) 90 : Func(_Func), ExecutionMode(_ExecutionMode) {} 91 }; 92 93 namespace { 94 bool checkResult(CUresult Err, const char *ErrMsg) { 95 if (Err == CUDA_SUCCESS) 96 return true; 97 98 REPORT("%s", ErrMsg); 99 CUDA_ERR_STRING(Err); 100 return false; 101 } 102 103 int memcpyDtoD(const void *SrcPtr, void *DstPtr, int64_t Size, 104 CUstream Stream) { 105 CUresult Err = 106 cuMemcpyDtoDAsync((CUdeviceptr)DstPtr, (CUdeviceptr)SrcPtr, Size, Stream); 107 108 if (Err != CUDA_SUCCESS) { 109 DP("Error when copying data from device to device. Pointers: src " 110 "= " DPxMOD ", dst = " DPxMOD ", size = %" PRId64 "\n", 111 DPxPTR(SrcPtr), DPxPTR(DstPtr), Size); 112 CUDA_ERR_STRING(Err); 113 return OFFLOAD_FAIL; 114 } 115 116 return OFFLOAD_SUCCESS; 117 } 118 119 int recordEvent(void *EventPtr, __tgt_async_info *AsyncInfo) { 120 CUstream Stream = reinterpret_cast<CUstream>(AsyncInfo->Queue); 121 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 122 123 CUresult Err = cuEventRecord(Event, Stream); 124 if (Err != CUDA_SUCCESS) { 125 DP("Error when recording event. stream = " DPxMOD ", event = " DPxMOD "\n", 126 DPxPTR(Stream), DPxPTR(Event)); 127 CUDA_ERR_STRING(Err); 128 return OFFLOAD_FAIL; 129 } 130 131 return OFFLOAD_SUCCESS; 132 } 133 134 int syncEvent(void *EventPtr) { 135 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 136 137 CUresult Err = cuEventSynchronize(Event); 138 if (Err != CUDA_SUCCESS) { 139 DP("Error when syncing event = " DPxMOD "\n", DPxPTR(Event)); 140 CUDA_ERR_STRING(Err); 141 return OFFLOAD_FAIL; 142 } 143 144 return OFFLOAD_SUCCESS; 145 } 146 147 namespace { 148 149 // Structure contains per-device data 150 struct DeviceDataTy { 151 /// List that contains all the kernels. 152 std::list<KernelTy> KernelsList; 153 154 std::list<FuncOrGblEntryTy> FuncGblEntries; 155 156 CUcontext Context = nullptr; 157 // Device properties 158 int ThreadsPerBlock = 0; 159 int BlocksPerGrid = 0; 160 int WarpSize = 0; 161 // OpenMP properties 162 int NumTeams = 0; 163 int NumThreads = 0; 164 }; 165 166 /// Resource allocator where \p T is the resource type. 167 /// Functions \p create and \p destroy return OFFLOAD_SUCCESS and OFFLOAD_FAIL 168 /// accordingly. The implementation should not raise any exception. 169 template <typename T> struct AllocatorTy { 170 using ElementTy = T; 171 /// Create a resource and assign to R. 172 virtual int create(T &R) noexcept = 0; 173 /// Destroy the resource. 174 virtual int destroy(T) noexcept = 0; 175 }; 176 177 /// Allocator for CUstream. 178 struct StreamAllocatorTy final : public AllocatorTy<CUstream> { 179 /// See AllocatorTy<T>::create. 180 int create(CUstream &Stream) noexcept override { 181 if (!checkResult(cuStreamCreate(&Stream, CU_STREAM_NON_BLOCKING), 182 "Error returned from cuStreamCreate\n")) 183 return OFFLOAD_FAIL; 184 185 return OFFLOAD_SUCCESS; 186 } 187 188 /// See AllocatorTy<T>::destroy. 189 int destroy(CUstream Stream) noexcept override { 190 if (!checkResult(cuStreamDestroy(Stream), 191 "Error returned from cuStreamDestroy\n")) 192 return OFFLOAD_FAIL; 193 194 return OFFLOAD_SUCCESS; 195 } 196 }; 197 198 /// Allocator for CUevent. 199 struct EventAllocatorTy final : public AllocatorTy<CUevent> { 200 /// See AllocatorTy<T>::create. 201 int create(CUevent &Event) noexcept override { 202 if (!checkResult(cuEventCreate(&Event, CU_EVENT_DEFAULT), 203 "Error returned from cuEventCreate\n")) 204 return OFFLOAD_FAIL; 205 206 return OFFLOAD_SUCCESS; 207 } 208 209 /// See AllocatorTy<T>::destroy. 210 int destroy(CUevent Event) noexcept override { 211 if (!checkResult(cuEventDestroy(Event), 212 "Error returned from cuEventDestroy\n")) 213 return OFFLOAD_FAIL; 214 215 return OFFLOAD_SUCCESS; 216 } 217 }; 218 219 /// A generic pool of resources where \p T is the resource type. 220 /// \p T should be copyable as the object is stored in \p std::vector . 221 template <typename AllocTy> class ResourcePoolTy { 222 using ElementTy = typename AllocTy::ElementTy; 223 /// Index of the next available resource. 224 size_t Next = 0; 225 /// Mutex to guard the pool. 226 std::mutex Mutex; 227 /// Pool of resources. The difference between \p Resources and \p Pool is, 228 /// when a resource is acquired and released, it is all on \p Resources. When 229 /// a batch of new resources are needed, they are both added to \p Resources 230 /// and \p Pool. The reason for this setting is, \p Resources could contain 231 /// redundant elements because resources are not released, which can cause 232 /// double free. This setting makes sure that \p Pool always has every 233 /// resource allocated from the device. 234 std::vector<ElementTy> Resources; 235 std::vector<ElementTy> Pool; 236 /// A reference to the corresponding allocator. 237 AllocTy Allocator; 238 239 /// If `Resources` is used up, we will fill in more resources. It assumes that 240 /// the new size `Size` should be always larger than the current size. 241 bool resize(size_t Size) { 242 assert(Resources.size() == Pool.size() && "size mismatch"); 243 auto CurSize = Resources.size(); 244 assert(Size > CurSize && "Unexpected smaller size"); 245 Pool.reserve(Size); 246 Resources.reserve(Size); 247 for (auto I = CurSize; I < Size; ++I) { 248 ElementTy NewItem; 249 int Ret = Allocator.create(NewItem); 250 if (Ret != OFFLOAD_SUCCESS) 251 return false; 252 Pool.push_back(NewItem); 253 Resources.push_back(NewItem); 254 } 255 return true; 256 } 257 258 public: 259 ResourcePoolTy(AllocTy &&A, size_t Size = 0) noexcept 260 : Allocator(std::move(A)) { 261 if (Size) 262 (void)resize(Size); 263 } 264 265 ~ResourcePoolTy() noexcept { clear(); } 266 267 /// Get a resource from pool. `Next` always points to the next available 268 /// resource. That means, `[0, next-1]` have been assigned, and `[id,]` are 269 /// still available. If there is no resource left, we will ask for more. Each 270 /// time a resource is assigned, the id will increase one. 271 /// xxxxxs+++++++++ 272 /// ^ 273 /// Next 274 /// After assignment, the pool becomes the following and s is assigned. 275 /// xxxxxs+++++++++ 276 /// ^ 277 /// Next 278 int acquire(ElementTy &R) noexcept { 279 std::lock_guard<std::mutex> LG(Mutex); 280 if (Next == Resources.size()) { 281 auto NewSize = Resources.size() ? Resources.size() * 2 : 1; 282 if (!resize(NewSize)) 283 return OFFLOAD_FAIL; 284 } 285 286 assert(Next < Resources.size()); 287 288 R = Resources[Next++]; 289 290 return OFFLOAD_SUCCESS; 291 } 292 293 /// Return the resource back to the pool. When we return a resource, we need 294 /// to first decrease `Next`, and then copy the resource back. It is worth 295 /// noting that, the order of resources return might be different from that 296 /// they're assigned, that saying, at some point, there might be two identical 297 /// resources. 298 /// xxax+a+++++ 299 /// ^ 300 /// Next 301 /// However, it doesn't matter, because they're always on the two sides of 302 /// `Next`. The left one will in the end be overwritten by another resource. 303 /// Therefore, after several execution, the order of pool might be different 304 /// from its initial state. 305 void release(ElementTy R) noexcept { 306 std::lock_guard<std::mutex> LG(Mutex); 307 Resources[--Next] = R; 308 } 309 310 /// Released all stored resources and clear the pool. 311 /// Note: This function is not thread safe. Be sure to guard it if necessary. 312 void clear() noexcept { 313 for (auto &R : Pool) 314 (void)Allocator.destroy(R); 315 Pool.clear(); 316 Resources.clear(); 317 } 318 }; 319 320 } // namespace 321 322 class DeviceRTLTy { 323 int NumberOfDevices; 324 // OpenMP environment properties 325 int EnvNumTeams; 326 int EnvTeamLimit; 327 int EnvTeamThreadLimit; 328 // OpenMP requires flags 329 int64_t RequiresFlags; 330 // Amount of dynamic shared memory to use at launch. 331 uint64_t DynamicMemorySize; 332 333 /// Number of initial streams for each device. 334 int NumInitialStreams = 32; 335 336 /// Number of initial events for each device. 337 int NumInitialEvents = 8; 338 339 static constexpr const int32_t HardThreadLimit = 1024; 340 static constexpr const int32_t DefaultNumTeams = 128; 341 static constexpr const int32_t DefaultNumThreads = 128; 342 343 using StreamPoolTy = ResourcePoolTy<StreamAllocatorTy>; 344 std::vector<std::unique_ptr<StreamPoolTy>> StreamPool; 345 346 using EventPoolTy = ResourcePoolTy<EventAllocatorTy>; 347 std::vector<std::unique_ptr<EventPoolTy>> EventPool; 348 349 std::vector<DeviceDataTy> DeviceData; 350 std::vector<std::vector<CUmodule>> Modules; 351 352 /// Vector of flags indicating the initalization status of all associated 353 /// devices. 354 std::vector<bool> InitializedFlags; 355 356 /// A class responsible for interacting with device native runtime library to 357 /// allocate and free memory. 358 class CUDADeviceAllocatorTy : public DeviceAllocatorTy { 359 std::unordered_map<void *, TargetAllocTy> HostPinnedAllocs; 360 361 public: 362 void *allocate(size_t Size, void *, TargetAllocTy Kind) override { 363 if (Size == 0) 364 return nullptr; 365 366 void *MemAlloc = nullptr; 367 CUresult Err; 368 switch (Kind) { 369 case TARGET_ALLOC_DEFAULT: 370 case TARGET_ALLOC_DEVICE: 371 CUdeviceptr DevicePtr; 372 Err = cuMemAlloc(&DevicePtr, Size); 373 MemAlloc = (void *)DevicePtr; 374 if (!checkResult(Err, "Error returned from cuMemAlloc\n")) 375 return nullptr; 376 break; 377 case TARGET_ALLOC_HOST: 378 void *HostPtr; 379 Err = cuMemAllocHost(&HostPtr, Size); 380 MemAlloc = HostPtr; 381 if (!checkResult(Err, "Error returned from cuMemAllocHost\n")) 382 return nullptr; 383 HostPinnedAllocs[MemAlloc] = Kind; 384 break; 385 case TARGET_ALLOC_SHARED: 386 CUdeviceptr SharedPtr; 387 Err = cuMemAllocManaged(&SharedPtr, Size, CU_MEM_ATTACH_GLOBAL); 388 MemAlloc = (void *)SharedPtr; 389 if (!checkResult(Err, "Error returned from cuMemAllocManaged\n")) 390 return nullptr; 391 break; 392 } 393 394 return MemAlloc; 395 } 396 397 int free(void *TgtPtr) override { 398 CUresult Err; 399 // Host pinned memory must be freed differently. 400 TargetAllocTy Kind = 401 (HostPinnedAllocs.find(TgtPtr) == HostPinnedAllocs.end()) 402 ? TARGET_ALLOC_DEFAULT 403 : TARGET_ALLOC_HOST; 404 switch (Kind) { 405 case TARGET_ALLOC_DEFAULT: 406 case TARGET_ALLOC_DEVICE: 407 case TARGET_ALLOC_SHARED: 408 Err = cuMemFree((CUdeviceptr)TgtPtr); 409 if (!checkResult(Err, "Error returned from cuMemFree\n")) 410 return OFFLOAD_FAIL; 411 break; 412 case TARGET_ALLOC_HOST: 413 Err = cuMemFreeHost(TgtPtr); 414 if (!checkResult(Err, "Error returned from cuMemFreeHost\n")) 415 return OFFLOAD_FAIL; 416 break; 417 } 418 419 return OFFLOAD_SUCCESS; 420 } 421 }; 422 423 /// A vector of device allocators 424 std::vector<CUDADeviceAllocatorTy> DeviceAllocators; 425 426 /// A vector of memory managers. Since the memory manager is non-copyable and 427 // non-removable, we wrap them into std::unique_ptr. 428 std::vector<std::unique_ptr<MemoryManagerTy>> MemoryManagers; 429 430 /// Whether use memory manager 431 bool UseMemoryManager = true; 432 433 // Record entry point associated with device 434 void addOffloadEntry(const int DeviceId, const __tgt_offload_entry entry) { 435 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 436 E.Entries.push_back(entry); 437 } 438 439 // Return a pointer to the entry associated with the pointer 440 const __tgt_offload_entry *getOffloadEntry(const int DeviceId, 441 const void *Addr) const { 442 for (const __tgt_offload_entry &Itr : 443 DeviceData[DeviceId].FuncGblEntries.back().Entries) 444 if (Itr.addr == Addr) 445 return &Itr; 446 447 return nullptr; 448 } 449 450 // Return the pointer to the target entries table 451 __tgt_target_table *getOffloadEntriesTable(const int DeviceId) { 452 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 453 454 if (E.Entries.empty()) 455 return nullptr; 456 457 // Update table info according to the entries and return the pointer 458 E.Table.EntriesBegin = E.Entries.data(); 459 E.Table.EntriesEnd = E.Entries.data() + E.Entries.size(); 460 461 return &E.Table; 462 } 463 464 // Clear entries table for a device 465 void clearOffloadEntriesTable(const int DeviceId) { 466 DeviceData[DeviceId].FuncGblEntries.emplace_back(); 467 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 468 E.Entries.clear(); 469 E.Table.EntriesBegin = E.Table.EntriesEnd = nullptr; 470 } 471 472 public: 473 CUstream getStream(const int DeviceId, __tgt_async_info *AsyncInfo) const { 474 assert(AsyncInfo && "AsyncInfo is nullptr"); 475 476 if (!AsyncInfo->Queue) { 477 CUstream S; 478 if (StreamPool[DeviceId]->acquire(S) != OFFLOAD_SUCCESS) 479 return nullptr; 480 481 AsyncInfo->Queue = S; 482 } 483 484 return reinterpret_cast<CUstream>(AsyncInfo->Queue); 485 } 486 487 // This class should not be copied 488 DeviceRTLTy(const DeviceRTLTy &) = delete; 489 DeviceRTLTy(DeviceRTLTy &&) = delete; 490 491 DeviceRTLTy() 492 : NumberOfDevices(0), EnvNumTeams(-1), EnvTeamLimit(-1), 493 EnvTeamThreadLimit(-1), RequiresFlags(OMP_REQ_UNDEFINED), 494 DynamicMemorySize(0) { 495 496 DP("Start initializing CUDA\n"); 497 498 CUresult Err = cuInit(0); 499 if (Err == CUDA_ERROR_INVALID_HANDLE) { 500 // Can't call cuGetErrorString if dlsym failed 501 DP("Failed to load CUDA shared library\n"); 502 return; 503 } 504 if (!checkResult(Err, "Error returned from cuInit\n")) { 505 return; 506 } 507 508 Err = cuDeviceGetCount(&NumberOfDevices); 509 if (!checkResult(Err, "Error returned from cuDeviceGetCount\n")) 510 return; 511 512 if (NumberOfDevices == 0) { 513 DP("There are no devices supporting CUDA.\n"); 514 return; 515 } 516 517 DeviceData.resize(NumberOfDevices); 518 Modules.resize(NumberOfDevices); 519 StreamPool.resize(NumberOfDevices); 520 EventPool.resize(NumberOfDevices); 521 522 // Get environment variables regarding teams 523 if (const char *EnvStr = getenv("OMP_TEAM_LIMIT")) { 524 // OMP_TEAM_LIMIT has been set 525 EnvTeamLimit = std::stoi(EnvStr); 526 DP("Parsed OMP_TEAM_LIMIT=%d\n", EnvTeamLimit); 527 } 528 if (const char *EnvStr = getenv("OMP_TEAMS_THREAD_LIMIT")) { 529 // OMP_TEAMS_THREAD_LIMIT has been set 530 EnvTeamThreadLimit = std::stoi(EnvStr); 531 DP("Parsed OMP_TEAMS_THREAD_LIMIT=%d\n", EnvTeamThreadLimit); 532 } 533 if (const char *EnvStr = getenv("OMP_NUM_TEAMS")) { 534 // OMP_NUM_TEAMS has been set 535 EnvNumTeams = std::stoi(EnvStr); 536 DP("Parsed OMP_NUM_TEAMS=%d\n", EnvNumTeams); 537 } 538 if (const char *EnvStr = getenv("LIBOMPTARGET_SHARED_MEMORY_SIZE")) { 539 // LIBOMPTARGET_SHARED_MEMORY_SIZE has been set 540 DynamicMemorySize = std::stoi(EnvStr); 541 DP("Parsed LIBOMPTARGET_SHARED_MEMORY_SIZE = %" PRIu64 "\n", 542 DynamicMemorySize); 543 } 544 if (const char *EnvStr = getenv("LIBOMPTARGET_NUM_INITIAL_STREAMS")) { 545 // LIBOMPTARGET_NUM_INITIAL_STREAMS has been set 546 NumInitialStreams = std::stoi(EnvStr); 547 DP("Parsed LIBOMPTARGET_NUM_INITIAL_STREAMS=%d\n", NumInitialStreams); 548 } 549 550 for (int I = 0; I < NumberOfDevices; ++I) 551 DeviceAllocators.emplace_back(); 552 553 // Get the size threshold from environment variable 554 std::pair<size_t, bool> Res = MemoryManagerTy::getSizeThresholdFromEnv(); 555 UseMemoryManager = Res.second; 556 size_t MemoryManagerThreshold = Res.first; 557 558 if (UseMemoryManager) 559 for (int I = 0; I < NumberOfDevices; ++I) 560 MemoryManagers.emplace_back(std::make_unique<MemoryManagerTy>( 561 DeviceAllocators[I], MemoryManagerThreshold)); 562 563 // We lazily initialize all devices later. 564 InitializedFlags.assign(NumberOfDevices, false); 565 } 566 567 ~DeviceRTLTy() { 568 for (int DeviceId = 0; DeviceId < NumberOfDevices; ++DeviceId) 569 deinitDevice(DeviceId); 570 } 571 572 // Check whether a given DeviceId is valid 573 bool isValidDeviceId(const int DeviceId) const { 574 return DeviceId >= 0 && DeviceId < NumberOfDevices; 575 } 576 577 int getNumOfDevices() const { return NumberOfDevices; } 578 579 void setRequiresFlag(const int64_t Flags) { this->RequiresFlags = Flags; } 580 581 int initDevice(const int DeviceId) { 582 CUdevice Device; 583 584 DP("Getting device %d\n", DeviceId); 585 CUresult Err = cuDeviceGet(&Device, DeviceId); 586 if (!checkResult(Err, "Error returned from cuDeviceGet\n")) 587 return OFFLOAD_FAIL; 588 589 assert(InitializedFlags[DeviceId] == false && "Reinitializing device!"); 590 InitializedFlags[DeviceId] = true; 591 592 // Query the current flags of the primary context and set its flags if 593 // it is inactive 594 unsigned int FormerPrimaryCtxFlags = 0; 595 int FormerPrimaryCtxIsActive = 0; 596 Err = cuDevicePrimaryCtxGetState(Device, &FormerPrimaryCtxFlags, 597 &FormerPrimaryCtxIsActive); 598 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxGetState\n")) 599 return OFFLOAD_FAIL; 600 601 if (FormerPrimaryCtxIsActive) { 602 DP("The primary context is active, no change to its flags\n"); 603 if ((FormerPrimaryCtxFlags & CU_CTX_SCHED_MASK) != 604 CU_CTX_SCHED_BLOCKING_SYNC) 605 DP("Warning the current flags are not CU_CTX_SCHED_BLOCKING_SYNC\n"); 606 } else { 607 DP("The primary context is inactive, set its flags to " 608 "CU_CTX_SCHED_BLOCKING_SYNC\n"); 609 Err = cuDevicePrimaryCtxSetFlags(Device, CU_CTX_SCHED_BLOCKING_SYNC); 610 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxSetFlags\n")) 611 return OFFLOAD_FAIL; 612 } 613 614 // Retain the per device primary context and save it to use whenever this 615 // device is selected. 616 Err = cuDevicePrimaryCtxRetain(&DeviceData[DeviceId].Context, Device); 617 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxRetain\n")) 618 return OFFLOAD_FAIL; 619 620 Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 621 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 622 return OFFLOAD_FAIL; 623 624 // Initialize the stream pool. 625 if (!StreamPool[DeviceId]) 626 StreamPool[DeviceId] = std::make_unique<StreamPoolTy>(StreamAllocatorTy(), 627 NumInitialStreams); 628 629 // Initialize the event pool. 630 if (!EventPool[DeviceId]) 631 EventPool[DeviceId] = 632 std::make_unique<EventPoolTy>(EventAllocatorTy(), NumInitialEvents); 633 634 // Query attributes to determine number of threads/block and blocks/grid. 635 int MaxGridDimX; 636 Err = cuDeviceGetAttribute(&MaxGridDimX, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X, 637 Device); 638 if (Err != CUDA_SUCCESS) { 639 DP("Error getting max grid dimension, use default value %d\n", 640 DeviceRTLTy::DefaultNumTeams); 641 DeviceData[DeviceId].BlocksPerGrid = DeviceRTLTy::DefaultNumTeams; 642 } else { 643 DP("Using %d CUDA blocks per grid\n", MaxGridDimX); 644 DeviceData[DeviceId].BlocksPerGrid = MaxGridDimX; 645 } 646 647 // We are only exploiting threads along the x axis. 648 int MaxBlockDimX; 649 Err = cuDeviceGetAttribute(&MaxBlockDimX, 650 CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, Device); 651 if (Err != CUDA_SUCCESS) { 652 DP("Error getting max block dimension, use default value %d\n", 653 DeviceRTLTy::DefaultNumThreads); 654 DeviceData[DeviceId].ThreadsPerBlock = DeviceRTLTy::DefaultNumThreads; 655 } else { 656 DP("Using %d CUDA threads per block\n", MaxBlockDimX); 657 DeviceData[DeviceId].ThreadsPerBlock = MaxBlockDimX; 658 659 if (EnvTeamThreadLimit > 0 && 660 DeviceData[DeviceId].ThreadsPerBlock > EnvTeamThreadLimit) { 661 DP("Max CUDA threads per block %d exceeds the thread limit %d set by " 662 "OMP_TEAMS_THREAD_LIMIT, capping at the limit\n", 663 DeviceData[DeviceId].ThreadsPerBlock, EnvTeamThreadLimit); 664 DeviceData[DeviceId].ThreadsPerBlock = EnvTeamThreadLimit; 665 } 666 if (DeviceData[DeviceId].ThreadsPerBlock > DeviceRTLTy::HardThreadLimit) { 667 DP("Max CUDA threads per block %d exceeds the hard thread limit %d, " 668 "capping at the hard limit\n", 669 DeviceData[DeviceId].ThreadsPerBlock, DeviceRTLTy::HardThreadLimit); 670 DeviceData[DeviceId].ThreadsPerBlock = DeviceRTLTy::HardThreadLimit; 671 } 672 } 673 674 // Get and set warp size 675 int WarpSize; 676 Err = 677 cuDeviceGetAttribute(&WarpSize, CU_DEVICE_ATTRIBUTE_WARP_SIZE, Device); 678 if (Err != CUDA_SUCCESS) { 679 DP("Error getting warp size, assume default value 32\n"); 680 DeviceData[DeviceId].WarpSize = 32; 681 } else { 682 DP("Using warp size %d\n", WarpSize); 683 DeviceData[DeviceId].WarpSize = WarpSize; 684 } 685 686 // Adjust teams to the env variables 687 if (EnvTeamLimit > 0 && DeviceData[DeviceId].BlocksPerGrid > EnvTeamLimit) { 688 DP("Capping max CUDA blocks per grid to OMP_TEAM_LIMIT=%d\n", 689 EnvTeamLimit); 690 DeviceData[DeviceId].BlocksPerGrid = EnvTeamLimit; 691 } 692 693 size_t StackLimit; 694 size_t HeapLimit; 695 if (const char *EnvStr = getenv("LIBOMPTARGET_STACK_SIZE")) { 696 StackLimit = std::stol(EnvStr); 697 if (cuCtxSetLimit(CU_LIMIT_STACK_SIZE, StackLimit) != CUDA_SUCCESS) 698 return OFFLOAD_FAIL; 699 } else { 700 if (cuCtxGetLimit(&StackLimit, CU_LIMIT_STACK_SIZE) != CUDA_SUCCESS) 701 return OFFLOAD_FAIL; 702 } 703 if (const char *EnvStr = getenv("LIBOMPTARGET_HEAP_SIZE")) { 704 HeapLimit = std::stol(EnvStr); 705 if (cuCtxSetLimit(CU_LIMIT_MALLOC_HEAP_SIZE, HeapLimit) != CUDA_SUCCESS) 706 return OFFLOAD_FAIL; 707 } else { 708 if (cuCtxGetLimit(&HeapLimit, CU_LIMIT_MALLOC_HEAP_SIZE) != CUDA_SUCCESS) 709 return OFFLOAD_FAIL; 710 } 711 712 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 713 "Device supports up to %d CUDA blocks and %d threads with a " 714 "warp size of %d\n", 715 DeviceData[DeviceId].BlocksPerGrid, 716 DeviceData[DeviceId].ThreadsPerBlock, DeviceData[DeviceId].WarpSize); 717 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 718 "Device heap size is %d Bytes, device stack size is %d Bytes per " 719 "thread\n", 720 (int)HeapLimit, (int)StackLimit); 721 722 // Set default number of teams 723 if (EnvNumTeams > 0) { 724 DP("Default number of teams set according to environment %d\n", 725 EnvNumTeams); 726 DeviceData[DeviceId].NumTeams = EnvNumTeams; 727 } else { 728 DeviceData[DeviceId].NumTeams = DeviceRTLTy::DefaultNumTeams; 729 DP("Default number of teams set according to library's default %d\n", 730 DeviceRTLTy::DefaultNumTeams); 731 } 732 733 if (DeviceData[DeviceId].NumTeams > DeviceData[DeviceId].BlocksPerGrid) { 734 DP("Default number of teams exceeds device limit, capping at %d\n", 735 DeviceData[DeviceId].BlocksPerGrid); 736 DeviceData[DeviceId].NumTeams = DeviceData[DeviceId].BlocksPerGrid; 737 } 738 739 // Set default number of threads 740 DeviceData[DeviceId].NumThreads = DeviceRTLTy::DefaultNumThreads; 741 DP("Default number of threads set according to library's default %d\n", 742 DeviceRTLTy::DefaultNumThreads); 743 if (DeviceData[DeviceId].NumThreads > 744 DeviceData[DeviceId].ThreadsPerBlock) { 745 DP("Default number of threads exceeds device limit, capping at %d\n", 746 DeviceData[DeviceId].ThreadsPerBlock); 747 DeviceData[DeviceId].NumThreads = DeviceData[DeviceId].ThreadsPerBlock; 748 } 749 750 return OFFLOAD_SUCCESS; 751 } 752 753 int deinitDevice(const int DeviceId) { 754 auto IsInitialized = InitializedFlags[DeviceId]; 755 if (!IsInitialized) 756 return OFFLOAD_SUCCESS; 757 InitializedFlags[DeviceId] = false; 758 759 if (UseMemoryManager) 760 MemoryManagers[DeviceId].release(); 761 762 StreamPool[DeviceId].reset(); 763 EventPool[DeviceId].reset(); 764 765 DeviceDataTy &D = DeviceData[DeviceId]; 766 if (!checkResult(cuCtxSetCurrent(D.Context), 767 "Error returned from cuCtxSetCurrent\n")) 768 return OFFLOAD_FAIL; 769 770 // Unload all modules. 771 for (auto &M : Modules[DeviceId]) 772 if (!checkResult(cuModuleUnload(M), 773 "Error returned from cuModuleUnload\n")) 774 return OFFLOAD_FAIL; 775 776 // Destroy context. 777 CUdevice Device; 778 if (!checkResult(cuCtxGetDevice(&Device), 779 "Error returned from cuCtxGetDevice\n")) 780 return OFFLOAD_FAIL; 781 782 if (!checkResult(cuDevicePrimaryCtxRelease(Device), 783 "Error returned from cuDevicePrimaryCtxRelease\n")) 784 return OFFLOAD_FAIL; 785 786 return OFFLOAD_SUCCESS; 787 } 788 789 __tgt_target_table *loadBinary(const int DeviceId, 790 const __tgt_device_image *Image) { 791 // Clear the offload table as we are going to create a new one. 792 clearOffloadEntriesTable(DeviceId); 793 794 // Create the module and extract the function pointers. 795 CUmodule Module; 796 DP("Load data from image " DPxMOD "\n", DPxPTR(Image->ImageStart)); 797 CUresult Err = 798 cuModuleLoadDataEx(&Module, Image->ImageStart, 0, nullptr, nullptr); 799 if (!checkResult(Err, "Error returned from cuModuleLoadDataEx\n")) 800 return nullptr; 801 802 DP("CUDA module successfully loaded!\n"); 803 804 Modules[DeviceId].push_back(Module); 805 806 // Find the symbols in the module by name. 807 const __tgt_offload_entry *HostBegin = Image->EntriesBegin; 808 const __tgt_offload_entry *HostEnd = Image->EntriesEnd; 809 810 std::list<KernelTy> &KernelsList = DeviceData[DeviceId].KernelsList; 811 for (const __tgt_offload_entry *E = HostBegin; E != HostEnd; ++E) { 812 if (!E->addr) { 813 // We return nullptr when something like this happens, the host should 814 // have always something in the address to uniquely identify the target 815 // region. 816 DP("Invalid binary: host entry '<null>' (size = %zd)...\n", E->size); 817 return nullptr; 818 } 819 820 if (E->size) { 821 __tgt_offload_entry Entry = *E; 822 CUdeviceptr CUPtr; 823 size_t CUSize; 824 Err = cuModuleGetGlobal(&CUPtr, &CUSize, Module, E->name); 825 // We keep this style here because we need the name 826 if (Err != CUDA_SUCCESS) { 827 REPORT("Loading global '%s' Failed\n", E->name); 828 CUDA_ERR_STRING(Err); 829 return nullptr; 830 } 831 832 if (CUSize != E->size) { 833 DP("Loading global '%s' - size mismatch (%zd != %zd)\n", E->name, 834 CUSize, E->size); 835 return nullptr; 836 } 837 838 DP("Entry point " DPxMOD " maps to global %s (" DPxMOD ")\n", 839 DPxPTR(E - HostBegin), E->name, DPxPTR(CUPtr)); 840 841 Entry.addr = (void *)(CUPtr); 842 843 // Note: In the current implementation declare target variables 844 // can either be link or to. This means that once unified 845 // memory is activated via the requires directive, the variable 846 // can be used directly from the host in both cases. 847 // TODO: when variables types other than to or link are added, 848 // the below condition should be changed to explicitly 849 // check for to and link variables types: 850 // (RequiresFlags & OMP_REQ_UNIFIED_SHARED_MEMORY && (e->flags & 851 // OMP_DECLARE_TARGET_LINK || e->flags == OMP_DECLARE_TARGET_TO)) 852 if (RequiresFlags & OMP_REQ_UNIFIED_SHARED_MEMORY) { 853 // If unified memory is present any target link or to variables 854 // can access host addresses directly. There is no longer a 855 // need for device copies. 856 cuMemcpyHtoD(CUPtr, E->addr, sizeof(void *)); 857 DP("Copy linked variable host address (" DPxMOD 858 ") to device address (" DPxMOD ")\n", 859 DPxPTR(*((void **)E->addr)), DPxPTR(CUPtr)); 860 } 861 862 addOffloadEntry(DeviceId, Entry); 863 864 continue; 865 } 866 867 CUfunction Func; 868 Err = cuModuleGetFunction(&Func, Module, E->name); 869 // We keep this style here because we need the name 870 if (Err != CUDA_SUCCESS) { 871 REPORT("Loading '%s' Failed\n", E->name); 872 CUDA_ERR_STRING(Err); 873 return nullptr; 874 } 875 876 DP("Entry point " DPxMOD " maps to %s (" DPxMOD ")\n", 877 DPxPTR(E - HostBegin), E->name, DPxPTR(Func)); 878 879 // default value GENERIC (in case symbol is missing from cubin file) 880 llvm::omp::OMPTgtExecModeFlags ExecModeVal; 881 std::string ExecModeNameStr(E->name); 882 ExecModeNameStr += "_exec_mode"; 883 const char *ExecModeName = ExecModeNameStr.c_str(); 884 885 CUdeviceptr ExecModePtr; 886 size_t CUSize; 887 Err = cuModuleGetGlobal(&ExecModePtr, &CUSize, Module, ExecModeName); 888 if (Err == CUDA_SUCCESS) { 889 if (CUSize != sizeof(llvm::omp::OMPTgtExecModeFlags)) { 890 DP("Loading global exec_mode '%s' - size mismatch (%zd != %zd)\n", 891 ExecModeName, CUSize, sizeof(llvm::omp::OMPTgtExecModeFlags)); 892 return nullptr; 893 } 894 895 Err = cuMemcpyDtoH(&ExecModeVal, ExecModePtr, CUSize); 896 if (Err != CUDA_SUCCESS) { 897 REPORT("Error when copying data from device to host. Pointers: " 898 "host = " DPxMOD ", device = " DPxMOD ", size = %zd\n", 899 DPxPTR(&ExecModeVal), DPxPTR(ExecModePtr), CUSize); 900 CUDA_ERR_STRING(Err); 901 return nullptr; 902 } 903 } else { 904 DP("Loading global exec_mode '%s' - symbol missing, using default " 905 "value GENERIC (1)\n", 906 ExecModeName); 907 } 908 909 KernelsList.emplace_back(Func, ExecModeVal); 910 911 __tgt_offload_entry Entry = *E; 912 Entry.addr = &KernelsList.back(); 913 addOffloadEntry(DeviceId, Entry); 914 } 915 916 // send device environment data to the device 917 { 918 // TODO: The device ID used here is not the real device ID used by OpenMP. 919 DeviceEnvironmentTy DeviceEnv{0, static_cast<uint32_t>(NumberOfDevices), 920 static_cast<uint32_t>(DeviceId), 921 static_cast<uint32_t>(DynamicMemorySize)}; 922 923 if (const char *EnvStr = getenv("LIBOMPTARGET_DEVICE_RTL_DEBUG")) 924 DeviceEnv.DebugKind = std::stoi(EnvStr); 925 926 const char *DeviceEnvName = "omptarget_device_environment"; 927 CUdeviceptr DeviceEnvPtr; 928 size_t CUSize; 929 930 Err = cuModuleGetGlobal(&DeviceEnvPtr, &CUSize, Module, DeviceEnvName); 931 if (Err == CUDA_SUCCESS) { 932 if (CUSize != sizeof(DeviceEnv)) { 933 REPORT( 934 "Global device_environment '%s' - size mismatch (%zu != %zu)\n", 935 DeviceEnvName, CUSize, sizeof(int32_t)); 936 CUDA_ERR_STRING(Err); 937 return nullptr; 938 } 939 940 Err = cuMemcpyHtoD(DeviceEnvPtr, &DeviceEnv, CUSize); 941 if (Err != CUDA_SUCCESS) { 942 REPORT("Error when copying data from host to device. Pointers: " 943 "host = " DPxMOD ", device = " DPxMOD ", size = %zu\n", 944 DPxPTR(&DeviceEnv), DPxPTR(DeviceEnvPtr), CUSize); 945 CUDA_ERR_STRING(Err); 946 return nullptr; 947 } 948 949 DP("Sending global device environment data %zu bytes\n", CUSize); 950 } else { 951 DP("Finding global device environment '%s' - symbol missing.\n", 952 DeviceEnvName); 953 DP("Continue, considering this is a device RTL which does not accept " 954 "environment setting.\n"); 955 } 956 } 957 958 return getOffloadEntriesTable(DeviceId); 959 } 960 961 void *dataAlloc(const int DeviceId, const int64_t Size, 962 const TargetAllocTy Kind) { 963 switch (Kind) { 964 case TARGET_ALLOC_DEFAULT: 965 case TARGET_ALLOC_DEVICE: 966 if (UseMemoryManager) 967 return MemoryManagers[DeviceId]->allocate(Size, nullptr); 968 else 969 return DeviceAllocators[DeviceId].allocate(Size, nullptr, Kind); 970 case TARGET_ALLOC_HOST: 971 case TARGET_ALLOC_SHARED: 972 return DeviceAllocators[DeviceId].allocate(Size, nullptr, Kind); 973 } 974 975 REPORT("Invalid target data allocation kind or requested allocator not " 976 "implemented yet\n"); 977 978 return nullptr; 979 } 980 981 int dataSubmit(const int DeviceId, const void *TgtPtr, const void *HstPtr, 982 const int64_t Size, __tgt_async_info *AsyncInfo) const { 983 assert(AsyncInfo && "AsyncInfo is nullptr"); 984 985 CUstream Stream = getStream(DeviceId, AsyncInfo); 986 CUresult Err = cuMemcpyHtoDAsync((CUdeviceptr)TgtPtr, HstPtr, Size, Stream); 987 if (Err != CUDA_SUCCESS) { 988 DP("Error when copying data from host to device. Pointers: host " 989 "= " DPxMOD ", device = " DPxMOD ", size = %" PRId64 "\n", 990 DPxPTR(HstPtr), DPxPTR(TgtPtr), Size); 991 CUDA_ERR_STRING(Err); 992 return OFFLOAD_FAIL; 993 } 994 995 return OFFLOAD_SUCCESS; 996 } 997 998 int dataRetrieve(const int DeviceId, void *HstPtr, const void *TgtPtr, 999 const int64_t Size, __tgt_async_info *AsyncInfo) const { 1000 assert(AsyncInfo && "AsyncInfo is nullptr"); 1001 1002 CUstream Stream = getStream(DeviceId, AsyncInfo); 1003 CUresult Err = cuMemcpyDtoHAsync(HstPtr, (CUdeviceptr)TgtPtr, Size, Stream); 1004 if (Err != CUDA_SUCCESS) { 1005 DP("Error when copying data from device to host. Pointers: host " 1006 "= " DPxMOD ", device = " DPxMOD ", size = %" PRId64 "\n", 1007 DPxPTR(HstPtr), DPxPTR(TgtPtr), Size); 1008 CUDA_ERR_STRING(Err); 1009 return OFFLOAD_FAIL; 1010 } 1011 1012 return OFFLOAD_SUCCESS; 1013 } 1014 1015 int dataExchange(int SrcDevId, const void *SrcPtr, int DstDevId, void *DstPtr, 1016 int64_t Size, __tgt_async_info *AsyncInfo) const { 1017 assert(AsyncInfo && "AsyncInfo is nullptr"); 1018 1019 CUresult Err; 1020 CUstream Stream = getStream(SrcDevId, AsyncInfo); 1021 1022 // If they are two devices, we try peer to peer copy first 1023 if (SrcDevId != DstDevId) { 1024 int CanAccessPeer = 0; 1025 Err = cuDeviceCanAccessPeer(&CanAccessPeer, SrcDevId, DstDevId); 1026 if (Err != CUDA_SUCCESS) { 1027 REPORT("Error returned from cuDeviceCanAccessPeer. src = %" PRId32 1028 ", dst = %" PRId32 "\n", 1029 SrcDevId, DstDevId); 1030 CUDA_ERR_STRING(Err); 1031 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1032 } 1033 1034 if (!CanAccessPeer) { 1035 DP("P2P memcpy not supported so fall back to D2D memcpy"); 1036 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1037 } 1038 1039 Err = cuCtxEnablePeerAccess(DeviceData[DstDevId].Context, 0); 1040 if (Err != CUDA_SUCCESS) { 1041 REPORT("Error returned from cuCtxEnablePeerAccess. src = %" PRId32 1042 ", dst = %" PRId32 "\n", 1043 SrcDevId, DstDevId); 1044 CUDA_ERR_STRING(Err); 1045 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1046 } 1047 1048 Err = cuMemcpyPeerAsync((CUdeviceptr)DstPtr, DeviceData[DstDevId].Context, 1049 (CUdeviceptr)SrcPtr, DeviceData[SrcDevId].Context, 1050 Size, Stream); 1051 if (Err == CUDA_SUCCESS) 1052 return OFFLOAD_SUCCESS; 1053 1054 DP("Error returned from cuMemcpyPeerAsync. src_ptr = " DPxMOD 1055 ", src_id =%" PRId32 ", dst_ptr = " DPxMOD ", dst_id =%" PRId32 "\n", 1056 DPxPTR(SrcPtr), SrcDevId, DPxPTR(DstPtr), DstDevId); 1057 CUDA_ERR_STRING(Err); 1058 } 1059 1060 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1061 } 1062 1063 int dataDelete(const int DeviceId, void *TgtPtr) { 1064 if (UseMemoryManager) 1065 return MemoryManagers[DeviceId]->free(TgtPtr); 1066 1067 return DeviceAllocators[DeviceId].free(TgtPtr); 1068 } 1069 1070 int runTargetTeamRegion(const int DeviceId, void *TgtEntryPtr, void **TgtArgs, 1071 ptrdiff_t *TgtOffsets, const int ArgNum, 1072 const int TeamNum, const int ThreadLimit, 1073 const unsigned int LoopTripCount, 1074 __tgt_async_info *AsyncInfo) const { 1075 // All args are references. 1076 std::vector<void *> Args(ArgNum); 1077 std::vector<void *> Ptrs(ArgNum); 1078 1079 for (int I = 0; I < ArgNum; ++I) { 1080 Ptrs[I] = (void *)((intptr_t)TgtArgs[I] + TgtOffsets[I]); 1081 Args[I] = &Ptrs[I]; 1082 } 1083 1084 KernelTy *KernelInfo = reinterpret_cast<KernelTy *>(TgtEntryPtr); 1085 1086 const bool IsSPMDGenericMode = 1087 KernelInfo->ExecutionMode == llvm::omp::OMP_TGT_EXEC_MODE_GENERIC_SPMD; 1088 const bool IsSPMDMode = 1089 KernelInfo->ExecutionMode == llvm::omp::OMP_TGT_EXEC_MODE_SPMD; 1090 const bool IsGenericMode = 1091 KernelInfo->ExecutionMode == llvm::omp::OMP_TGT_EXEC_MODE_GENERIC; 1092 1093 int CudaThreadsPerBlock; 1094 if (ThreadLimit > 0) { 1095 DP("Setting CUDA threads per block to requested %d\n", ThreadLimit); 1096 CudaThreadsPerBlock = ThreadLimit; 1097 // Add master warp if necessary 1098 if (IsGenericMode) { 1099 DP("Adding master warp: +%d threads\n", DeviceData[DeviceId].WarpSize); 1100 CudaThreadsPerBlock += DeviceData[DeviceId].WarpSize; 1101 } 1102 } else { 1103 DP("Setting CUDA threads per block to default %d\n", 1104 DeviceData[DeviceId].NumThreads); 1105 CudaThreadsPerBlock = DeviceData[DeviceId].NumThreads; 1106 } 1107 1108 if (CudaThreadsPerBlock > DeviceData[DeviceId].ThreadsPerBlock) { 1109 DP("Threads per block capped at device limit %d\n", 1110 DeviceData[DeviceId].ThreadsPerBlock); 1111 CudaThreadsPerBlock = DeviceData[DeviceId].ThreadsPerBlock; 1112 } 1113 1114 CUresult Err; 1115 if (!KernelInfo->MaxThreadsPerBlock) { 1116 Err = cuFuncGetAttribute(&KernelInfo->MaxThreadsPerBlock, 1117 CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK, 1118 KernelInfo->Func); 1119 if (!checkResult(Err, "Error returned from cuFuncGetAttribute\n")) 1120 return OFFLOAD_FAIL; 1121 } 1122 1123 if (KernelInfo->MaxThreadsPerBlock < CudaThreadsPerBlock) { 1124 DP("Threads per block capped at kernel limit %d\n", 1125 KernelInfo->MaxThreadsPerBlock); 1126 CudaThreadsPerBlock = KernelInfo->MaxThreadsPerBlock; 1127 } 1128 1129 unsigned int CudaBlocksPerGrid; 1130 if (TeamNum <= 0) { 1131 if (LoopTripCount > 0 && EnvNumTeams < 0) { 1132 if (IsSPMDGenericMode) { 1133 // If we reach this point, then we are executing a kernel that was 1134 // transformed from Generic-mode to SPMD-mode. This kernel has 1135 // SPMD-mode execution, but needs its blocks to be scheduled 1136 // differently because the current loop trip count only applies to the 1137 // `teams distribute` region and will create var too few blocks using 1138 // the regular SPMD-mode method. 1139 CudaBlocksPerGrid = LoopTripCount; 1140 } else if (IsSPMDMode) { 1141 // We have a combined construct, i.e. `target teams distribute 1142 // parallel for [simd]`. We launch so many teams so that each thread 1143 // will execute one iteration of the loop. round up to the nearest 1144 // integer 1145 CudaBlocksPerGrid = ((LoopTripCount - 1) / CudaThreadsPerBlock) + 1; 1146 } else if (IsGenericMode) { 1147 // If we reach this point, then we have a non-combined construct, i.e. 1148 // `teams distribute` with a nested `parallel for` and each team is 1149 // assigned one iteration of the `distribute` loop. E.g.: 1150 // 1151 // #pragma omp target teams distribute 1152 // for(...loop_tripcount...) { 1153 // #pragma omp parallel for 1154 // for(...) {} 1155 // } 1156 // 1157 // Threads within a team will execute the iterations of the `parallel` 1158 // loop. 1159 CudaBlocksPerGrid = LoopTripCount; 1160 } else { 1161 REPORT("Unknown execution mode: %d\n", 1162 static_cast<int8_t>(KernelInfo->ExecutionMode)); 1163 return OFFLOAD_FAIL; 1164 } 1165 DP("Using %d teams due to loop trip count %" PRIu32 1166 " and number of threads per block %d\n", 1167 CudaBlocksPerGrid, LoopTripCount, CudaThreadsPerBlock); 1168 } else { 1169 DP("Using default number of teams %d\n", DeviceData[DeviceId].NumTeams); 1170 CudaBlocksPerGrid = DeviceData[DeviceId].NumTeams; 1171 } 1172 } else { 1173 DP("Using requested number of teams %d\n", TeamNum); 1174 CudaBlocksPerGrid = TeamNum; 1175 } 1176 1177 if (CudaBlocksPerGrid > DeviceData[DeviceId].BlocksPerGrid) { 1178 DP("Capping number of teams to team limit %d\n", 1179 DeviceData[DeviceId].BlocksPerGrid); 1180 CudaBlocksPerGrid = DeviceData[DeviceId].BlocksPerGrid; 1181 } 1182 1183 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 1184 "Launching kernel %s with %d blocks and %d threads in %s mode\n", 1185 (getOffloadEntry(DeviceId, TgtEntryPtr)) 1186 ? getOffloadEntry(DeviceId, TgtEntryPtr)->name 1187 : "(null)", 1188 CudaBlocksPerGrid, CudaThreadsPerBlock, 1189 (!IsSPMDMode ? (IsGenericMode ? "Generic" : "SPMD-Generic") : "SPMD")); 1190 1191 CUstream Stream = getStream(DeviceId, AsyncInfo); 1192 Err = cuLaunchKernel(KernelInfo->Func, CudaBlocksPerGrid, /* gridDimY */ 1, 1193 /* gridDimZ */ 1, CudaThreadsPerBlock, 1194 /* blockDimY */ 1, /* blockDimZ */ 1, 1195 DynamicMemorySize, Stream, &Args[0], nullptr); 1196 if (!checkResult(Err, "Error returned from cuLaunchKernel\n")) 1197 return OFFLOAD_FAIL; 1198 1199 DP("Launch of entry point at " DPxMOD " successful!\n", 1200 DPxPTR(TgtEntryPtr)); 1201 1202 return OFFLOAD_SUCCESS; 1203 } 1204 1205 int synchronize(const int DeviceId, __tgt_async_info *AsyncInfo) const { 1206 CUstream Stream = reinterpret_cast<CUstream>(AsyncInfo->Queue); 1207 CUresult Err = cuStreamSynchronize(Stream); 1208 1209 // Once the stream is synchronized, return it to stream pool and reset 1210 // AsyncInfo. This is to make sure the synchronization only works for its 1211 // own tasks. 1212 StreamPool[DeviceId]->release(reinterpret_cast<CUstream>(AsyncInfo->Queue)); 1213 AsyncInfo->Queue = nullptr; 1214 1215 if (Err != CUDA_SUCCESS) { 1216 DP("Error when synchronizing stream. stream = " DPxMOD 1217 ", async info ptr = " DPxMOD "\n", 1218 DPxPTR(Stream), DPxPTR(AsyncInfo)); 1219 CUDA_ERR_STRING(Err); 1220 } 1221 return (Err == CUDA_SUCCESS) ? OFFLOAD_SUCCESS : OFFLOAD_FAIL; 1222 } 1223 1224 void printDeviceInfo(int32_t device_id) { 1225 char TmpChar[1000]; 1226 std::string TmpStr; 1227 size_t TmpSt; 1228 int TmpInt, TmpInt2, TmpInt3; 1229 1230 CUdevice Device; 1231 checkResult(cuDeviceGet(&Device, device_id), 1232 "Error returned from cuCtxGetDevice\n"); 1233 1234 cuDriverGetVersion(&TmpInt); 1235 printf(" CUDA Driver Version: \t\t%d \n", TmpInt); 1236 printf(" CUDA Device Number: \t\t%d \n", device_id); 1237 checkResult(cuDeviceGetName(TmpChar, 1000, Device), 1238 "Error returned from cuDeviceGetName\n"); 1239 printf(" Device Name: \t\t\t%s \n", TmpChar); 1240 checkResult(cuDeviceTotalMem(&TmpSt, Device), 1241 "Error returned from cuDeviceTotalMem\n"); 1242 printf(" Global Memory Size: \t\t%zu bytes \n", TmpSt); 1243 checkResult(cuDeviceGetAttribute( 1244 &TmpInt, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, Device), 1245 "Error returned from cuDeviceGetAttribute\n"); 1246 printf(" Number of Multiprocessors: \t\t%d \n", TmpInt); 1247 checkResult( 1248 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_GPU_OVERLAP, Device), 1249 "Error returned from cuDeviceGetAttribute\n"); 1250 printf(" Concurrent Copy and Execution: \t%s \n", BOOL2TEXT(TmpInt)); 1251 checkResult(cuDeviceGetAttribute( 1252 &TmpInt, CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY, Device), 1253 "Error returned from cuDeviceGetAttribute\n"); 1254 printf(" Total Constant Memory: \t\t%d bytes\n", TmpInt); 1255 checkResult( 1256 cuDeviceGetAttribute( 1257 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK, Device), 1258 "Error returned from cuDeviceGetAttribute\n"); 1259 printf(" Max Shared Memory per Block: \t%d bytes \n", TmpInt); 1260 checkResult( 1261 cuDeviceGetAttribute( 1262 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK, Device), 1263 "Error returned from cuDeviceGetAttribute\n"); 1264 printf(" Registers per Block: \t\t%d \n", TmpInt); 1265 checkResult( 1266 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_WARP_SIZE, Device), 1267 "Error returned from cuDeviceGetAttribute\n"); 1268 printf(" Warp Size: \t\t\t\t%d Threads \n", TmpInt); 1269 checkResult(cuDeviceGetAttribute( 1270 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK, Device), 1271 "Error returned from cuDeviceGetAttribute\n"); 1272 printf(" Maximum Threads per Block: \t\t%d \n", TmpInt); 1273 checkResult(cuDeviceGetAttribute( 1274 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, Device), 1275 "Error returned from cuDeviceGetAttribute\n"); 1276 checkResult(cuDeviceGetAttribute( 1277 &TmpInt2, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y, Device), 1278 "Error returned from cuDeviceGetAttribute\n"); 1279 checkResult(cuDeviceGetAttribute( 1280 &TmpInt3, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z, Device), 1281 "Error returned from cuDeviceGetAttribute\n"); 1282 printf(" Maximum Block Dimensions: \t\t%d, %d, %d \n", TmpInt, TmpInt2, 1283 TmpInt3); 1284 checkResult(cuDeviceGetAttribute( 1285 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X, Device), 1286 "Error returned from cuDeviceGetAttribute\n"); 1287 checkResult(cuDeviceGetAttribute( 1288 &TmpInt2, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y, Device), 1289 "Error returned from cuDeviceGetAttribute\n"); 1290 checkResult(cuDeviceGetAttribute( 1291 &TmpInt3, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z, Device), 1292 "Error returned from cuDeviceGetAttribute\n"); 1293 printf(" Maximum Grid Dimensions: \t\t%d x %d x %d \n", TmpInt, TmpInt2, 1294 TmpInt3); 1295 checkResult( 1296 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_MAX_PITCH, Device), 1297 "Error returned from cuDeviceGetAttribute\n"); 1298 printf(" Maximum Memory Pitch: \t\t%d bytes \n", TmpInt); 1299 checkResult(cuDeviceGetAttribute( 1300 &TmpInt, CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT, Device), 1301 "Error returned from cuDeviceGetAttribute\n"); 1302 printf(" Texture Alignment: \t\t\t%d bytes \n", TmpInt); 1303 checkResult( 1304 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, Device), 1305 "Error returned from cuDeviceGetAttribute\n"); 1306 printf(" Clock Rate: \t\t\t%d kHz\n", TmpInt); 1307 checkResult(cuDeviceGetAttribute( 1308 &TmpInt, CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT, Device), 1309 "Error returned from cuDeviceGetAttribute\n"); 1310 printf(" Execution Timeout: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1311 checkResult( 1312 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_INTEGRATED, Device), 1313 "Error returned from cuDeviceGetAttribute\n"); 1314 printf(" Integrated Device: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1315 checkResult(cuDeviceGetAttribute( 1316 &TmpInt, CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY, Device), 1317 "Error returned from cuDeviceGetAttribute\n"); 1318 printf(" Can Map Host Memory: \t\t%s \n", BOOL2TEXT(TmpInt)); 1319 checkResult( 1320 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_COMPUTE_MODE, Device), 1321 "Error returned from cuDeviceGetAttribute\n"); 1322 if (TmpInt == CU_COMPUTEMODE_DEFAULT) 1323 TmpStr = "DEFAULT"; 1324 else if (TmpInt == CU_COMPUTEMODE_PROHIBITED) 1325 TmpStr = "PROHIBITED"; 1326 else if (TmpInt == CU_COMPUTEMODE_EXCLUSIVE_PROCESS) 1327 TmpStr = "EXCLUSIVE PROCESS"; 1328 else 1329 TmpStr = "unknown"; 1330 printf(" Compute Mode: \t\t\t%s \n", TmpStr.c_str()); 1331 checkResult(cuDeviceGetAttribute( 1332 &TmpInt, CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS, Device), 1333 "Error returned from cuDeviceGetAttribute\n"); 1334 printf(" Concurrent Kernels: \t\t%s \n", BOOL2TEXT(TmpInt)); 1335 checkResult( 1336 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_ECC_ENABLED, Device), 1337 "Error returned from cuDeviceGetAttribute\n"); 1338 printf(" ECC Enabled: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1339 checkResult(cuDeviceGetAttribute( 1340 &TmpInt, CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE, Device), 1341 "Error returned from cuDeviceGetAttribute\n"); 1342 printf(" Memory Clock Rate: \t\t\t%d kHz\n", TmpInt); 1343 checkResult( 1344 cuDeviceGetAttribute( 1345 &TmpInt, CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH, Device), 1346 "Error returned from cuDeviceGetAttribute\n"); 1347 printf(" Memory Bus Width: \t\t\t%d bits\n", TmpInt); 1348 checkResult(cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE, 1349 Device), 1350 "Error returned from cuDeviceGetAttribute\n"); 1351 printf(" L2 Cache Size: \t\t\t%d bytes \n", TmpInt); 1352 checkResult(cuDeviceGetAttribute( 1353 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_MULTIPROCESSOR, 1354 Device), 1355 "Error returned from cuDeviceGetAttribute\n"); 1356 printf(" Max Threads Per SMP: \t\t%d \n", TmpInt); 1357 checkResult(cuDeviceGetAttribute( 1358 &TmpInt, CU_DEVICE_ATTRIBUTE_ASYNC_ENGINE_COUNT, Device), 1359 "Error returned from cuDeviceGetAttribute\n"); 1360 printf(" Async Engines: \t\t\t%s (%d) \n", BOOL2TEXT(TmpInt), TmpInt); 1361 checkResult(cuDeviceGetAttribute( 1362 &TmpInt, CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING, Device), 1363 "Error returned from cuDeviceGetAttribute\n"); 1364 printf(" Unified Addressing: \t\t%s \n", BOOL2TEXT(TmpInt)); 1365 checkResult(cuDeviceGetAttribute( 1366 &TmpInt, CU_DEVICE_ATTRIBUTE_MANAGED_MEMORY, Device), 1367 "Error returned from cuDeviceGetAttribute\n"); 1368 printf(" Managed Memory: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1369 checkResult( 1370 cuDeviceGetAttribute( 1371 &TmpInt, CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS, Device), 1372 "Error returned from cuDeviceGetAttribute\n"); 1373 printf(" Concurrent Managed Memory: \t\t%s \n", BOOL2TEXT(TmpInt)); 1374 checkResult( 1375 cuDeviceGetAttribute( 1376 &TmpInt, CU_DEVICE_ATTRIBUTE_COMPUTE_PREEMPTION_SUPPORTED, Device), 1377 "Error returned from cuDeviceGetAttribute\n"); 1378 printf(" Preemption Supported: \t\t%s \n", BOOL2TEXT(TmpInt)); 1379 checkResult(cuDeviceGetAttribute( 1380 &TmpInt, CU_DEVICE_ATTRIBUTE_COOPERATIVE_LAUNCH, Device), 1381 "Error returned from cuDeviceGetAttribute\n"); 1382 printf(" Cooperative Launch: \t\t%s \n", BOOL2TEXT(TmpInt)); 1383 checkResult(cuDeviceGetAttribute( 1384 &TmpInt, CU_DEVICE_ATTRIBUTE_MULTI_GPU_BOARD, Device), 1385 "Error returned from cuDeviceGetAttribute\n"); 1386 printf(" Multi-Device Boars: \t\t%s \n", BOOL2TEXT(TmpInt)); 1387 checkResult( 1388 cuDeviceGetAttribute( 1389 &TmpInt, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, Device), 1390 "Error returned from cuDeviceGetAttribute\n"); 1391 checkResult( 1392 cuDeviceGetAttribute( 1393 &TmpInt2, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, Device), 1394 "Error returned from cuDeviceGetAttribute\n"); 1395 printf(" Compute Capabilities: \t\t%d%d \n", TmpInt, TmpInt2); 1396 } 1397 1398 int createEvent(int DeviceId, void **P) { 1399 CUevent Event = nullptr; 1400 if (EventPool[DeviceId]->acquire(Event) != OFFLOAD_SUCCESS) 1401 return OFFLOAD_FAIL; 1402 *P = Event; 1403 return OFFLOAD_SUCCESS; 1404 } 1405 1406 int destroyEvent(int DeviceId, void *EventPtr) { 1407 EventPool[DeviceId]->release(reinterpret_cast<CUevent>(EventPtr)); 1408 return OFFLOAD_SUCCESS; 1409 } 1410 1411 int waitEvent(const int DeviceId, __tgt_async_info *AsyncInfo, 1412 void *EventPtr) const { 1413 CUstream Stream = getStream(DeviceId, AsyncInfo); 1414 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 1415 1416 // We don't use CU_EVENT_WAIT_DEFAULT here as it is only available from 1417 // specific CUDA version, and defined as 0x0. In previous version, per CUDA 1418 // API document, that argument has to be 0x0. 1419 CUresult Err = cuStreamWaitEvent(Stream, Event, 0); 1420 if (Err != CUDA_SUCCESS) { 1421 DP("Error when waiting event. stream = " DPxMOD ", event = " DPxMOD "\n", 1422 DPxPTR(Stream), DPxPTR(Event)); 1423 CUDA_ERR_STRING(Err); 1424 return OFFLOAD_FAIL; 1425 } 1426 1427 return OFFLOAD_SUCCESS; 1428 } 1429 1430 int releaseAsyncInfo(int DeviceId, __tgt_async_info *AsyncInfo) const { 1431 if (AsyncInfo->Queue) { 1432 StreamPool[DeviceId]->release( 1433 reinterpret_cast<CUstream>(AsyncInfo->Queue)); 1434 AsyncInfo->Queue = nullptr; 1435 } 1436 1437 return OFFLOAD_SUCCESS; 1438 } 1439 1440 int initAsyncInfo(int DeviceId, __tgt_async_info **AsyncInfo) const { 1441 *AsyncInfo = new __tgt_async_info; 1442 getStream(DeviceId, *AsyncInfo); 1443 return OFFLOAD_SUCCESS; 1444 } 1445 1446 int initDeviceInfo(int DeviceId, __tgt_device_info *DeviceInfo, 1447 const char **ErrStr) const { 1448 assert(DeviceInfo && "DeviceInfo is nullptr"); 1449 1450 if (!DeviceInfo->Context) 1451 DeviceInfo->Context = DeviceData[DeviceId].Context; 1452 if (!DeviceInfo->Device) { 1453 CUdevice Dev; 1454 CUresult Err = cuDeviceGet(&Dev, DeviceId); 1455 if (Err == CUDA_SUCCESS) { 1456 DeviceInfo->Device = reinterpret_cast<void *>(Dev); 1457 } else { 1458 cuGetErrorString(Err, ErrStr); 1459 return OFFLOAD_FAIL; 1460 } 1461 } 1462 return OFFLOAD_SUCCESS; 1463 } 1464 1465 int setContext(int DeviceId) { 1466 assert(InitializedFlags[DeviceId] && "Device is not initialized"); 1467 1468 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 1469 if (!checkResult(Err, "error returned from cuCtxSetCurrent")) 1470 return OFFLOAD_FAIL; 1471 1472 return OFFLOAD_SUCCESS; 1473 } 1474 }; 1475 1476 DeviceRTLTy DeviceRTL; 1477 } // namespace 1478 1479 // Exposed library API function 1480 #ifdef __cplusplus 1481 extern "C" { 1482 #endif 1483 1484 int32_t __tgt_rtl_is_valid_binary(__tgt_device_image *image) { 1485 return elf_check_machine(image, /* EM_CUDA */ 190); 1486 } 1487 1488 int32_t __tgt_rtl_number_of_devices() { return DeviceRTL.getNumOfDevices(); } 1489 1490 int64_t __tgt_rtl_init_requires(int64_t RequiresFlags) { 1491 DP("Init requires flags to %" PRId64 "\n", RequiresFlags); 1492 DeviceRTL.setRequiresFlag(RequiresFlags); 1493 return RequiresFlags; 1494 } 1495 1496 int32_t __tgt_rtl_is_data_exchangable(int32_t src_dev_id, int dst_dev_id) { 1497 if (DeviceRTL.isValidDeviceId(src_dev_id) && 1498 DeviceRTL.isValidDeviceId(dst_dev_id)) 1499 return 1; 1500 1501 return 0; 1502 } 1503 1504 int32_t __tgt_rtl_init_device(int32_t device_id) { 1505 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1506 // Context is set when init the device. 1507 1508 return DeviceRTL.initDevice(device_id); 1509 } 1510 1511 int32_t __tgt_rtl_deinit_device(int32_t device_id) { 1512 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1513 // Context is set when deinit the device. 1514 1515 return DeviceRTL.deinitDevice(device_id); 1516 } 1517 1518 __tgt_target_table *__tgt_rtl_load_binary(int32_t device_id, 1519 __tgt_device_image *image) { 1520 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1521 1522 if (DeviceRTL.setContext(device_id) != OFFLOAD_SUCCESS) 1523 return nullptr; 1524 1525 return DeviceRTL.loadBinary(device_id, image); 1526 } 1527 1528 void *__tgt_rtl_data_alloc(int32_t device_id, int64_t size, void *, 1529 int32_t kind) { 1530 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1531 1532 if (DeviceRTL.setContext(device_id) != OFFLOAD_SUCCESS) 1533 return nullptr; 1534 1535 return DeviceRTL.dataAlloc(device_id, size, (TargetAllocTy)kind); 1536 } 1537 1538 int32_t __tgt_rtl_data_submit(int32_t device_id, void *tgt_ptr, void *hst_ptr, 1539 int64_t size) { 1540 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1541 // Context is set in __tgt_rtl_data_submit_async. 1542 1543 __tgt_async_info AsyncInfo; 1544 const int32_t rc = __tgt_rtl_data_submit_async(device_id, tgt_ptr, hst_ptr, 1545 size, &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_data_submit_async(int32_t device_id, void *tgt_ptr, 1553 void *hst_ptr, int64_t size, 1554 __tgt_async_info *async_info_ptr) { 1555 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1556 assert(async_info_ptr && "async_info_ptr is nullptr"); 1557 1558 if (DeviceRTL.setContext(device_id) != OFFLOAD_SUCCESS) 1559 return OFFLOAD_FAIL; 1560 1561 return DeviceRTL.dataSubmit(device_id, tgt_ptr, hst_ptr, size, 1562 async_info_ptr); 1563 } 1564 1565 int32_t __tgt_rtl_data_retrieve(int32_t device_id, void *hst_ptr, void *tgt_ptr, 1566 int64_t size) { 1567 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1568 // Context is set in __tgt_rtl_data_retrieve_async. 1569 1570 __tgt_async_info AsyncInfo; 1571 const int32_t rc = __tgt_rtl_data_retrieve_async(device_id, hst_ptr, tgt_ptr, 1572 size, &AsyncInfo); 1573 if (rc != OFFLOAD_SUCCESS) 1574 return OFFLOAD_FAIL; 1575 1576 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1577 } 1578 1579 int32_t __tgt_rtl_data_retrieve_async(int32_t device_id, void *hst_ptr, 1580 void *tgt_ptr, int64_t size, 1581 __tgt_async_info *async_info_ptr) { 1582 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1583 assert(async_info_ptr && "async_info_ptr is nullptr"); 1584 1585 if (DeviceRTL.setContext(device_id) != OFFLOAD_SUCCESS) 1586 return OFFLOAD_FAIL; 1587 1588 return DeviceRTL.dataRetrieve(device_id, hst_ptr, tgt_ptr, size, 1589 async_info_ptr); 1590 } 1591 1592 int32_t __tgt_rtl_data_exchange_async(int32_t src_dev_id, void *src_ptr, 1593 int dst_dev_id, void *dst_ptr, 1594 int64_t size, 1595 __tgt_async_info *AsyncInfo) { 1596 assert(DeviceRTL.isValidDeviceId(src_dev_id) && "src_dev_id is invalid"); 1597 assert(DeviceRTL.isValidDeviceId(dst_dev_id) && "dst_dev_id is invalid"); 1598 assert(AsyncInfo && "AsyncInfo is nullptr"); 1599 // NOTE: We don't need to set context for data exchange as the device contexts 1600 // are passed to CUDA function directly. 1601 return DeviceRTL.dataExchange(src_dev_id, src_ptr, dst_dev_id, dst_ptr, size, 1602 AsyncInfo); 1603 } 1604 1605 int32_t __tgt_rtl_data_exchange(int32_t src_dev_id, void *src_ptr, 1606 int32_t dst_dev_id, void *dst_ptr, 1607 int64_t size) { 1608 assert(DeviceRTL.isValidDeviceId(src_dev_id) && "src_dev_id is invalid"); 1609 assert(DeviceRTL.isValidDeviceId(dst_dev_id) && "dst_dev_id is invalid"); 1610 // Context is set in __tgt_rtl_data_exchange_async. 1611 1612 __tgt_async_info AsyncInfo; 1613 const int32_t rc = __tgt_rtl_data_exchange_async( 1614 src_dev_id, src_ptr, dst_dev_id, dst_ptr, size, &AsyncInfo); 1615 if (rc != OFFLOAD_SUCCESS) 1616 return OFFLOAD_FAIL; 1617 1618 return __tgt_rtl_synchronize(src_dev_id, &AsyncInfo); 1619 } 1620 1621 int32_t __tgt_rtl_data_delete(int32_t device_id, void *tgt_ptr) { 1622 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1623 1624 if (DeviceRTL.setContext(device_id) != OFFLOAD_SUCCESS) 1625 return OFFLOAD_FAIL; 1626 1627 return DeviceRTL.dataDelete(device_id, tgt_ptr); 1628 } 1629 1630 int32_t __tgt_rtl_run_target_team_region(int32_t device_id, void *tgt_entry_ptr, 1631 void **tgt_args, 1632 ptrdiff_t *tgt_offsets, 1633 int32_t arg_num, int32_t team_num, 1634 int32_t thread_limit, 1635 uint64_t loop_tripcount) { 1636 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1637 // Context is set in __tgt_rtl_run_target_team_region_async. 1638 1639 __tgt_async_info AsyncInfo; 1640 const int32_t rc = __tgt_rtl_run_target_team_region_async( 1641 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, team_num, 1642 thread_limit, loop_tripcount, &AsyncInfo); 1643 if (rc != OFFLOAD_SUCCESS) 1644 return OFFLOAD_FAIL; 1645 1646 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1647 } 1648 1649 int32_t __tgt_rtl_run_target_team_region_async( 1650 int32_t device_id, void *tgt_entry_ptr, void **tgt_args, 1651 ptrdiff_t *tgt_offsets, int32_t arg_num, int32_t team_num, 1652 int32_t thread_limit, uint64_t loop_tripcount, 1653 __tgt_async_info *async_info_ptr) { 1654 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1655 1656 if (DeviceRTL.setContext(device_id) != OFFLOAD_SUCCESS) 1657 return OFFLOAD_FAIL; 1658 1659 return DeviceRTL.runTargetTeamRegion( 1660 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, team_num, 1661 thread_limit, loop_tripcount, async_info_ptr); 1662 } 1663 1664 int32_t __tgt_rtl_run_target_region(int32_t device_id, void *tgt_entry_ptr, 1665 void **tgt_args, ptrdiff_t *tgt_offsets, 1666 int32_t arg_num) { 1667 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1668 // Context is set in __tgt_rtl_run_target_region_async. 1669 1670 __tgt_async_info AsyncInfo; 1671 const int32_t rc = __tgt_rtl_run_target_region_async( 1672 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, &AsyncInfo); 1673 if (rc != OFFLOAD_SUCCESS) 1674 return OFFLOAD_FAIL; 1675 1676 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1677 } 1678 1679 int32_t __tgt_rtl_run_target_region_async(int32_t device_id, 1680 void *tgt_entry_ptr, void **tgt_args, 1681 ptrdiff_t *tgt_offsets, 1682 int32_t arg_num, 1683 __tgt_async_info *async_info_ptr) { 1684 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1685 // Context is set in __tgt_rtl_run_target_team_region_async. 1686 return __tgt_rtl_run_target_team_region_async( 1687 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, 1688 /* team num*/ 1, /* thread_limit */ 1, /* loop_tripcount */ 0, 1689 async_info_ptr); 1690 } 1691 1692 int32_t __tgt_rtl_synchronize(int32_t device_id, 1693 __tgt_async_info *async_info_ptr) { 1694 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1695 assert(async_info_ptr && "async_info_ptr is nullptr"); 1696 assert(async_info_ptr->Queue && "async_info_ptr->Queue is nullptr"); 1697 // NOTE: We don't need to set context for stream sync. 1698 return DeviceRTL.synchronize(device_id, async_info_ptr); 1699 } 1700 1701 void __tgt_rtl_set_info_flag(uint32_t NewInfoLevel) { 1702 std::atomic<uint32_t> &InfoLevel = getInfoLevelInternal(); 1703 InfoLevel.store(NewInfoLevel); 1704 } 1705 1706 void __tgt_rtl_print_device_info(int32_t device_id) { 1707 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1708 // NOTE: We don't need to set context for print device info. 1709 DeviceRTL.printDeviceInfo(device_id); 1710 } 1711 1712 int32_t __tgt_rtl_create_event(int32_t device_id, void **event) { 1713 assert(event && "event is nullptr"); 1714 1715 if (DeviceRTL.setContext(device_id) != OFFLOAD_SUCCESS) 1716 return OFFLOAD_FAIL; 1717 1718 return DeviceRTL.createEvent(device_id, event); 1719 } 1720 1721 int32_t __tgt_rtl_record_event(int32_t device_id, void *event_ptr, 1722 __tgt_async_info *async_info_ptr) { 1723 assert(async_info_ptr && "async_info_ptr is nullptr"); 1724 assert(async_info_ptr->Queue && "async_info_ptr->Queue is nullptr"); 1725 assert(event_ptr && "event_ptr is nullptr"); 1726 // NOTE: We might not need to set context for event record. 1727 return recordEvent(event_ptr, async_info_ptr); 1728 } 1729 1730 int32_t __tgt_rtl_wait_event(int32_t device_id, void *event_ptr, 1731 __tgt_async_info *async_info_ptr) { 1732 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1733 assert(async_info_ptr && "async_info_ptr is nullptr"); 1734 assert(event_ptr && "event is nullptr"); 1735 // NOTE: We might not need to set context for event sync. 1736 return DeviceRTL.waitEvent(device_id, async_info_ptr, event_ptr); 1737 } 1738 1739 int32_t __tgt_rtl_sync_event(int32_t device_id, void *event_ptr) { 1740 assert(event_ptr && "event is nullptr"); 1741 // NOTE: We might not need to set context for event sync. 1742 return syncEvent(event_ptr); 1743 } 1744 1745 int32_t __tgt_rtl_destroy_event(int32_t device_id, void *event_ptr) { 1746 assert(event_ptr && "event is nullptr"); 1747 1748 if (DeviceRTL.setContext(device_id) != OFFLOAD_SUCCESS) 1749 return OFFLOAD_FAIL; 1750 1751 return DeviceRTL.destroyEvent(device_id, event_ptr); 1752 } 1753 1754 int32_t __tgt_rtl_release_async_info(int32_t device_id, 1755 __tgt_async_info *async_info) { 1756 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1757 assert(async_info && "async_info is nullptr"); 1758 1759 if (DeviceRTL.setContext(device_id) != OFFLOAD_SUCCESS) 1760 return OFFLOAD_FAIL; 1761 1762 return DeviceRTL.releaseAsyncInfo(device_id, async_info); 1763 } 1764 1765 int32_t __tgt_rtl_init_async_info(int32_t device_id, 1766 __tgt_async_info **async_info) { 1767 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1768 assert(async_info && "async_info is nullptr"); 1769 1770 if (DeviceRTL.setContext(device_id) != OFFLOAD_SUCCESS) 1771 return OFFLOAD_FAIL; 1772 1773 return DeviceRTL.initAsyncInfo(device_id, async_info); 1774 } 1775 1776 int32_t __tgt_rtl_init_device_info(int32_t device_id, 1777 __tgt_device_info *device_info_ptr, 1778 const char **err_str) { 1779 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1780 assert(device_info_ptr && "device_info_ptr is nullptr"); 1781 1782 if (DeviceRTL.setContext(device_id) != OFFLOAD_SUCCESS) 1783 return OFFLOAD_FAIL; 1784 1785 return DeviceRTL.initDeviceInfo(device_id, device_info_ptr, err_str); 1786 } 1787 1788 #ifdef __cplusplus 1789 } 1790 #endif 1791