1 //===----RTLs/cuda/src/rtl.cpp - Target RTLs Implementation ------- C++ -*-===// 2 // 3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. 4 // See https://llvm.org/LICENSE.txt for license information. 5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception 6 // 7 //===----------------------------------------------------------------------===// 8 // 9 // RTL for CUDA machine 10 // 11 //===----------------------------------------------------------------------===// 12 13 #include <cassert> 14 #include <cstddef> 15 #include <cuda.h> 16 #include <list> 17 #include <memory> 18 #include <mutex> 19 #include <string> 20 #include <unordered_map> 21 #include <vector> 22 23 #include "Debug.h" 24 #include "DeviceEnvironment.h" 25 #include "omptargetplugin.h" 26 27 #define TARGET_NAME CUDA 28 #define DEBUG_PREFIX "Target " GETNAME(TARGET_NAME) " RTL" 29 30 #include "MemoryManager.h" 31 32 #include "llvm/Frontend/OpenMP/OMPConstants.h" 33 34 // Utility for retrieving and printing CUDA error string. 35 #ifdef OMPTARGET_DEBUG 36 #define CUDA_ERR_STRING(err) \ 37 do { \ 38 if (getDebugLevel() > 0) { \ 39 const char *errStr = nullptr; \ 40 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 41 if (errStr_status == CUDA_ERROR_INVALID_VALUE) \ 42 REPORT("Unrecognized CUDA error code: %d\n", err); \ 43 else if (errStr_status == CUDA_SUCCESS) \ 44 REPORT("CUDA error is: %s\n", errStr); \ 45 else { \ 46 REPORT("Unresolved CUDA error code: %d\n", err); \ 47 REPORT("Unsuccessful cuGetErrorString return status: %d\n", \ 48 errStr_status); \ 49 } \ 50 } else { \ 51 const char *errStr = nullptr; \ 52 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 53 if (errStr_status == CUDA_SUCCESS) \ 54 REPORT("%s \n", errStr); \ 55 } \ 56 } while (false) 57 #else // OMPTARGET_DEBUG 58 #define CUDA_ERR_STRING(err) \ 59 do { \ 60 const char *errStr = nullptr; \ 61 CUresult errStr_status = cuGetErrorString(err, &errStr); \ 62 if (errStr_status == CUDA_SUCCESS) \ 63 REPORT("%s \n", errStr); \ 64 } while (false) 65 #endif // OMPTARGET_DEBUG 66 67 #define BOOL2TEXT(b) ((b) ? "Yes" : "No") 68 69 #include "elf_common.h" 70 71 /// Keep entries table per device. 72 struct FuncOrGblEntryTy { 73 __tgt_target_table Table; 74 std::vector<__tgt_offload_entry> Entries; 75 }; 76 77 /// Use a single entity to encode a kernel and a set of flags. 78 struct KernelTy { 79 CUfunction Func; 80 81 // execution mode of kernel 82 llvm::omp::OMPTgtExecModeFlags ExecutionMode; 83 84 /// Maximal number of threads per block for this kernel. 85 int MaxThreadsPerBlock = 0; 86 87 KernelTy(CUfunction _Func, llvm::omp::OMPTgtExecModeFlags _ExecutionMode) 88 : Func(_Func), ExecutionMode(_ExecutionMode) {} 89 }; 90 91 namespace { 92 bool checkResult(CUresult Err, const char *ErrMsg) { 93 if (Err == CUDA_SUCCESS) 94 return true; 95 96 REPORT("%s", ErrMsg); 97 CUDA_ERR_STRING(Err); 98 return false; 99 } 100 101 int memcpyDtoD(const void *SrcPtr, void *DstPtr, int64_t Size, 102 CUstream Stream) { 103 CUresult Err = 104 cuMemcpyDtoDAsync((CUdeviceptr)DstPtr, (CUdeviceptr)SrcPtr, Size, Stream); 105 106 if (Err != CUDA_SUCCESS) { 107 DP("Error when copying data from device to device. Pointers: src " 108 "= " DPxMOD ", dst = " DPxMOD ", size = %" PRId64 "\n", 109 DPxPTR(SrcPtr), DPxPTR(DstPtr), Size); 110 CUDA_ERR_STRING(Err); 111 return OFFLOAD_FAIL; 112 } 113 114 return OFFLOAD_SUCCESS; 115 } 116 117 int recordEvent(void *EventPtr, __tgt_async_info *AsyncInfo) { 118 CUstream Stream = reinterpret_cast<CUstream>(AsyncInfo->Queue); 119 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 120 121 CUresult Err = cuEventRecord(Event, Stream); 122 if (Err != CUDA_SUCCESS) { 123 DP("Error when recording event. stream = " DPxMOD ", event = " DPxMOD "\n", 124 DPxPTR(Stream), DPxPTR(Event)); 125 CUDA_ERR_STRING(Err); 126 return OFFLOAD_FAIL; 127 } 128 129 return OFFLOAD_SUCCESS; 130 } 131 132 int syncEvent(void *EventPtr) { 133 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 134 135 CUresult Err = cuEventSynchronize(Event); 136 if (Err != CUDA_SUCCESS) { 137 DP("Error when syncing event = " DPxMOD "\n", DPxPTR(Event)); 138 CUDA_ERR_STRING(Err); 139 return OFFLOAD_FAIL; 140 } 141 142 return OFFLOAD_SUCCESS; 143 } 144 145 // Structure contains per-device data 146 struct DeviceDataTy { 147 /// List that contains all the kernels. 148 std::list<KernelTy> KernelsList; 149 150 std::list<FuncOrGblEntryTy> FuncGblEntries; 151 152 CUcontext Context = nullptr; 153 // Device properties 154 int ThreadsPerBlock = 0; 155 int BlocksPerGrid = 0; 156 int WarpSize = 0; 157 // OpenMP properties 158 int NumTeams = 0; 159 int NumThreads = 0; 160 }; 161 162 /// Resource allocator where \p T is the resource type. 163 /// Functions \p create and \p destroy return OFFLOAD_SUCCESS and OFFLOAD_FAIL 164 /// accordingly. The implementation should not raise any exception. 165 template <typename T> class AllocatorTy { 166 public: 167 /// Create a resource and assign to R. 168 int create(T &R) noexcept; 169 /// Destroy the resource. 170 int destroy(T) noexcept; 171 }; 172 173 /// Allocator for CUstream. 174 template <> class AllocatorTy<CUstream> { 175 CUcontext Context; 176 177 public: 178 AllocatorTy(CUcontext C) noexcept : Context(C) {} 179 180 /// See AllocatorTy<T>::create. 181 int create(CUstream &Stream) noexcept { 182 if (!checkResult(cuCtxSetCurrent(Context), 183 "Error returned from cuCtxSetCurrent\n")) 184 return OFFLOAD_FAIL; 185 186 if (!checkResult(cuStreamCreate(&Stream, CU_STREAM_NON_BLOCKING), 187 "Error returned from cuStreamCreate\n")) 188 return OFFLOAD_FAIL; 189 190 return OFFLOAD_SUCCESS; 191 } 192 193 /// See AllocatorTy<T>::destroy. 194 int destroy(CUstream Stream) noexcept { 195 if (!checkResult(cuCtxSetCurrent(Context), 196 "Error returned from cuCtxSetCurrent\n")) 197 return OFFLOAD_FAIL; 198 if (!checkResult(cuStreamDestroy(Stream), 199 "Error returned from cuStreamDestroy\n")) 200 return OFFLOAD_FAIL; 201 202 return OFFLOAD_SUCCESS; 203 } 204 }; 205 206 /// Allocator for CUevent. 207 template <> class AllocatorTy<CUevent> { 208 public: 209 /// See AllocatorTy<T>::create. 210 int create(CUevent &Event) noexcept { 211 if (!checkResult(cuEventCreate(&Event, CU_EVENT_DEFAULT), 212 "Error returned from cuEventCreate\n")) 213 return OFFLOAD_FAIL; 214 215 return OFFLOAD_SUCCESS; 216 } 217 218 /// See AllocatorTy<T>::destroy. 219 int destroy(CUevent Event) noexcept { 220 if (!checkResult(cuEventDestroy(Event), 221 "Error returned from cuEventDestroy\n")) 222 return OFFLOAD_FAIL; 223 224 return OFFLOAD_SUCCESS; 225 } 226 }; 227 228 /// A generic pool of resources where \p T is the resource type. 229 /// \p T should be copyable as the object is stored in \p std::vector . 230 template <typename T> class ResourcePoolTy { 231 /// Index of the next available resource. 232 size_t Next = 0; 233 /// Mutex to guard the pool. 234 std::mutex Mutex; 235 /// Pool of resources. 236 std::vector<T> Resources; 237 /// A reference to the corresponding allocator. 238 AllocatorTy<T> Allocator; 239 240 /// If `Resources` is used up, we will fill in more resources. It assumes that 241 /// the new size `Size` should be always larger than the current size. 242 bool resize(size_t Size) { 243 auto CurSize = Resources.size(); 244 assert(Size > CurSize && "Unexpected smaller size"); 245 Resources.reserve(Size); 246 for (auto I = CurSize; I < Size; ++I) { 247 T NewItem; 248 int Ret = Allocator.create(NewItem); 249 if (Ret != OFFLOAD_SUCCESS) 250 return false; 251 Resources.push_back(NewItem); 252 } 253 return true; 254 } 255 256 public: 257 ResourcePoolTy(AllocatorTy<T> &&A, size_t Size = 0) noexcept 258 : Allocator(std::move(A)) { 259 if (Size) 260 (void)resize(Size); 261 } 262 263 ~ResourcePoolTy() noexcept { clear(); } 264 265 /// Get a resource from pool. `Next` always points to the next available 266 /// resource. That means, `[0, next-1]` have been assigned, and `[id,]` are 267 /// still available. If there is no resource left, we will ask for more. Each 268 /// time a resource is assigned, the id will increase one. 269 /// xxxxxs+++++++++ 270 /// ^ 271 /// Next 272 /// After assignment, the pool becomes the following and s is assigned. 273 /// xxxxxs+++++++++ 274 /// ^ 275 /// Next 276 int acquire(T &R) noexcept { 277 std::lock_guard<std::mutex> LG(Mutex); 278 if (Next == Resources.size()) { 279 auto NewSize = Resources.size() ? Resources.size() * 2 : 1; 280 if (!resize(NewSize)) 281 return OFFLOAD_FAIL; 282 } 283 284 assert(Next < Resources.size()); 285 286 R = Resources[Next++]; 287 288 return OFFLOAD_SUCCESS; 289 } 290 291 /// Return the resource back to the pool. When we return a resource, we need 292 /// to first decrease `Next`, and then copy the resource back. It is worth 293 /// noting that, the order of resources return might be different from that 294 /// they're assigned, that saying, at some point, there might be two identical 295 /// resources. 296 /// xxax+a+++++ 297 /// ^ 298 /// Next 299 /// However, it doesn't matter, because they're always on the two sides of 300 /// `Next`. The left one will in the end be overwritten by another resource. 301 /// Therefore, after several execution, the order of pool might be different 302 /// from its initial state. 303 void release(T R) noexcept { 304 std::lock_guard<std::mutex> LG(Mutex); 305 Resources[--Next] = R; 306 } 307 308 /// Released all stored resources and clear the pool. 309 /// Note: This function is not thread safe. Be sure to guard it if necessary. 310 void clear() noexcept { 311 for (auto &R : Resources) 312 (void)Allocator.destroy(R); 313 Resources.clear(); 314 } 315 }; 316 317 class DeviceRTLTy { 318 int NumberOfDevices; 319 // OpenMP environment properties 320 int EnvNumTeams; 321 int EnvTeamLimit; 322 int EnvTeamThreadLimit; 323 // OpenMP requires flags 324 int64_t RequiresFlags; 325 // Amount of dynamic shared memory to use at launch. 326 uint64_t DynamicMemorySize; 327 // Number of initial streams for each device. 328 int NumInitialStreams = 32; 329 330 static constexpr const int HardTeamLimit = 1U << 16U; // 64k 331 static constexpr const int HardThreadLimit = 1024; 332 static constexpr const int DefaultNumTeams = 128; 333 static constexpr const int DefaultNumThreads = 128; 334 335 using StreamPoolTy = ResourcePoolTy<CUstream>; 336 std::vector<std::unique_ptr<StreamPoolTy>> StreamPool; 337 338 ResourcePoolTy<CUevent> EventPool; 339 340 std::vector<DeviceDataTy> DeviceData; 341 std::vector<CUmodule> Modules; 342 343 /// A class responsible for interacting with device native runtime library to 344 /// allocate and free memory. 345 class CUDADeviceAllocatorTy : public DeviceAllocatorTy { 346 const int DeviceId; 347 const std::vector<DeviceDataTy> &DeviceData; 348 std::unordered_map<void *, TargetAllocTy> HostPinnedAllocs; 349 350 public: 351 CUDADeviceAllocatorTy(int DeviceId, std::vector<DeviceDataTy> &DeviceData) 352 : DeviceId(DeviceId), DeviceData(DeviceData) {} 353 354 void *allocate(size_t Size, void *, TargetAllocTy Kind) override { 355 if (Size == 0) 356 return nullptr; 357 358 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 359 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 360 return nullptr; 361 362 void *MemAlloc = nullptr; 363 switch (Kind) { 364 case TARGET_ALLOC_DEFAULT: 365 case TARGET_ALLOC_DEVICE: 366 CUdeviceptr DevicePtr; 367 Err = cuMemAlloc(&DevicePtr, Size); 368 MemAlloc = (void *)DevicePtr; 369 if (!checkResult(Err, "Error returned from cuMemAlloc\n")) 370 return nullptr; 371 break; 372 case TARGET_ALLOC_HOST: 373 void *HostPtr; 374 Err = cuMemAllocHost(&HostPtr, Size); 375 MemAlloc = HostPtr; 376 if (!checkResult(Err, "Error returned from cuMemAllocHost\n")) 377 return nullptr; 378 HostPinnedAllocs[MemAlloc] = Kind; 379 break; 380 case TARGET_ALLOC_SHARED: 381 CUdeviceptr SharedPtr; 382 Err = cuMemAllocManaged(&SharedPtr, Size, CU_MEM_ATTACH_GLOBAL); 383 MemAlloc = (void *)SharedPtr; 384 if (!checkResult(Err, "Error returned from cuMemAllocManaged\n")) 385 return nullptr; 386 break; 387 } 388 389 return MemAlloc; 390 } 391 392 int free(void *TgtPtr) override { 393 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 394 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 395 return OFFLOAD_FAIL; 396 397 // Host pinned memory must be freed differently. 398 TargetAllocTy Kind = 399 (HostPinnedAllocs.find(TgtPtr) == HostPinnedAllocs.end()) 400 ? TARGET_ALLOC_DEFAULT 401 : TARGET_ALLOC_HOST; 402 switch (Kind) { 403 case TARGET_ALLOC_DEFAULT: 404 case TARGET_ALLOC_DEVICE: 405 case TARGET_ALLOC_SHARED: 406 Err = cuMemFree((CUdeviceptr)TgtPtr); 407 if (!checkResult(Err, "Error returned from cuMemFree\n")) 408 return OFFLOAD_FAIL; 409 break; 410 case TARGET_ALLOC_HOST: 411 Err = cuMemFreeHost(TgtPtr); 412 if (!checkResult(Err, "Error returned from cuMemFreeHost\n")) 413 return OFFLOAD_FAIL; 414 break; 415 } 416 417 return OFFLOAD_SUCCESS; 418 } 419 }; 420 421 /// A vector of device allocators 422 std::vector<CUDADeviceAllocatorTy> DeviceAllocators; 423 424 /// A vector of memory managers. Since the memory manager is non-copyable and 425 // non-removable, we wrap them into std::unique_ptr. 426 std::vector<std::unique_ptr<MemoryManagerTy>> MemoryManagers; 427 428 /// Whether use memory manager 429 bool UseMemoryManager = true; 430 431 // Record entry point associated with device 432 void addOffloadEntry(const int DeviceId, const __tgt_offload_entry entry) { 433 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 434 E.Entries.push_back(entry); 435 } 436 437 // Return a pointer to the entry associated with the pointer 438 const __tgt_offload_entry *getOffloadEntry(const int DeviceId, 439 const void *Addr) const { 440 for (const __tgt_offload_entry &Itr : 441 DeviceData[DeviceId].FuncGblEntries.back().Entries) 442 if (Itr.addr == Addr) 443 return &Itr; 444 445 return nullptr; 446 } 447 448 // Return the pointer to the target entries table 449 __tgt_target_table *getOffloadEntriesTable(const int DeviceId) { 450 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 451 452 if (E.Entries.empty()) 453 return nullptr; 454 455 // Update table info according to the entries and return the pointer 456 E.Table.EntriesBegin = E.Entries.data(); 457 E.Table.EntriesEnd = E.Entries.data() + E.Entries.size(); 458 459 return &E.Table; 460 } 461 462 // Clear entries table for a device 463 void clearOffloadEntriesTable(const int DeviceId) { 464 DeviceData[DeviceId].FuncGblEntries.emplace_back(); 465 FuncOrGblEntryTy &E = DeviceData[DeviceId].FuncGblEntries.back(); 466 E.Entries.clear(); 467 E.Table.EntriesBegin = E.Table.EntriesEnd = nullptr; 468 } 469 470 CUstream getStream(const int DeviceId, __tgt_async_info *AsyncInfo) const { 471 assert(AsyncInfo && "AsyncInfo is nullptr"); 472 473 if (!AsyncInfo->Queue) { 474 CUstream S; 475 if (StreamPool[DeviceId]->acquire(S) != OFFLOAD_SUCCESS) 476 return nullptr; 477 478 AsyncInfo->Queue = S; 479 } 480 481 return reinterpret_cast<CUstream>(AsyncInfo->Queue); 482 } 483 484 public: 485 // This class should not be copied 486 DeviceRTLTy(const DeviceRTLTy &) = delete; 487 DeviceRTLTy(DeviceRTLTy &&) = delete; 488 489 DeviceRTLTy() 490 : NumberOfDevices(0), EnvNumTeams(-1), EnvTeamLimit(-1), 491 EnvTeamThreadLimit(-1), RequiresFlags(OMP_REQ_UNDEFINED), 492 DynamicMemorySize(0), EventPool(AllocatorTy<CUevent>()) { 493 494 DP("Start initializing CUDA\n"); 495 496 CUresult Err = cuInit(0); 497 if (Err == CUDA_ERROR_INVALID_HANDLE) { 498 // Can't call cuGetErrorString if dlsym failed 499 DP("Failed to load CUDA shared library\n"); 500 return; 501 } 502 if (!checkResult(Err, "Error returned from cuInit\n")) { 503 return; 504 } 505 506 Err = cuDeviceGetCount(&NumberOfDevices); 507 if (!checkResult(Err, "Error returned from cuDeviceGetCount\n")) 508 return; 509 510 if (NumberOfDevices == 0) { 511 DP("There are no devices supporting CUDA.\n"); 512 return; 513 } 514 515 DeviceData.resize(NumberOfDevices); 516 StreamPool.resize(NumberOfDevices); 517 518 // Get environment variables regarding teams 519 if (const char *EnvStr = getenv("OMP_TEAM_LIMIT")) { 520 // OMP_TEAM_LIMIT has been set 521 EnvTeamLimit = std::stoi(EnvStr); 522 DP("Parsed OMP_TEAM_LIMIT=%d\n", EnvTeamLimit); 523 } 524 if (const char *EnvStr = getenv("OMP_TEAMS_THREAD_LIMIT")) { 525 // OMP_TEAMS_THREAD_LIMIT has been set 526 EnvTeamThreadLimit = std::stoi(EnvStr); 527 DP("Parsed OMP_TEAMS_THREAD_LIMIT=%d\n", EnvTeamThreadLimit); 528 } 529 if (const char *EnvStr = getenv("OMP_NUM_TEAMS")) { 530 // OMP_NUM_TEAMS has been set 531 EnvNumTeams = std::stoi(EnvStr); 532 DP("Parsed OMP_NUM_TEAMS=%d\n", EnvNumTeams); 533 } 534 if (const char *EnvStr = getenv("LIBOMPTARGET_SHARED_MEMORY_SIZE")) { 535 // LIBOMPTARGET_SHARED_MEMORY_SIZE has been set 536 DynamicMemorySize = std::stoi(EnvStr); 537 DP("Parsed LIBOMPTARGET_SHARED_MEMORY_SIZE = %" PRIu64 "\n", 538 DynamicMemorySize); 539 } 540 if (const char *EnvStr = getenv("LIBOMPTARGET_NUM_INITIAL_STREAMS")) { 541 // LIBOMPTARGET_NUM_INITIAL_STREAMS has been set 542 NumInitialStreams = std::stoi(EnvStr); 543 DP("Parsed LIBOMPTARGET_NUM_INITIAL_STREAMS=%d\n", NumInitialStreams); 544 } 545 546 for (int I = 0; I < NumberOfDevices; ++I) 547 DeviceAllocators.emplace_back(I, DeviceData); 548 549 // Get the size threshold from environment variable 550 std::pair<size_t, bool> Res = MemoryManagerTy::getSizeThresholdFromEnv(); 551 UseMemoryManager = Res.second; 552 size_t MemoryManagerThreshold = Res.first; 553 554 if (UseMemoryManager) 555 for (int I = 0; I < NumberOfDevices; ++I) 556 MemoryManagers.emplace_back(std::make_unique<MemoryManagerTy>( 557 DeviceAllocators[I], MemoryManagerThreshold)); 558 } 559 560 ~DeviceRTLTy() { 561 // We first destruct memory managers in case that its dependent data are 562 // destroyed before it. 563 for (auto &M : MemoryManagers) 564 M.release(); 565 566 for (CUmodule &M : Modules) 567 // Close module 568 if (M) 569 checkResult(cuModuleUnload(M), "Error returned from cuModuleUnload\n"); 570 571 for (auto &S : StreamPool) 572 S.reset(); 573 574 EventPool.clear(); 575 576 for (DeviceDataTy &D : DeviceData) { 577 // Destroy context 578 if (D.Context) { 579 checkResult(cuCtxSetCurrent(D.Context), 580 "Error returned from cuCtxSetCurrent\n"); 581 CUdevice Device; 582 checkResult(cuCtxGetDevice(&Device), 583 "Error returned from cuCtxGetDevice\n"); 584 checkResult(cuDevicePrimaryCtxRelease(Device), 585 "Error returned from cuDevicePrimaryCtxRelease\n"); 586 } 587 } 588 } 589 590 // Check whether a given DeviceId is valid 591 bool isValidDeviceId(const int DeviceId) const { 592 return DeviceId >= 0 && DeviceId < NumberOfDevices; 593 } 594 595 int getNumOfDevices() const { return NumberOfDevices; } 596 597 void setRequiresFlag(const int64_t Flags) { this->RequiresFlags = Flags; } 598 599 int initDevice(const int DeviceId) { 600 CUdevice Device; 601 602 DP("Getting device %d\n", DeviceId); 603 CUresult Err = cuDeviceGet(&Device, DeviceId); 604 if (!checkResult(Err, "Error returned from cuDeviceGet\n")) 605 return OFFLOAD_FAIL; 606 607 // Query the current flags of the primary context and set its flags if 608 // it is inactive 609 unsigned int FormerPrimaryCtxFlags = 0; 610 int FormerPrimaryCtxIsActive = 0; 611 Err = cuDevicePrimaryCtxGetState(Device, &FormerPrimaryCtxFlags, 612 &FormerPrimaryCtxIsActive); 613 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxGetState\n")) 614 return OFFLOAD_FAIL; 615 616 if (FormerPrimaryCtxIsActive) { 617 DP("The primary context is active, no change to its flags\n"); 618 if ((FormerPrimaryCtxFlags & CU_CTX_SCHED_MASK) != 619 CU_CTX_SCHED_BLOCKING_SYNC) 620 DP("Warning the current flags are not CU_CTX_SCHED_BLOCKING_SYNC\n"); 621 } else { 622 DP("The primary context is inactive, set its flags to " 623 "CU_CTX_SCHED_BLOCKING_SYNC\n"); 624 Err = cuDevicePrimaryCtxSetFlags(Device, CU_CTX_SCHED_BLOCKING_SYNC); 625 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxSetFlags\n")) 626 return OFFLOAD_FAIL; 627 } 628 629 // Retain the per device primary context and save it to use whenever this 630 // device is selected. 631 Err = cuDevicePrimaryCtxRetain(&DeviceData[DeviceId].Context, Device); 632 if (!checkResult(Err, "Error returned from cuDevicePrimaryCtxRetain\n")) 633 return OFFLOAD_FAIL; 634 635 Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 636 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 637 return OFFLOAD_FAIL; 638 639 // Initialize stream pool 640 if (!StreamPool[DeviceId]) 641 StreamPool[DeviceId] = std::make_unique<StreamPoolTy>( 642 AllocatorTy<CUstream>(DeviceData[DeviceId].Context), 643 NumInitialStreams); 644 645 // Query attributes to determine number of threads/block and blocks/grid. 646 int MaxGridDimX; 647 Err = cuDeviceGetAttribute(&MaxGridDimX, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X, 648 Device); 649 if (Err != CUDA_SUCCESS) { 650 DP("Error getting max grid dimension, use default value %d\n", 651 DeviceRTLTy::DefaultNumTeams); 652 DeviceData[DeviceId].BlocksPerGrid = DeviceRTLTy::DefaultNumTeams; 653 } else if (MaxGridDimX <= DeviceRTLTy::HardTeamLimit) { 654 DP("Using %d CUDA blocks per grid\n", MaxGridDimX); 655 DeviceData[DeviceId].BlocksPerGrid = MaxGridDimX; 656 } else { 657 DP("Max CUDA blocks per grid %d exceeds the hard team limit %d, capping " 658 "at the hard limit\n", 659 MaxGridDimX, DeviceRTLTy::HardTeamLimit); 660 DeviceData[DeviceId].BlocksPerGrid = DeviceRTLTy::HardTeamLimit; 661 } 662 663 // We are only exploiting threads along the x axis. 664 int MaxBlockDimX; 665 Err = cuDeviceGetAttribute(&MaxBlockDimX, 666 CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, Device); 667 if (Err != CUDA_SUCCESS) { 668 DP("Error getting max block dimension, use default value %d\n", 669 DeviceRTLTy::DefaultNumThreads); 670 DeviceData[DeviceId].ThreadsPerBlock = DeviceRTLTy::DefaultNumThreads; 671 } else { 672 DP("Using %d CUDA threads per block\n", MaxBlockDimX); 673 DeviceData[DeviceId].ThreadsPerBlock = MaxBlockDimX; 674 675 if (EnvTeamThreadLimit > 0 && 676 DeviceData[DeviceId].ThreadsPerBlock > EnvTeamThreadLimit) { 677 DP("Max CUDA threads per block %d exceeds the thread limit %d set by " 678 "OMP_TEAMS_THREAD_LIMIT, capping at the limit\n", 679 DeviceData[DeviceId].ThreadsPerBlock, EnvTeamThreadLimit); 680 DeviceData[DeviceId].ThreadsPerBlock = EnvTeamThreadLimit; 681 } 682 if (DeviceData[DeviceId].ThreadsPerBlock > DeviceRTLTy::HardThreadLimit) { 683 DP("Max CUDA threads per block %d exceeds the hard thread limit %d, " 684 "capping at the hard limit\n", 685 DeviceData[DeviceId].ThreadsPerBlock, DeviceRTLTy::HardThreadLimit); 686 DeviceData[DeviceId].ThreadsPerBlock = DeviceRTLTy::HardThreadLimit; 687 } 688 } 689 690 // Get and set warp size 691 int WarpSize; 692 Err = 693 cuDeviceGetAttribute(&WarpSize, CU_DEVICE_ATTRIBUTE_WARP_SIZE, Device); 694 if (Err != CUDA_SUCCESS) { 695 DP("Error getting warp size, assume default value 32\n"); 696 DeviceData[DeviceId].WarpSize = 32; 697 } else { 698 DP("Using warp size %d\n", WarpSize); 699 DeviceData[DeviceId].WarpSize = WarpSize; 700 } 701 702 // Adjust teams to the env variables 703 if (EnvTeamLimit > 0 && DeviceData[DeviceId].BlocksPerGrid > EnvTeamLimit) { 704 DP("Capping max CUDA blocks per grid to OMP_TEAM_LIMIT=%d\n", 705 EnvTeamLimit); 706 DeviceData[DeviceId].BlocksPerGrid = EnvTeamLimit; 707 } 708 709 size_t StackLimit; 710 size_t HeapLimit; 711 if (const char *EnvStr = getenv("LIBOMPTARGET_STACK_SIZE")) { 712 StackLimit = std::stol(EnvStr); 713 if (cuCtxSetLimit(CU_LIMIT_STACK_SIZE, StackLimit) != CUDA_SUCCESS) 714 return OFFLOAD_FAIL; 715 } else { 716 if (cuCtxGetLimit(&StackLimit, CU_LIMIT_STACK_SIZE) != CUDA_SUCCESS) 717 return OFFLOAD_FAIL; 718 } 719 if (const char *EnvStr = getenv("LIBOMPTARGET_HEAP_SIZE")) { 720 HeapLimit = std::stol(EnvStr); 721 if (cuCtxSetLimit(CU_LIMIT_MALLOC_HEAP_SIZE, HeapLimit) != CUDA_SUCCESS) 722 return OFFLOAD_FAIL; 723 } else { 724 if (cuCtxGetLimit(&HeapLimit, CU_LIMIT_MALLOC_HEAP_SIZE) != CUDA_SUCCESS) 725 return OFFLOAD_FAIL; 726 } 727 728 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 729 "Device supports up to %d CUDA blocks and %d threads with a " 730 "warp size of %d\n", 731 DeviceData[DeviceId].BlocksPerGrid, 732 DeviceData[DeviceId].ThreadsPerBlock, DeviceData[DeviceId].WarpSize); 733 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 734 "Device heap size is %d Bytes, device stack size is %d Bytes per " 735 "thread\n", 736 (int)HeapLimit, (int)StackLimit); 737 738 // Set default number of teams 739 if (EnvNumTeams > 0) { 740 DP("Default number of teams set according to environment %d\n", 741 EnvNumTeams); 742 DeviceData[DeviceId].NumTeams = EnvNumTeams; 743 } else { 744 DeviceData[DeviceId].NumTeams = DeviceRTLTy::DefaultNumTeams; 745 DP("Default number of teams set according to library's default %d\n", 746 DeviceRTLTy::DefaultNumTeams); 747 } 748 749 if (DeviceData[DeviceId].NumTeams > DeviceData[DeviceId].BlocksPerGrid) { 750 DP("Default number of teams exceeds device limit, capping at %d\n", 751 DeviceData[DeviceId].BlocksPerGrid); 752 DeviceData[DeviceId].NumTeams = DeviceData[DeviceId].BlocksPerGrid; 753 } 754 755 // Set default number of threads 756 DeviceData[DeviceId].NumThreads = DeviceRTLTy::DefaultNumThreads; 757 DP("Default number of threads set according to library's default %d\n", 758 DeviceRTLTy::DefaultNumThreads); 759 if (DeviceData[DeviceId].NumThreads > 760 DeviceData[DeviceId].ThreadsPerBlock) { 761 DP("Default number of threads exceeds device limit, capping at %d\n", 762 DeviceData[DeviceId].ThreadsPerBlock); 763 DeviceData[DeviceId].NumThreads = DeviceData[DeviceId].ThreadsPerBlock; 764 } 765 766 return OFFLOAD_SUCCESS; 767 } 768 769 __tgt_target_table *loadBinary(const int DeviceId, 770 const __tgt_device_image *Image) { 771 // Set the context we are using 772 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 773 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 774 return nullptr; 775 776 // Clear the offload table as we are going to create a new one. 777 clearOffloadEntriesTable(DeviceId); 778 779 // Create the module and extract the function pointers. 780 CUmodule Module; 781 DP("Load data from image " DPxMOD "\n", DPxPTR(Image->ImageStart)); 782 Err = cuModuleLoadDataEx(&Module, Image->ImageStart, 0, nullptr, nullptr); 783 if (!checkResult(Err, "Error returned from cuModuleLoadDataEx\n")) 784 return nullptr; 785 786 DP("CUDA module successfully loaded!\n"); 787 788 Modules.push_back(Module); 789 790 // Find the symbols in the module by name. 791 const __tgt_offload_entry *HostBegin = Image->EntriesBegin; 792 const __tgt_offload_entry *HostEnd = Image->EntriesEnd; 793 794 std::list<KernelTy> &KernelsList = DeviceData[DeviceId].KernelsList; 795 for (const __tgt_offload_entry *E = HostBegin; E != HostEnd; ++E) { 796 if (!E->addr) { 797 // We return nullptr when something like this happens, the host should 798 // have always something in the address to uniquely identify the target 799 // region. 800 DP("Invalid binary: host entry '<null>' (size = %zd)...\n", E->size); 801 return nullptr; 802 } 803 804 if (E->size) { 805 __tgt_offload_entry Entry = *E; 806 CUdeviceptr CUPtr; 807 size_t CUSize; 808 Err = cuModuleGetGlobal(&CUPtr, &CUSize, Module, E->name); 809 // We keep this style here because we need the name 810 if (Err != CUDA_SUCCESS) { 811 REPORT("Loading global '%s' Failed\n", E->name); 812 CUDA_ERR_STRING(Err); 813 return nullptr; 814 } 815 816 if (CUSize != E->size) { 817 DP("Loading global '%s' - size mismatch (%zd != %zd)\n", E->name, 818 CUSize, E->size); 819 return nullptr; 820 } 821 822 DP("Entry point " DPxMOD " maps to global %s (" DPxMOD ")\n", 823 DPxPTR(E - HostBegin), E->name, DPxPTR(CUPtr)); 824 825 Entry.addr = (void *)(CUPtr); 826 827 // Note: In the current implementation declare target variables 828 // can either be link or to. This means that once unified 829 // memory is activated via the requires directive, the variable 830 // can be used directly from the host in both cases. 831 // TODO: when variables types other than to or link are added, 832 // the below condition should be changed to explicitly 833 // check for to and link variables types: 834 // (RequiresFlags & OMP_REQ_UNIFIED_SHARED_MEMORY && (e->flags & 835 // OMP_DECLARE_TARGET_LINK || e->flags == OMP_DECLARE_TARGET_TO)) 836 if (RequiresFlags & OMP_REQ_UNIFIED_SHARED_MEMORY) { 837 // If unified memory is present any target link or to variables 838 // can access host addresses directly. There is no longer a 839 // need for device copies. 840 cuMemcpyHtoD(CUPtr, E->addr, sizeof(void *)); 841 DP("Copy linked variable host address (" DPxMOD 842 ") to device address (" DPxMOD ")\n", 843 DPxPTR(*((void **)E->addr)), DPxPTR(CUPtr)); 844 } 845 846 addOffloadEntry(DeviceId, Entry); 847 848 continue; 849 } 850 851 CUfunction Func; 852 Err = cuModuleGetFunction(&Func, Module, E->name); 853 // We keep this style here because we need the name 854 if (Err != CUDA_SUCCESS) { 855 REPORT("Loading '%s' Failed\n", E->name); 856 CUDA_ERR_STRING(Err); 857 return nullptr; 858 } 859 860 DP("Entry point " DPxMOD " maps to %s (" DPxMOD ")\n", 861 DPxPTR(E - HostBegin), E->name, DPxPTR(Func)); 862 863 // default value GENERIC (in case symbol is missing from cubin file) 864 llvm::omp::OMPTgtExecModeFlags ExecModeVal; 865 std::string ExecModeNameStr(E->name); 866 ExecModeNameStr += "_exec_mode"; 867 const char *ExecModeName = ExecModeNameStr.c_str(); 868 869 CUdeviceptr ExecModePtr; 870 size_t CUSize; 871 Err = cuModuleGetGlobal(&ExecModePtr, &CUSize, Module, ExecModeName); 872 if (Err == CUDA_SUCCESS) { 873 if (CUSize != sizeof(llvm::omp::OMPTgtExecModeFlags)) { 874 DP("Loading global exec_mode '%s' - size mismatch (%zd != %zd)\n", 875 ExecModeName, CUSize, sizeof(llvm::omp::OMPTgtExecModeFlags)); 876 return nullptr; 877 } 878 879 Err = cuMemcpyDtoH(&ExecModeVal, ExecModePtr, CUSize); 880 if (Err != CUDA_SUCCESS) { 881 REPORT("Error when copying data from device to host. Pointers: " 882 "host = " DPxMOD ", device = " DPxMOD ", size = %zd\n", 883 DPxPTR(&ExecModeVal), DPxPTR(ExecModePtr), CUSize); 884 CUDA_ERR_STRING(Err); 885 return nullptr; 886 } 887 } else { 888 DP("Loading global exec_mode '%s' - symbol missing, using default " 889 "value GENERIC (1)\n", 890 ExecModeName); 891 } 892 893 KernelsList.emplace_back(Func, ExecModeVal); 894 895 __tgt_offload_entry Entry = *E; 896 Entry.addr = &KernelsList.back(); 897 addOffloadEntry(DeviceId, Entry); 898 } 899 900 // send device environment data to the device 901 { 902 // TODO: The device ID used here is not the real device ID used by OpenMP. 903 DeviceEnvironmentTy DeviceEnv{0, static_cast<uint32_t>(NumberOfDevices), 904 static_cast<uint32_t>(DeviceId), 905 static_cast<uint32_t>(DynamicMemorySize)}; 906 907 if (const char *EnvStr = getenv("LIBOMPTARGET_DEVICE_RTL_DEBUG")) 908 DeviceEnv.DebugKind = std::stoi(EnvStr); 909 910 const char *DeviceEnvName = "omptarget_device_environment"; 911 CUdeviceptr DeviceEnvPtr; 912 size_t CUSize; 913 914 Err = cuModuleGetGlobal(&DeviceEnvPtr, &CUSize, Module, DeviceEnvName); 915 if (Err == CUDA_SUCCESS) { 916 if (CUSize != sizeof(DeviceEnv)) { 917 REPORT( 918 "Global device_environment '%s' - size mismatch (%zu != %zu)\n", 919 DeviceEnvName, CUSize, sizeof(int32_t)); 920 CUDA_ERR_STRING(Err); 921 return nullptr; 922 } 923 924 Err = cuMemcpyHtoD(DeviceEnvPtr, &DeviceEnv, CUSize); 925 if (Err != CUDA_SUCCESS) { 926 REPORT("Error when copying data from host to device. Pointers: " 927 "host = " DPxMOD ", device = " DPxMOD ", size = %zu\n", 928 DPxPTR(&DeviceEnv), DPxPTR(DeviceEnvPtr), CUSize); 929 CUDA_ERR_STRING(Err); 930 return nullptr; 931 } 932 933 DP("Sending global device environment data %zu bytes\n", CUSize); 934 } else { 935 DP("Finding global device environment '%s' - symbol missing.\n", 936 DeviceEnvName); 937 DP("Continue, considering this is a device RTL which does not accept " 938 "environment setting.\n"); 939 } 940 } 941 942 return getOffloadEntriesTable(DeviceId); 943 } 944 945 void *dataAlloc(const int DeviceId, const int64_t Size, 946 const TargetAllocTy Kind) { 947 switch (Kind) { 948 case TARGET_ALLOC_DEFAULT: 949 case TARGET_ALLOC_DEVICE: 950 if (UseMemoryManager) 951 return MemoryManagers[DeviceId]->allocate(Size, nullptr); 952 else 953 return DeviceAllocators[DeviceId].allocate(Size, nullptr, Kind); 954 case TARGET_ALLOC_HOST: 955 case TARGET_ALLOC_SHARED: 956 return DeviceAllocators[DeviceId].allocate(Size, nullptr, Kind); 957 } 958 959 REPORT("Invalid target data allocation kind or requested allocator not " 960 "implemented yet\n"); 961 962 return nullptr; 963 } 964 965 int dataSubmit(const int DeviceId, const void *TgtPtr, const void *HstPtr, 966 const int64_t Size, __tgt_async_info *AsyncInfo) const { 967 assert(AsyncInfo && "AsyncInfo is nullptr"); 968 969 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 970 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 971 return OFFLOAD_FAIL; 972 973 CUstream Stream = getStream(DeviceId, AsyncInfo); 974 975 Err = cuMemcpyHtoDAsync((CUdeviceptr)TgtPtr, HstPtr, Size, Stream); 976 if (Err != CUDA_SUCCESS) { 977 DP("Error when copying data from host to device. Pointers: host " 978 "= " DPxMOD ", device = " DPxMOD ", size = %" PRId64 "\n", 979 DPxPTR(HstPtr), DPxPTR(TgtPtr), Size); 980 CUDA_ERR_STRING(Err); 981 return OFFLOAD_FAIL; 982 } 983 984 return OFFLOAD_SUCCESS; 985 } 986 987 int dataRetrieve(const int DeviceId, void *HstPtr, const void *TgtPtr, 988 const int64_t Size, __tgt_async_info *AsyncInfo) const { 989 assert(AsyncInfo && "AsyncInfo is nullptr"); 990 991 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 992 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 993 return OFFLOAD_FAIL; 994 995 CUstream Stream = getStream(DeviceId, AsyncInfo); 996 997 Err = cuMemcpyDtoHAsync(HstPtr, (CUdeviceptr)TgtPtr, Size, Stream); 998 if (Err != CUDA_SUCCESS) { 999 DP("Error when copying data from device to host. Pointers: host " 1000 "= " DPxMOD ", device = " DPxMOD ", size = %" PRId64 "\n", 1001 DPxPTR(HstPtr), DPxPTR(TgtPtr), Size); 1002 CUDA_ERR_STRING(Err); 1003 return OFFLOAD_FAIL; 1004 } 1005 1006 return OFFLOAD_SUCCESS; 1007 } 1008 1009 int dataExchange(int SrcDevId, const void *SrcPtr, int DstDevId, void *DstPtr, 1010 int64_t Size, __tgt_async_info *AsyncInfo) const { 1011 assert(AsyncInfo && "AsyncInfo is nullptr"); 1012 1013 CUresult Err = cuCtxSetCurrent(DeviceData[SrcDevId].Context); 1014 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 1015 return OFFLOAD_FAIL; 1016 1017 CUstream Stream = getStream(SrcDevId, AsyncInfo); 1018 1019 // If they are two devices, we try peer to peer copy first 1020 if (SrcDevId != DstDevId) { 1021 int CanAccessPeer = 0; 1022 Err = cuDeviceCanAccessPeer(&CanAccessPeer, SrcDevId, DstDevId); 1023 if (Err != CUDA_SUCCESS) { 1024 REPORT("Error returned from cuDeviceCanAccessPeer. src = %" PRId32 1025 ", dst = %" PRId32 "\n", 1026 SrcDevId, DstDevId); 1027 CUDA_ERR_STRING(Err); 1028 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1029 } 1030 1031 if (!CanAccessPeer) { 1032 DP("P2P memcpy not supported so fall back to D2D memcpy"); 1033 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1034 } 1035 1036 Err = cuCtxEnablePeerAccess(DeviceData[DstDevId].Context, 0); 1037 if (Err != CUDA_SUCCESS) { 1038 REPORT("Error returned from cuCtxEnablePeerAccess. src = %" PRId32 1039 ", dst = %" PRId32 "\n", 1040 SrcDevId, DstDevId); 1041 CUDA_ERR_STRING(Err); 1042 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1043 } 1044 1045 Err = cuMemcpyPeerAsync((CUdeviceptr)DstPtr, DeviceData[DstDevId].Context, 1046 (CUdeviceptr)SrcPtr, DeviceData[SrcDevId].Context, 1047 Size, Stream); 1048 if (Err == CUDA_SUCCESS) 1049 return OFFLOAD_SUCCESS; 1050 1051 DP("Error returned from cuMemcpyPeerAsync. src_ptr = " DPxMOD 1052 ", src_id =%" PRId32 ", dst_ptr = " DPxMOD ", dst_id =%" PRId32 "\n", 1053 DPxPTR(SrcPtr), SrcDevId, DPxPTR(DstPtr), DstDevId); 1054 CUDA_ERR_STRING(Err); 1055 } 1056 1057 return memcpyDtoD(SrcPtr, DstPtr, Size, Stream); 1058 } 1059 1060 int dataDelete(const int DeviceId, void *TgtPtr) { 1061 if (UseMemoryManager) 1062 return MemoryManagers[DeviceId]->free(TgtPtr); 1063 1064 return DeviceAllocators[DeviceId].free(TgtPtr); 1065 } 1066 1067 int runTargetTeamRegion(const int DeviceId, void *TgtEntryPtr, void **TgtArgs, 1068 ptrdiff_t *TgtOffsets, const int ArgNum, 1069 const int TeamNum, const int ThreadLimit, 1070 const unsigned int LoopTripCount, 1071 __tgt_async_info *AsyncInfo) const { 1072 CUresult Err = cuCtxSetCurrent(DeviceData[DeviceId].Context); 1073 if (!checkResult(Err, "Error returned from cuCtxSetCurrent\n")) 1074 return OFFLOAD_FAIL; 1075 1076 // All args are references. 1077 std::vector<void *> Args(ArgNum); 1078 std::vector<void *> Ptrs(ArgNum); 1079 1080 for (int I = 0; I < ArgNum; ++I) { 1081 Ptrs[I] = (void *)((intptr_t)TgtArgs[I] + TgtOffsets[I]); 1082 Args[I] = &Ptrs[I]; 1083 } 1084 1085 KernelTy *KernelInfo = reinterpret_cast<KernelTy *>(TgtEntryPtr); 1086 1087 const bool IsSPMDGenericMode = 1088 KernelInfo->ExecutionMode == llvm::omp::OMP_TGT_EXEC_MODE_GENERIC_SPMD; 1089 const bool IsSPMDMode = 1090 KernelInfo->ExecutionMode == llvm::omp::OMP_TGT_EXEC_MODE_SPMD; 1091 const bool IsGenericMode = 1092 KernelInfo->ExecutionMode == llvm::omp::OMP_TGT_EXEC_MODE_GENERIC; 1093 1094 int CudaThreadsPerBlock; 1095 if (ThreadLimit > 0) { 1096 DP("Setting CUDA threads per block to requested %d\n", ThreadLimit); 1097 CudaThreadsPerBlock = ThreadLimit; 1098 // Add master warp if necessary 1099 if (IsGenericMode) { 1100 DP("Adding master warp: +%d threads\n", DeviceData[DeviceId].WarpSize); 1101 CudaThreadsPerBlock += DeviceData[DeviceId].WarpSize; 1102 } 1103 } else { 1104 DP("Setting CUDA threads per block to default %d\n", 1105 DeviceData[DeviceId].NumThreads); 1106 CudaThreadsPerBlock = DeviceData[DeviceId].NumThreads; 1107 } 1108 1109 if (CudaThreadsPerBlock > DeviceData[DeviceId].ThreadsPerBlock) { 1110 DP("Threads per block capped at device limit %d\n", 1111 DeviceData[DeviceId].ThreadsPerBlock); 1112 CudaThreadsPerBlock = DeviceData[DeviceId].ThreadsPerBlock; 1113 } 1114 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 if (TeamNum > DeviceData[DeviceId].BlocksPerGrid) { 1173 DP("Capping number of teams to team limit %d\n", 1174 DeviceData[DeviceId].BlocksPerGrid); 1175 CudaBlocksPerGrid = DeviceData[DeviceId].BlocksPerGrid; 1176 } else { 1177 DP("Using requested number of teams %d\n", TeamNum); 1178 CudaBlocksPerGrid = TeamNum; 1179 } 1180 1181 INFO(OMP_INFOTYPE_PLUGIN_KERNEL, DeviceId, 1182 "Launching kernel %s with %d blocks and %d threads in %s mode\n", 1183 (getOffloadEntry(DeviceId, TgtEntryPtr)) 1184 ? getOffloadEntry(DeviceId, TgtEntryPtr)->name 1185 : "(null)", 1186 CudaBlocksPerGrid, CudaThreadsPerBlock, 1187 (!IsSPMDMode ? (IsGenericMode ? "Generic" : "SPMD-Generic") : "SPMD")); 1188 1189 CUstream Stream = getStream(DeviceId, AsyncInfo); 1190 Err = cuLaunchKernel(KernelInfo->Func, CudaBlocksPerGrid, /* gridDimY */ 1, 1191 /* gridDimZ */ 1, CudaThreadsPerBlock, 1192 /* blockDimY */ 1, /* blockDimZ */ 1, 1193 DynamicMemorySize, Stream, &Args[0], nullptr); 1194 if (!checkResult(Err, "Error returned from cuLaunchKernel\n")) 1195 return OFFLOAD_FAIL; 1196 1197 DP("Launch of entry point at " DPxMOD " successful!\n", 1198 DPxPTR(TgtEntryPtr)); 1199 1200 return OFFLOAD_SUCCESS; 1201 } 1202 1203 int synchronize(const int DeviceId, __tgt_async_info *AsyncInfo) const { 1204 CUstream Stream = reinterpret_cast<CUstream>(AsyncInfo->Queue); 1205 CUresult Err = cuStreamSynchronize(Stream); 1206 1207 // Once the stream is synchronized, return it to stream pool and reset 1208 // AsyncInfo. This is to make sure the synchronization only works for its 1209 // own tasks. 1210 StreamPool[DeviceId]->release(reinterpret_cast<CUstream>(AsyncInfo->Queue)); 1211 AsyncInfo->Queue = nullptr; 1212 1213 if (Err != CUDA_SUCCESS) { 1214 DP("Error when synchronizing stream. stream = " DPxMOD 1215 ", async info ptr = " DPxMOD "\n", 1216 DPxPTR(Stream), DPxPTR(AsyncInfo)); 1217 CUDA_ERR_STRING(Err); 1218 } 1219 return (Err == CUDA_SUCCESS) ? OFFLOAD_SUCCESS : OFFLOAD_FAIL; 1220 } 1221 1222 void printDeviceInfo(int32_t device_id) { 1223 char TmpChar[1000]; 1224 std::string TmpStr; 1225 size_t TmpSt; 1226 int TmpInt, TmpInt2, TmpInt3; 1227 1228 CUdevice Device; 1229 checkResult(cuDeviceGet(&Device, device_id), 1230 "Error returned from cuCtxGetDevice\n"); 1231 1232 cuDriverGetVersion(&TmpInt); 1233 printf(" CUDA Driver Version: \t\t%d \n", TmpInt); 1234 printf(" CUDA Device Number: \t\t%d \n", device_id); 1235 checkResult(cuDeviceGetName(TmpChar, 1000, Device), 1236 "Error returned from cuDeviceGetName\n"); 1237 printf(" Device Name: \t\t\t%s \n", TmpChar); 1238 checkResult(cuDeviceTotalMem(&TmpSt, Device), 1239 "Error returned from cuDeviceTotalMem\n"); 1240 printf(" Global Memory Size: \t\t%zu bytes \n", TmpSt); 1241 checkResult(cuDeviceGetAttribute( 1242 &TmpInt, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, Device), 1243 "Error returned from cuDeviceGetAttribute\n"); 1244 printf(" Number of Multiprocessors: \t\t%d \n", TmpInt); 1245 checkResult( 1246 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_GPU_OVERLAP, Device), 1247 "Error returned from cuDeviceGetAttribute\n"); 1248 printf(" Concurrent Copy and Execution: \t%s \n", BOOL2TEXT(TmpInt)); 1249 checkResult(cuDeviceGetAttribute( 1250 &TmpInt, CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY, Device), 1251 "Error returned from cuDeviceGetAttribute\n"); 1252 printf(" Total Constant Memory: \t\t%d bytes\n", TmpInt); 1253 checkResult( 1254 cuDeviceGetAttribute( 1255 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK, Device), 1256 "Error returned from cuDeviceGetAttribute\n"); 1257 printf(" Max Shared Memory per Block: \t%d bytes \n", TmpInt); 1258 checkResult( 1259 cuDeviceGetAttribute( 1260 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK, Device), 1261 "Error returned from cuDeviceGetAttribute\n"); 1262 printf(" Registers per Block: \t\t%d \n", TmpInt); 1263 checkResult( 1264 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_WARP_SIZE, Device), 1265 "Error returned from cuDeviceGetAttribute\n"); 1266 printf(" Warp Size: \t\t\t\t%d Threads \n", TmpInt); 1267 checkResult(cuDeviceGetAttribute( 1268 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK, Device), 1269 "Error returned from cuDeviceGetAttribute\n"); 1270 printf(" Maximum Threads per Block: \t\t%d \n", TmpInt); 1271 checkResult(cuDeviceGetAttribute( 1272 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X, Device), 1273 "Error returned from cuDeviceGetAttribute\n"); 1274 checkResult(cuDeviceGetAttribute( 1275 &TmpInt2, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y, Device), 1276 "Error returned from cuDeviceGetAttribute\n"); 1277 checkResult(cuDeviceGetAttribute( 1278 &TmpInt3, CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z, Device), 1279 "Error returned from cuDeviceGetAttribute\n"); 1280 printf(" Maximum Block Dimensions: \t\t%d, %d, %d \n", TmpInt, TmpInt2, 1281 TmpInt3); 1282 checkResult(cuDeviceGetAttribute( 1283 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X, Device), 1284 "Error returned from cuDeviceGetAttribute\n"); 1285 checkResult(cuDeviceGetAttribute( 1286 &TmpInt2, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y, Device), 1287 "Error returned from cuDeviceGetAttribute\n"); 1288 checkResult(cuDeviceGetAttribute( 1289 &TmpInt3, CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z, Device), 1290 "Error returned from cuDeviceGetAttribute\n"); 1291 printf(" Maximum Grid Dimensions: \t\t%d x %d x %d \n", TmpInt, TmpInt2, 1292 TmpInt3); 1293 checkResult( 1294 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_MAX_PITCH, Device), 1295 "Error returned from cuDeviceGetAttribute\n"); 1296 printf(" Maximum Memory Pitch: \t\t%d bytes \n", TmpInt); 1297 checkResult(cuDeviceGetAttribute( 1298 &TmpInt, CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT, Device), 1299 "Error returned from cuDeviceGetAttribute\n"); 1300 printf(" Texture Alignment: \t\t\t%d bytes \n", TmpInt); 1301 checkResult( 1302 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, Device), 1303 "Error returned from cuDeviceGetAttribute\n"); 1304 printf(" Clock Rate: \t\t\t%d kHz\n", TmpInt); 1305 checkResult(cuDeviceGetAttribute( 1306 &TmpInt, CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT, Device), 1307 "Error returned from cuDeviceGetAttribute\n"); 1308 printf(" Execution Timeout: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1309 checkResult( 1310 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_INTEGRATED, Device), 1311 "Error returned from cuDeviceGetAttribute\n"); 1312 printf(" Integrated Device: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1313 checkResult(cuDeviceGetAttribute( 1314 &TmpInt, CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY, Device), 1315 "Error returned from cuDeviceGetAttribute\n"); 1316 printf(" Can Map Host Memory: \t\t%s \n", BOOL2TEXT(TmpInt)); 1317 checkResult( 1318 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_COMPUTE_MODE, Device), 1319 "Error returned from cuDeviceGetAttribute\n"); 1320 if (TmpInt == CU_COMPUTEMODE_DEFAULT) 1321 TmpStr = "DEFAULT"; 1322 else if (TmpInt == CU_COMPUTEMODE_PROHIBITED) 1323 TmpStr = "PROHIBITED"; 1324 else if (TmpInt == CU_COMPUTEMODE_EXCLUSIVE_PROCESS) 1325 TmpStr = "EXCLUSIVE PROCESS"; 1326 else 1327 TmpStr = "unknown"; 1328 printf(" Compute Mode: \t\t\t%s \n", TmpStr.c_str()); 1329 checkResult(cuDeviceGetAttribute( 1330 &TmpInt, CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS, Device), 1331 "Error returned from cuDeviceGetAttribute\n"); 1332 printf(" Concurrent Kernels: \t\t%s \n", BOOL2TEXT(TmpInt)); 1333 checkResult( 1334 cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_ECC_ENABLED, Device), 1335 "Error returned from cuDeviceGetAttribute\n"); 1336 printf(" ECC Enabled: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1337 checkResult(cuDeviceGetAttribute( 1338 &TmpInt, CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE, Device), 1339 "Error returned from cuDeviceGetAttribute\n"); 1340 printf(" Memory Clock Rate: \t\t\t%d kHz\n", TmpInt); 1341 checkResult( 1342 cuDeviceGetAttribute( 1343 &TmpInt, CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH, Device), 1344 "Error returned from cuDeviceGetAttribute\n"); 1345 printf(" Memory Bus Width: \t\t\t%d bits\n", TmpInt); 1346 checkResult(cuDeviceGetAttribute(&TmpInt, CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE, 1347 Device), 1348 "Error returned from cuDeviceGetAttribute\n"); 1349 printf(" L2 Cache Size: \t\t\t%d bytes \n", TmpInt); 1350 checkResult(cuDeviceGetAttribute( 1351 &TmpInt, CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_MULTIPROCESSOR, 1352 Device), 1353 "Error returned from cuDeviceGetAttribute\n"); 1354 printf(" Max Threads Per SMP: \t\t%d \n", TmpInt); 1355 checkResult(cuDeviceGetAttribute( 1356 &TmpInt, CU_DEVICE_ATTRIBUTE_ASYNC_ENGINE_COUNT, Device), 1357 "Error returned from cuDeviceGetAttribute\n"); 1358 printf(" Async Engines: \t\t\t%s (%d) \n", BOOL2TEXT(TmpInt), TmpInt); 1359 checkResult(cuDeviceGetAttribute( 1360 &TmpInt, CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING, Device), 1361 "Error returned from cuDeviceGetAttribute\n"); 1362 printf(" Unified Addressing: \t\t%s \n", BOOL2TEXT(TmpInt)); 1363 checkResult(cuDeviceGetAttribute( 1364 &TmpInt, CU_DEVICE_ATTRIBUTE_MANAGED_MEMORY, Device), 1365 "Error returned from cuDeviceGetAttribute\n"); 1366 printf(" Managed Memory: \t\t\t%s \n", BOOL2TEXT(TmpInt)); 1367 checkResult( 1368 cuDeviceGetAttribute( 1369 &TmpInt, CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS, Device), 1370 "Error returned from cuDeviceGetAttribute\n"); 1371 printf(" Concurrent Managed Memory: \t\t%s \n", BOOL2TEXT(TmpInt)); 1372 checkResult( 1373 cuDeviceGetAttribute( 1374 &TmpInt, CU_DEVICE_ATTRIBUTE_COMPUTE_PREEMPTION_SUPPORTED, Device), 1375 "Error returned from cuDeviceGetAttribute\n"); 1376 printf(" Preemption Supported: \t\t%s \n", BOOL2TEXT(TmpInt)); 1377 checkResult(cuDeviceGetAttribute( 1378 &TmpInt, CU_DEVICE_ATTRIBUTE_COOPERATIVE_LAUNCH, Device), 1379 "Error returned from cuDeviceGetAttribute\n"); 1380 printf(" Cooperative Launch: \t\t%s \n", BOOL2TEXT(TmpInt)); 1381 checkResult(cuDeviceGetAttribute( 1382 &TmpInt, CU_DEVICE_ATTRIBUTE_MULTI_GPU_BOARD, Device), 1383 "Error returned from cuDeviceGetAttribute\n"); 1384 printf(" Multi-Device Boars: \t\t%s \n", BOOL2TEXT(TmpInt)); 1385 checkResult( 1386 cuDeviceGetAttribute( 1387 &TmpInt, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, Device), 1388 "Error returned from cuDeviceGetAttribute\n"); 1389 checkResult( 1390 cuDeviceGetAttribute( 1391 &TmpInt2, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, Device), 1392 "Error returned from cuDeviceGetAttribute\n"); 1393 printf(" Compute Capabilities: \t\t%d%d \n", TmpInt, TmpInt2); 1394 } 1395 1396 int createEvent(void **P) { 1397 CUevent Event = nullptr; 1398 if (EventPool.acquire(Event) != OFFLOAD_SUCCESS) 1399 return OFFLOAD_FAIL; 1400 *P = Event; 1401 return OFFLOAD_SUCCESS; 1402 } 1403 1404 int destroyEvent(void *EventPtr) { 1405 EventPool.release(reinterpret_cast<CUevent>(EventPtr)); 1406 return OFFLOAD_SUCCESS; 1407 } 1408 1409 int waitEvent(const int DeviceId, __tgt_async_info *AsyncInfo, 1410 void *EventPtr) const { 1411 CUstream Stream = getStream(DeviceId, AsyncInfo); 1412 CUevent Event = reinterpret_cast<CUevent>(EventPtr); 1413 1414 // We don't use CU_EVENT_WAIT_DEFAULT here as it is only available from 1415 // specific CUDA version, and defined as 0x0. In previous version, per CUDA 1416 // API document, that argument has to be 0x0. 1417 CUresult Err = cuStreamWaitEvent(Stream, Event, 0); 1418 if (Err != CUDA_SUCCESS) { 1419 DP("Error when waiting event. stream = " DPxMOD ", event = " DPxMOD "\n", 1420 DPxPTR(Stream), DPxPTR(Event)); 1421 CUDA_ERR_STRING(Err); 1422 return OFFLOAD_FAIL; 1423 } 1424 1425 return OFFLOAD_SUCCESS; 1426 } 1427 }; 1428 1429 DeviceRTLTy DeviceRTL; 1430 } // namespace 1431 1432 // Exposed library API function 1433 #ifdef __cplusplus 1434 extern "C" { 1435 #endif 1436 1437 int32_t __tgt_rtl_is_valid_binary(__tgt_device_image *image) { 1438 return elf_check_machine(image, /* EM_CUDA */ 190); 1439 } 1440 1441 int32_t __tgt_rtl_number_of_devices() { return DeviceRTL.getNumOfDevices(); } 1442 1443 int64_t __tgt_rtl_init_requires(int64_t RequiresFlags) { 1444 DP("Init requires flags to %" PRId64 "\n", RequiresFlags); 1445 DeviceRTL.setRequiresFlag(RequiresFlags); 1446 return RequiresFlags; 1447 } 1448 1449 int32_t __tgt_rtl_is_data_exchangable(int32_t src_dev_id, int dst_dev_id) { 1450 if (DeviceRTL.isValidDeviceId(src_dev_id) && 1451 DeviceRTL.isValidDeviceId(dst_dev_id)) 1452 return 1; 1453 1454 return 0; 1455 } 1456 1457 int32_t __tgt_rtl_init_device(int32_t device_id) { 1458 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1459 1460 return DeviceRTL.initDevice(device_id); 1461 } 1462 1463 __tgt_target_table *__tgt_rtl_load_binary(int32_t device_id, 1464 __tgt_device_image *image) { 1465 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1466 1467 return DeviceRTL.loadBinary(device_id, image); 1468 } 1469 1470 void *__tgt_rtl_data_alloc(int32_t device_id, int64_t size, void *, 1471 int32_t kind) { 1472 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1473 1474 return DeviceRTL.dataAlloc(device_id, size, (TargetAllocTy)kind); 1475 } 1476 1477 int32_t __tgt_rtl_data_submit(int32_t device_id, void *tgt_ptr, void *hst_ptr, 1478 int64_t size) { 1479 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1480 1481 __tgt_async_info AsyncInfo; 1482 const int32_t rc = __tgt_rtl_data_submit_async(device_id, tgt_ptr, hst_ptr, 1483 size, &AsyncInfo); 1484 if (rc != OFFLOAD_SUCCESS) 1485 return OFFLOAD_FAIL; 1486 1487 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1488 } 1489 1490 int32_t __tgt_rtl_data_submit_async(int32_t device_id, void *tgt_ptr, 1491 void *hst_ptr, int64_t size, 1492 __tgt_async_info *async_info_ptr) { 1493 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1494 assert(async_info_ptr && "async_info_ptr is nullptr"); 1495 1496 return DeviceRTL.dataSubmit(device_id, tgt_ptr, hst_ptr, size, 1497 async_info_ptr); 1498 } 1499 1500 int32_t __tgt_rtl_data_retrieve(int32_t device_id, void *hst_ptr, void *tgt_ptr, 1501 int64_t size) { 1502 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1503 1504 __tgt_async_info AsyncInfo; 1505 const int32_t rc = __tgt_rtl_data_retrieve_async(device_id, hst_ptr, tgt_ptr, 1506 size, &AsyncInfo); 1507 if (rc != OFFLOAD_SUCCESS) 1508 return OFFLOAD_FAIL; 1509 1510 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1511 } 1512 1513 int32_t __tgt_rtl_data_retrieve_async(int32_t device_id, void *hst_ptr, 1514 void *tgt_ptr, int64_t size, 1515 __tgt_async_info *async_info_ptr) { 1516 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1517 assert(async_info_ptr && "async_info_ptr is nullptr"); 1518 1519 return DeviceRTL.dataRetrieve(device_id, hst_ptr, tgt_ptr, size, 1520 async_info_ptr); 1521 } 1522 1523 int32_t __tgt_rtl_data_exchange_async(int32_t src_dev_id, void *src_ptr, 1524 int dst_dev_id, void *dst_ptr, 1525 int64_t size, 1526 __tgt_async_info *AsyncInfo) { 1527 assert(DeviceRTL.isValidDeviceId(src_dev_id) && "src_dev_id is invalid"); 1528 assert(DeviceRTL.isValidDeviceId(dst_dev_id) && "dst_dev_id is invalid"); 1529 assert(AsyncInfo && "AsyncInfo is nullptr"); 1530 1531 return DeviceRTL.dataExchange(src_dev_id, src_ptr, dst_dev_id, dst_ptr, size, 1532 AsyncInfo); 1533 } 1534 1535 int32_t __tgt_rtl_data_exchange(int32_t src_dev_id, void *src_ptr, 1536 int32_t dst_dev_id, void *dst_ptr, 1537 int64_t size) { 1538 assert(DeviceRTL.isValidDeviceId(src_dev_id) && "src_dev_id is invalid"); 1539 assert(DeviceRTL.isValidDeviceId(dst_dev_id) && "dst_dev_id is invalid"); 1540 1541 __tgt_async_info AsyncInfo; 1542 const int32_t rc = __tgt_rtl_data_exchange_async( 1543 src_dev_id, src_ptr, dst_dev_id, dst_ptr, size, &AsyncInfo); 1544 if (rc != OFFLOAD_SUCCESS) 1545 return OFFLOAD_FAIL; 1546 1547 return __tgt_rtl_synchronize(src_dev_id, &AsyncInfo); 1548 } 1549 1550 int32_t __tgt_rtl_data_delete(int32_t device_id, void *tgt_ptr) { 1551 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1552 1553 return DeviceRTL.dataDelete(device_id, tgt_ptr); 1554 } 1555 1556 int32_t __tgt_rtl_run_target_team_region(int32_t device_id, void *tgt_entry_ptr, 1557 void **tgt_args, 1558 ptrdiff_t *tgt_offsets, 1559 int32_t arg_num, int32_t team_num, 1560 int32_t thread_limit, 1561 uint64_t loop_tripcount) { 1562 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1563 1564 __tgt_async_info AsyncInfo; 1565 const int32_t rc = __tgt_rtl_run_target_team_region_async( 1566 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, team_num, 1567 thread_limit, loop_tripcount, &AsyncInfo); 1568 if (rc != OFFLOAD_SUCCESS) 1569 return OFFLOAD_FAIL; 1570 1571 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1572 } 1573 1574 int32_t __tgt_rtl_run_target_team_region_async( 1575 int32_t device_id, void *tgt_entry_ptr, void **tgt_args, 1576 ptrdiff_t *tgt_offsets, int32_t arg_num, int32_t team_num, 1577 int32_t thread_limit, uint64_t loop_tripcount, 1578 __tgt_async_info *async_info_ptr) { 1579 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1580 1581 return DeviceRTL.runTargetTeamRegion( 1582 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, team_num, 1583 thread_limit, loop_tripcount, async_info_ptr); 1584 } 1585 1586 int32_t __tgt_rtl_run_target_region(int32_t device_id, void *tgt_entry_ptr, 1587 void **tgt_args, ptrdiff_t *tgt_offsets, 1588 int32_t arg_num) { 1589 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1590 1591 __tgt_async_info AsyncInfo; 1592 const int32_t rc = __tgt_rtl_run_target_region_async( 1593 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, &AsyncInfo); 1594 if (rc != OFFLOAD_SUCCESS) 1595 return OFFLOAD_FAIL; 1596 1597 return __tgt_rtl_synchronize(device_id, &AsyncInfo); 1598 } 1599 1600 int32_t __tgt_rtl_run_target_region_async(int32_t device_id, 1601 void *tgt_entry_ptr, void **tgt_args, 1602 ptrdiff_t *tgt_offsets, 1603 int32_t arg_num, 1604 __tgt_async_info *async_info_ptr) { 1605 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1606 1607 return __tgt_rtl_run_target_team_region_async( 1608 device_id, tgt_entry_ptr, tgt_args, tgt_offsets, arg_num, 1609 /* team num*/ 1, /* thread_limit */ 1, /* loop_tripcount */ 0, 1610 async_info_ptr); 1611 } 1612 1613 int32_t __tgt_rtl_synchronize(int32_t device_id, 1614 __tgt_async_info *async_info_ptr) { 1615 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1616 assert(async_info_ptr && "async_info_ptr is nullptr"); 1617 assert(async_info_ptr->Queue && "async_info_ptr->Queue is nullptr"); 1618 1619 return DeviceRTL.synchronize(device_id, async_info_ptr); 1620 } 1621 1622 void __tgt_rtl_set_info_flag(uint32_t NewInfoLevel) { 1623 std::atomic<uint32_t> &InfoLevel = getInfoLevelInternal(); 1624 InfoLevel.store(NewInfoLevel); 1625 } 1626 1627 void __tgt_rtl_print_device_info(int32_t device_id) { 1628 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1629 DeviceRTL.printDeviceInfo(device_id); 1630 } 1631 1632 int32_t __tgt_rtl_create_event(int32_t device_id, void **event) { 1633 assert(event && "event is nullptr"); 1634 return DeviceRTL.createEvent(event); 1635 } 1636 1637 int32_t __tgt_rtl_record_event(int32_t device_id, void *event_ptr, 1638 __tgt_async_info *async_info_ptr) { 1639 assert(async_info_ptr && "async_info_ptr is nullptr"); 1640 assert(async_info_ptr->Queue && "async_info_ptr->Queue is nullptr"); 1641 assert(event_ptr && "event_ptr is nullptr"); 1642 1643 return recordEvent(event_ptr, async_info_ptr); 1644 } 1645 1646 int32_t __tgt_rtl_wait_event(int32_t device_id, void *event_ptr, 1647 __tgt_async_info *async_info_ptr) { 1648 assert(DeviceRTL.isValidDeviceId(device_id) && "device_id is invalid"); 1649 assert(async_info_ptr && "async_info_ptr is nullptr"); 1650 assert(event_ptr && "event is nullptr"); 1651 1652 return DeviceRTL.waitEvent(device_id, async_info_ptr, event_ptr); 1653 } 1654 1655 int32_t __tgt_rtl_sync_event(int32_t device_id, void *event_ptr) { 1656 assert(event_ptr && "event is nullptr"); 1657 1658 return syncEvent(event_ptr); 1659 } 1660 1661 int32_t __tgt_rtl_destroy_event(int32_t device_id, void *event_ptr) { 1662 assert(event_ptr && "event is nullptr"); 1663 1664 return DeviceRTL.destroyEvent(event_ptr); 1665 } 1666 1667 #ifdef __cplusplus 1668 } 1669 #endif 1670