1 //===--- Cuda.cpp - Cuda Tool and ToolChain Implementations -----*- 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 #include "Cuda.h" 10 #include "CommonArgs.h" 11 #include "InputInfo.h" 12 #include "clang/Basic/Cuda.h" 13 #include "clang/Config/config.h" 14 #include "clang/Driver/Compilation.h" 15 #include "clang/Driver/Distro.h" 16 #include "clang/Driver/Driver.h" 17 #include "clang/Driver/DriverDiagnostic.h" 18 #include "clang/Driver/Options.h" 19 #include "llvm/Option/ArgList.h" 20 #include "llvm/Support/FileSystem.h" 21 #include "llvm/Support/Path.h" 22 #include "llvm/Support/Process.h" 23 #include "llvm/Support/Program.h" 24 #include "llvm/Support/VirtualFileSystem.h" 25 #include <system_error> 26 27 using namespace clang::driver; 28 using namespace clang::driver::toolchains; 29 using namespace clang::driver::tools; 30 using namespace clang; 31 using namespace llvm::opt; 32 33 // Parses the contents of version.txt in an CUDA installation. It should 34 // contain one line of the from e.g. "CUDA Version 7.5.2". 35 void CudaInstallationDetector::ParseCudaVersionFile(llvm::StringRef V) { 36 Version = CudaVersion::UNKNOWN; 37 if (!V.startswith("CUDA Version ")) 38 return; 39 V = V.substr(strlen("CUDA Version ")); 40 SmallVector<StringRef,4> VersionParts; 41 V.split(VersionParts, '.'); 42 if (VersionParts.size() < 2) 43 return; 44 DetectedVersion = join_items(".", VersionParts[0], VersionParts[1]); 45 Version = CudaStringToVersion(DetectedVersion); 46 if (Version != CudaVersion::UNKNOWN) 47 return; 48 49 Version = CudaVersion::LATEST; 50 DetectedVersionIsNotSupported = true; 51 } 52 53 void CudaInstallationDetector::WarnIfUnsupportedVersion() { 54 if (DetectedVersionIsNotSupported) 55 D.Diag(diag::warn_drv_unknown_cuda_version) 56 << DetectedVersion << CudaVersionToString(Version); 57 } 58 59 CudaInstallationDetector::CudaInstallationDetector( 60 const Driver &D, const llvm::Triple &HostTriple, 61 const llvm::opt::ArgList &Args) 62 : D(D) { 63 struct Candidate { 64 std::string Path; 65 bool StrictChecking; 66 67 Candidate(std::string Path, bool StrictChecking = false) 68 : Path(Path), StrictChecking(StrictChecking) {} 69 }; 70 SmallVector<Candidate, 4> Candidates; 71 72 // In decreasing order so we prefer newer versions to older versions. 73 std::initializer_list<const char *> Versions = {"8.0", "7.5", "7.0"}; 74 75 if (Args.hasArg(clang::driver::options::OPT_cuda_path_EQ)) { 76 Candidates.emplace_back( 77 Args.getLastArgValue(clang::driver::options::OPT_cuda_path_EQ).str()); 78 } else if (HostTriple.isOSWindows()) { 79 for (const char *Ver : Versions) 80 Candidates.emplace_back( 81 D.SysRoot + "/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v" + 82 Ver); 83 } else { 84 if (!Args.hasArg(clang::driver::options::OPT_cuda_path_ignore_env)) { 85 // Try to find ptxas binary. If the executable is located in a directory 86 // called 'bin/', its parent directory might be a good guess for a valid 87 // CUDA installation. 88 // However, some distributions might installs 'ptxas' to /usr/bin. In that 89 // case the candidate would be '/usr' which passes the following checks 90 // because '/usr/include' exists as well. To avoid this case, we always 91 // check for the directory potentially containing files for libdevice, 92 // even if the user passes -nocudalib. 93 if (llvm::ErrorOr<std::string> ptxas = 94 llvm::sys::findProgramByName("ptxas")) { 95 SmallString<256> ptxasAbsolutePath; 96 llvm::sys::fs::real_path(*ptxas, ptxasAbsolutePath); 97 98 StringRef ptxasDir = llvm::sys::path::parent_path(ptxasAbsolutePath); 99 if (llvm::sys::path::filename(ptxasDir) == "bin") 100 Candidates.emplace_back(llvm::sys::path::parent_path(ptxasDir), 101 /*StrictChecking=*/true); 102 } 103 } 104 105 Candidates.emplace_back(D.SysRoot + "/usr/local/cuda"); 106 for (const char *Ver : Versions) 107 Candidates.emplace_back(D.SysRoot + "/usr/local/cuda-" + Ver); 108 109 Distro Dist(D.getVFS(), llvm::Triple(llvm::sys::getProcessTriple())); 110 if (Dist.IsDebian() || Dist.IsUbuntu()) 111 // Special case for Debian to have nvidia-cuda-toolkit work 112 // out of the box. More info on http://bugs.debian.org/882505 113 Candidates.emplace_back(D.SysRoot + "/usr/lib/cuda"); 114 } 115 116 bool NoCudaLib = Args.hasArg(options::OPT_nogpulib); 117 118 for (const auto &Candidate : Candidates) { 119 InstallPath = Candidate.Path; 120 if (InstallPath.empty() || !D.getVFS().exists(InstallPath)) 121 continue; 122 123 BinPath = InstallPath + "/bin"; 124 IncludePath = InstallPath + "/include"; 125 LibDevicePath = InstallPath + "/nvvm/libdevice"; 126 127 auto &FS = D.getVFS(); 128 if (!(FS.exists(IncludePath) && FS.exists(BinPath))) 129 continue; 130 bool CheckLibDevice = (!NoCudaLib || Candidate.StrictChecking); 131 if (CheckLibDevice && !FS.exists(LibDevicePath)) 132 continue; 133 134 // On Linux, we have both lib and lib64 directories, and we need to choose 135 // based on our triple. On MacOS, we have only a lib directory. 136 // 137 // It's sufficient for our purposes to be flexible: If both lib and lib64 138 // exist, we choose whichever one matches our triple. Otherwise, if only 139 // lib exists, we use it. 140 if (HostTriple.isArch64Bit() && FS.exists(InstallPath + "/lib64")) 141 LibPath = InstallPath + "/lib64"; 142 else if (FS.exists(InstallPath + "/lib")) 143 LibPath = InstallPath + "/lib"; 144 else 145 continue; 146 147 llvm::ErrorOr<std::unique_ptr<llvm::MemoryBuffer>> VersionFile = 148 FS.getBufferForFile(InstallPath + "/version.txt"); 149 if (!VersionFile) { 150 // CUDA 7.0 doesn't have a version.txt, so guess that's our version if 151 // version.txt isn't present. 152 Version = CudaVersion::CUDA_70; 153 } else { 154 ParseCudaVersionFile((*VersionFile)->getBuffer()); 155 } 156 157 if (Version >= CudaVersion::CUDA_90) { 158 // CUDA-9+ uses single libdevice file for all GPU variants. 159 std::string FilePath = LibDevicePath + "/libdevice.10.bc"; 160 if (FS.exists(FilePath)) { 161 for (const char *GpuArchName : 162 {"sm_30", "sm_32", "sm_35", "sm_37", "sm_50", "sm_52", "sm_53", 163 "sm_60", "sm_61", "sm_62", "sm_70", "sm_72", "sm_75"}) { 164 const CudaArch GpuArch = StringToCudaArch(GpuArchName); 165 if (Version >= MinVersionForCudaArch(GpuArch) && 166 Version <= MaxVersionForCudaArch(GpuArch)) 167 LibDeviceMap[GpuArchName] = FilePath; 168 } 169 } 170 } else { 171 std::error_code EC; 172 for (llvm::sys::fs::directory_iterator LI(LibDevicePath, EC), LE; 173 !EC && LI != LE; LI = LI.increment(EC)) { 174 StringRef FilePath = LI->path(); 175 StringRef FileName = llvm::sys::path::filename(FilePath); 176 // Process all bitcode filenames that look like 177 // libdevice.compute_XX.YY.bc 178 const StringRef LibDeviceName = "libdevice."; 179 if (!(FileName.startswith(LibDeviceName) && FileName.endswith(".bc"))) 180 continue; 181 StringRef GpuArch = FileName.slice( 182 LibDeviceName.size(), FileName.find('.', LibDeviceName.size())); 183 LibDeviceMap[GpuArch] = FilePath.str(); 184 // Insert map entries for specific devices with this compute 185 // capability. NVCC's choice of the libdevice library version is 186 // rather peculiar and depends on the CUDA version. 187 if (GpuArch == "compute_20") { 188 LibDeviceMap["sm_20"] = FilePath; 189 LibDeviceMap["sm_21"] = FilePath; 190 LibDeviceMap["sm_32"] = FilePath; 191 } else if (GpuArch == "compute_30") { 192 LibDeviceMap["sm_30"] = FilePath; 193 if (Version < CudaVersion::CUDA_80) { 194 LibDeviceMap["sm_50"] = FilePath; 195 LibDeviceMap["sm_52"] = FilePath; 196 LibDeviceMap["sm_53"] = FilePath; 197 } 198 LibDeviceMap["sm_60"] = FilePath; 199 LibDeviceMap["sm_61"] = FilePath; 200 LibDeviceMap["sm_62"] = FilePath; 201 } else if (GpuArch == "compute_35") { 202 LibDeviceMap["sm_35"] = FilePath; 203 LibDeviceMap["sm_37"] = FilePath; 204 } else if (GpuArch == "compute_50") { 205 if (Version >= CudaVersion::CUDA_80) { 206 LibDeviceMap["sm_50"] = FilePath; 207 LibDeviceMap["sm_52"] = FilePath; 208 LibDeviceMap["sm_53"] = FilePath; 209 } 210 } 211 } 212 } 213 214 // Check that we have found at least one libdevice that we can link in if 215 // -nocudalib hasn't been specified. 216 if (LibDeviceMap.empty() && !NoCudaLib) 217 continue; 218 219 IsValid = true; 220 break; 221 } 222 } 223 224 void CudaInstallationDetector::AddCudaIncludeArgs( 225 const ArgList &DriverArgs, ArgStringList &CC1Args) const { 226 if (!DriverArgs.hasArg(options::OPT_nobuiltininc)) { 227 // Add cuda_wrappers/* to our system include path. This lets us wrap 228 // standard library headers. 229 SmallString<128> P(D.ResourceDir); 230 llvm::sys::path::append(P, "include"); 231 llvm::sys::path::append(P, "cuda_wrappers"); 232 CC1Args.push_back("-internal-isystem"); 233 CC1Args.push_back(DriverArgs.MakeArgString(P)); 234 } 235 236 if (DriverArgs.hasArg(options::OPT_nocudainc)) 237 return; 238 239 if (!isValid()) { 240 D.Diag(diag::err_drv_no_cuda_installation); 241 return; 242 } 243 244 CC1Args.push_back("-internal-isystem"); 245 CC1Args.push_back(DriverArgs.MakeArgString(getIncludePath())); 246 CC1Args.push_back("-include"); 247 CC1Args.push_back("__clang_cuda_runtime_wrapper.h"); 248 } 249 250 void CudaInstallationDetector::CheckCudaVersionSupportsArch( 251 CudaArch Arch) const { 252 if (Arch == CudaArch::UNKNOWN || Version == CudaVersion::UNKNOWN || 253 ArchsWithBadVersion.count(Arch) > 0) 254 return; 255 256 auto MinVersion = MinVersionForCudaArch(Arch); 257 auto MaxVersion = MaxVersionForCudaArch(Arch); 258 if (Version < MinVersion || Version > MaxVersion) { 259 ArchsWithBadVersion.insert(Arch); 260 D.Diag(diag::err_drv_cuda_version_unsupported) 261 << CudaArchToString(Arch) << CudaVersionToString(MinVersion) 262 << CudaVersionToString(MaxVersion) << InstallPath 263 << CudaVersionToString(Version); 264 } 265 } 266 267 void CudaInstallationDetector::print(raw_ostream &OS) const { 268 if (isValid()) 269 OS << "Found CUDA installation: " << InstallPath << ", version " 270 << CudaVersionToString(Version) << "\n"; 271 } 272 273 namespace { 274 /// Debug info level for the NVPTX devices. We may need to emit different debug 275 /// info level for the host and for the device itselfi. This type controls 276 /// emission of the debug info for the devices. It either prohibits disable info 277 /// emission completely, or emits debug directives only, or emits same debug 278 /// info as for the host. 279 enum DeviceDebugInfoLevel { 280 DisableDebugInfo, /// Do not emit debug info for the devices. 281 DebugDirectivesOnly, /// Emit only debug directives. 282 EmitSameDebugInfoAsHost, /// Use the same debug info level just like for the 283 /// host. 284 }; 285 } // anonymous namespace 286 287 /// Define debug info level for the NVPTX devices. If the debug info for both 288 /// the host and device are disabled (-g0/-ggdb0 or no debug options at all). If 289 /// only debug directives are requested for the both host and device 290 /// (-gline-directvies-only), or the debug info only for the device is disabled 291 /// (optimization is on and --cuda-noopt-device-debug was not specified), the 292 /// debug directves only must be emitted for the device. Otherwise, use the same 293 /// debug info level just like for the host (with the limitations of only 294 /// supported DWARF2 standard). 295 static DeviceDebugInfoLevel mustEmitDebugInfo(const ArgList &Args) { 296 const Arg *A = Args.getLastArg(options::OPT_O_Group); 297 bool IsDebugEnabled = !A || A->getOption().matches(options::OPT_O0) || 298 Args.hasFlag(options::OPT_cuda_noopt_device_debug, 299 options::OPT_no_cuda_noopt_device_debug, 300 /*Default=*/false); 301 if (const Arg *A = Args.getLastArg(options::OPT_g_Group)) { 302 const Option &Opt = A->getOption(); 303 if (Opt.matches(options::OPT_gN_Group)) { 304 if (Opt.matches(options::OPT_g0) || Opt.matches(options::OPT_ggdb0)) 305 return DisableDebugInfo; 306 if (Opt.matches(options::OPT_gline_directives_only)) 307 return DebugDirectivesOnly; 308 } 309 return IsDebugEnabled ? EmitSameDebugInfoAsHost : DebugDirectivesOnly; 310 } 311 return DisableDebugInfo; 312 } 313 314 void NVPTX::Assembler::ConstructJob(Compilation &C, const JobAction &JA, 315 const InputInfo &Output, 316 const InputInfoList &Inputs, 317 const ArgList &Args, 318 const char *LinkingOutput) const { 319 const auto &TC = 320 static_cast<const toolchains::CudaToolChain &>(getToolChain()); 321 assert(TC.getTriple().isNVPTX() && "Wrong platform"); 322 323 StringRef GPUArchName; 324 // If this is an OpenMP action we need to extract the device architecture 325 // from the -march=arch option. This option may come from -Xopenmp-target 326 // flag or the default value. 327 if (JA.isDeviceOffloading(Action::OFK_OpenMP)) { 328 GPUArchName = Args.getLastArgValue(options::OPT_march_EQ); 329 assert(!GPUArchName.empty() && "Must have an architecture passed in."); 330 } else 331 GPUArchName = JA.getOffloadingArch(); 332 333 // Obtain architecture from the action. 334 CudaArch gpu_arch = StringToCudaArch(GPUArchName); 335 assert(gpu_arch != CudaArch::UNKNOWN && 336 "Device action expected to have an architecture."); 337 338 // Check that our installation's ptxas supports gpu_arch. 339 if (!Args.hasArg(options::OPT_no_cuda_version_check)) { 340 TC.CudaInstallation.CheckCudaVersionSupportsArch(gpu_arch); 341 } 342 343 ArgStringList CmdArgs; 344 CmdArgs.push_back(TC.getTriple().isArch64Bit() ? "-m64" : "-m32"); 345 DeviceDebugInfoLevel DIKind = mustEmitDebugInfo(Args); 346 if (DIKind == EmitSameDebugInfoAsHost) { 347 // ptxas does not accept -g option if optimization is enabled, so 348 // we ignore the compiler's -O* options if we want debug info. 349 CmdArgs.push_back("-g"); 350 CmdArgs.push_back("--dont-merge-basicblocks"); 351 CmdArgs.push_back("--return-at-end"); 352 } else if (Arg *A = Args.getLastArg(options::OPT_O_Group)) { 353 // Map the -O we received to -O{0,1,2,3}. 354 // 355 // TODO: Perhaps we should map host -O2 to ptxas -O3. -O3 is ptxas's 356 // default, so it may correspond more closely to the spirit of clang -O2. 357 358 // -O3 seems like the least-bad option when -Osomething is specified to 359 // clang but it isn't handled below. 360 StringRef OOpt = "3"; 361 if (A->getOption().matches(options::OPT_O4) || 362 A->getOption().matches(options::OPT_Ofast)) 363 OOpt = "3"; 364 else if (A->getOption().matches(options::OPT_O0)) 365 OOpt = "0"; 366 else if (A->getOption().matches(options::OPT_O)) { 367 // -Os, -Oz, and -O(anything else) map to -O2, for lack of better options. 368 OOpt = llvm::StringSwitch<const char *>(A->getValue()) 369 .Case("1", "1") 370 .Case("2", "2") 371 .Case("3", "3") 372 .Case("s", "2") 373 .Case("z", "2") 374 .Default("2"); 375 } 376 CmdArgs.push_back(Args.MakeArgString(llvm::Twine("-O") + OOpt)); 377 } else { 378 // If no -O was passed, pass -O0 to ptxas -- no opt flag should correspond 379 // to no optimizations, but ptxas's default is -O3. 380 CmdArgs.push_back("-O0"); 381 } 382 if (DIKind == DebugDirectivesOnly) 383 CmdArgs.push_back("-lineinfo"); 384 385 // Pass -v to ptxas if it was passed to the driver. 386 if (Args.hasArg(options::OPT_v)) 387 CmdArgs.push_back("-v"); 388 389 CmdArgs.push_back("--gpu-name"); 390 CmdArgs.push_back(Args.MakeArgString(CudaArchToString(gpu_arch))); 391 CmdArgs.push_back("--output-file"); 392 CmdArgs.push_back(Args.MakeArgString(TC.getInputFilename(Output))); 393 for (const auto& II : Inputs) 394 CmdArgs.push_back(Args.MakeArgString(II.getFilename())); 395 396 for (const auto& A : Args.getAllArgValues(options::OPT_Xcuda_ptxas)) 397 CmdArgs.push_back(Args.MakeArgString(A)); 398 399 bool Relocatable = false; 400 if (JA.isOffloading(Action::OFK_OpenMP)) 401 // In OpenMP we need to generate relocatable code. 402 Relocatable = Args.hasFlag(options::OPT_fopenmp_relocatable_target, 403 options::OPT_fnoopenmp_relocatable_target, 404 /*Default=*/true); 405 else if (JA.isOffloading(Action::OFK_Cuda)) 406 Relocatable = Args.hasFlag(options::OPT_fgpu_rdc, 407 options::OPT_fno_gpu_rdc, /*Default=*/false); 408 409 if (Relocatable) 410 CmdArgs.push_back("-c"); 411 412 const char *Exec; 413 if (Arg *A = Args.getLastArg(options::OPT_ptxas_path_EQ)) 414 Exec = A->getValue(); 415 else 416 Exec = Args.MakeArgString(TC.GetProgramPath("ptxas")); 417 C.addCommand(std::make_unique<Command>(JA, *this, Exec, CmdArgs, Inputs)); 418 } 419 420 static bool shouldIncludePTX(const ArgList &Args, const char *gpu_arch) { 421 bool includePTX = true; 422 for (Arg *A : Args) { 423 if (!(A->getOption().matches(options::OPT_cuda_include_ptx_EQ) || 424 A->getOption().matches(options::OPT_no_cuda_include_ptx_EQ))) 425 continue; 426 A->claim(); 427 const StringRef ArchStr = A->getValue(); 428 if (ArchStr == "all" || ArchStr == gpu_arch) { 429 includePTX = A->getOption().matches(options::OPT_cuda_include_ptx_EQ); 430 continue; 431 } 432 } 433 return includePTX; 434 } 435 436 // All inputs to this linker must be from CudaDeviceActions, as we need to look 437 // at the Inputs' Actions in order to figure out which GPU architecture they 438 // correspond to. 439 void NVPTX::Linker::ConstructJob(Compilation &C, const JobAction &JA, 440 const InputInfo &Output, 441 const InputInfoList &Inputs, 442 const ArgList &Args, 443 const char *LinkingOutput) const { 444 const auto &TC = 445 static_cast<const toolchains::CudaToolChain &>(getToolChain()); 446 assert(TC.getTriple().isNVPTX() && "Wrong platform"); 447 448 ArgStringList CmdArgs; 449 if (TC.CudaInstallation.version() <= CudaVersion::CUDA_100) 450 CmdArgs.push_back("--cuda"); 451 CmdArgs.push_back(TC.getTriple().isArch64Bit() ? "-64" : "-32"); 452 CmdArgs.push_back(Args.MakeArgString("--create")); 453 CmdArgs.push_back(Args.MakeArgString(Output.getFilename())); 454 if (mustEmitDebugInfo(Args) == EmitSameDebugInfoAsHost) 455 CmdArgs.push_back("-g"); 456 457 for (const auto& II : Inputs) { 458 auto *A = II.getAction(); 459 assert(A->getInputs().size() == 1 && 460 "Device offload action is expected to have a single input"); 461 const char *gpu_arch_str = A->getOffloadingArch(); 462 assert(gpu_arch_str && 463 "Device action expected to have associated a GPU architecture!"); 464 CudaArch gpu_arch = StringToCudaArch(gpu_arch_str); 465 466 if (II.getType() == types::TY_PP_Asm && 467 !shouldIncludePTX(Args, gpu_arch_str)) 468 continue; 469 // We need to pass an Arch of the form "sm_XX" for cubin files and 470 // "compute_XX" for ptx. 471 const char *Arch = 472 (II.getType() == types::TY_PP_Asm) 473 ? CudaVirtualArchToString(VirtualArchForCudaArch(gpu_arch)) 474 : gpu_arch_str; 475 CmdArgs.push_back(Args.MakeArgString(llvm::Twine("--image=profile=") + 476 Arch + ",file=" + II.getFilename())); 477 } 478 479 for (const auto& A : Args.getAllArgValues(options::OPT_Xcuda_fatbinary)) 480 CmdArgs.push_back(Args.MakeArgString(A)); 481 482 const char *Exec = Args.MakeArgString(TC.GetProgramPath("fatbinary")); 483 C.addCommand(std::make_unique<Command>(JA, *this, Exec, CmdArgs, Inputs)); 484 } 485 486 void NVPTX::OpenMPLinker::ConstructJob(Compilation &C, const JobAction &JA, 487 const InputInfo &Output, 488 const InputInfoList &Inputs, 489 const ArgList &Args, 490 const char *LinkingOutput) const { 491 const auto &TC = 492 static_cast<const toolchains::CudaToolChain &>(getToolChain()); 493 assert(TC.getTriple().isNVPTX() && "Wrong platform"); 494 495 ArgStringList CmdArgs; 496 497 // OpenMP uses nvlink to link cubin files. The result will be embedded in the 498 // host binary by the host linker. 499 assert(!JA.isHostOffloading(Action::OFK_OpenMP) && 500 "CUDA toolchain not expected for an OpenMP host device."); 501 502 if (Output.isFilename()) { 503 CmdArgs.push_back("-o"); 504 CmdArgs.push_back(Output.getFilename()); 505 } else 506 assert(Output.isNothing() && "Invalid output."); 507 if (mustEmitDebugInfo(Args) == EmitSameDebugInfoAsHost) 508 CmdArgs.push_back("-g"); 509 510 if (Args.hasArg(options::OPT_v)) 511 CmdArgs.push_back("-v"); 512 513 StringRef GPUArch = 514 Args.getLastArgValue(options::OPT_march_EQ); 515 assert(!GPUArch.empty() && "At least one GPU Arch required for ptxas."); 516 517 CmdArgs.push_back("-arch"); 518 CmdArgs.push_back(Args.MakeArgString(GPUArch)); 519 520 // Assume that the directory specified with --libomptarget_nvptx_path 521 // contains the static library libomptarget-nvptx.a. 522 if (const Arg *A = Args.getLastArg(options::OPT_libomptarget_nvptx_path_EQ)) 523 CmdArgs.push_back(Args.MakeArgString(Twine("-L") + A->getValue())); 524 525 // Add paths specified in LIBRARY_PATH environment variable as -L options. 526 addDirectoryList(Args, CmdArgs, "-L", "LIBRARY_PATH"); 527 528 // Add paths for the default clang library path. 529 SmallString<256> DefaultLibPath = 530 llvm::sys::path::parent_path(TC.getDriver().Dir); 531 llvm::sys::path::append(DefaultLibPath, "lib" CLANG_LIBDIR_SUFFIX); 532 CmdArgs.push_back(Args.MakeArgString(Twine("-L") + DefaultLibPath)); 533 534 // Add linking against library implementing OpenMP calls on NVPTX target. 535 CmdArgs.push_back("-lomptarget-nvptx"); 536 537 for (const auto &II : Inputs) { 538 if (II.getType() == types::TY_LLVM_IR || 539 II.getType() == types::TY_LTO_IR || 540 II.getType() == types::TY_LTO_BC || 541 II.getType() == types::TY_LLVM_BC) { 542 C.getDriver().Diag(diag::err_drv_no_linker_llvm_support) 543 << getToolChain().getTripleString(); 544 continue; 545 } 546 547 // Currently, we only pass the input files to the linker, we do not pass 548 // any libraries that may be valid only for the host. 549 if (!II.isFilename()) 550 continue; 551 552 const char *CubinF = C.addTempFile( 553 C.getArgs().MakeArgString(getToolChain().getInputFilename(II))); 554 555 CmdArgs.push_back(CubinF); 556 } 557 558 const char *Exec = 559 Args.MakeArgString(getToolChain().GetProgramPath("nvlink")); 560 C.addCommand(std::make_unique<Command>(JA, *this, Exec, CmdArgs, Inputs)); 561 } 562 563 /// CUDA toolchain. Our assembler is ptxas, and our "linker" is fatbinary, 564 /// which isn't properly a linker but nonetheless performs the step of stitching 565 /// together object files from the assembler into a single blob. 566 567 CudaToolChain::CudaToolChain(const Driver &D, const llvm::Triple &Triple, 568 const ToolChain &HostTC, const ArgList &Args, 569 const Action::OffloadKind OK) 570 : ToolChain(D, Triple, Args), HostTC(HostTC), 571 CudaInstallation(D, HostTC.getTriple(), Args), OK(OK) { 572 if (CudaInstallation.isValid()) { 573 CudaInstallation.WarnIfUnsupportedVersion(); 574 getProgramPaths().push_back(CudaInstallation.getBinPath()); 575 } 576 // Lookup binaries into the driver directory, this is used to 577 // discover the clang-offload-bundler executable. 578 getProgramPaths().push_back(getDriver().Dir); 579 } 580 581 std::string CudaToolChain::getInputFilename(const InputInfo &Input) const { 582 // Only object files are changed, for example assembly files keep their .s 583 // extensions. CUDA also continues to use .o as they don't use nvlink but 584 // fatbinary. 585 if (!(OK == Action::OFK_OpenMP && Input.getType() == types::TY_Object)) 586 return ToolChain::getInputFilename(Input); 587 588 // Replace extension for object files with cubin because nvlink relies on 589 // these particular file names. 590 SmallString<256> Filename(ToolChain::getInputFilename(Input)); 591 llvm::sys::path::replace_extension(Filename, "cubin"); 592 return Filename.str(); 593 } 594 595 void CudaToolChain::addClangTargetOptions( 596 const llvm::opt::ArgList &DriverArgs, 597 llvm::opt::ArgStringList &CC1Args, 598 Action::OffloadKind DeviceOffloadingKind) const { 599 HostTC.addClangTargetOptions(DriverArgs, CC1Args, DeviceOffloadingKind); 600 601 StringRef GpuArch = DriverArgs.getLastArgValue(options::OPT_march_EQ); 602 assert(!GpuArch.empty() && "Must have an explicit GPU arch."); 603 assert((DeviceOffloadingKind == Action::OFK_OpenMP || 604 DeviceOffloadingKind == Action::OFK_Cuda) && 605 "Only OpenMP or CUDA offloading kinds are supported for NVIDIA GPUs."); 606 607 if (DeviceOffloadingKind == Action::OFK_Cuda) { 608 CC1Args.push_back("-fcuda-is-device"); 609 610 if (DriverArgs.hasFlag(options::OPT_fcuda_flush_denormals_to_zero, 611 options::OPT_fno_cuda_flush_denormals_to_zero, false)) 612 CC1Args.push_back("-fcuda-flush-denormals-to-zero"); 613 614 if (DriverArgs.hasFlag(options::OPT_fcuda_approx_transcendentals, 615 options::OPT_fno_cuda_approx_transcendentals, false)) 616 CC1Args.push_back("-fcuda-approx-transcendentals"); 617 618 if (DriverArgs.hasFlag(options::OPT_fgpu_rdc, options::OPT_fno_gpu_rdc, 619 false)) 620 CC1Args.push_back("-fgpu-rdc"); 621 } 622 623 if (DriverArgs.hasArg(options::OPT_nogpulib)) 624 return; 625 626 std::string LibDeviceFile = CudaInstallation.getLibDeviceFile(GpuArch); 627 628 if (LibDeviceFile.empty()) { 629 if (DeviceOffloadingKind == Action::OFK_OpenMP && 630 DriverArgs.hasArg(options::OPT_S)) 631 return; 632 633 getDriver().Diag(diag::err_drv_no_cuda_libdevice) << GpuArch; 634 return; 635 } 636 637 CC1Args.push_back("-mlink-builtin-bitcode"); 638 CC1Args.push_back(DriverArgs.MakeArgString(LibDeviceFile)); 639 640 // New CUDA versions often introduce new instructions that are only supported 641 // by new PTX version, so we need to raise PTX level to enable them in NVPTX 642 // back-end. 643 const char *PtxFeature = nullptr; 644 switch(CudaInstallation.version()) { 645 case CudaVersion::CUDA_101: 646 PtxFeature = "+ptx64"; 647 break; 648 case CudaVersion::CUDA_100: 649 PtxFeature = "+ptx63"; 650 break; 651 case CudaVersion::CUDA_92: 652 PtxFeature = "+ptx61"; 653 break; 654 case CudaVersion::CUDA_91: 655 PtxFeature = "+ptx61"; 656 break; 657 case CudaVersion::CUDA_90: 658 PtxFeature = "+ptx60"; 659 break; 660 default: 661 PtxFeature = "+ptx42"; 662 } 663 CC1Args.append({"-target-feature", PtxFeature}); 664 if (DriverArgs.hasFlag(options::OPT_fcuda_short_ptr, 665 options::OPT_fno_cuda_short_ptr, false)) 666 CC1Args.append({"-mllvm", "--nvptx-short-ptr"}); 667 668 if (CudaInstallation.version() >= CudaVersion::UNKNOWN) 669 CC1Args.push_back(DriverArgs.MakeArgString( 670 Twine("-target-sdk-version=") + 671 CudaVersionToString(CudaInstallation.version()))); 672 673 if (DeviceOffloadingKind == Action::OFK_OpenMP) { 674 SmallVector<StringRef, 8> LibraryPaths; 675 if (const Arg *A = DriverArgs.getLastArg(options::OPT_libomptarget_nvptx_path_EQ)) 676 LibraryPaths.push_back(A->getValue()); 677 678 // Add user defined library paths from LIBRARY_PATH. 679 llvm::Optional<std::string> LibPath = 680 llvm::sys::Process::GetEnv("LIBRARY_PATH"); 681 if (LibPath) { 682 SmallVector<StringRef, 8> Frags; 683 const char EnvPathSeparatorStr[] = {llvm::sys::EnvPathSeparator, '\0'}; 684 llvm::SplitString(*LibPath, Frags, EnvPathSeparatorStr); 685 for (StringRef Path : Frags) 686 LibraryPaths.emplace_back(Path.trim()); 687 } 688 689 // Add path to lib / lib64 folder. 690 SmallString<256> DefaultLibPath = 691 llvm::sys::path::parent_path(getDriver().Dir); 692 llvm::sys::path::append(DefaultLibPath, Twine("lib") + CLANG_LIBDIR_SUFFIX); 693 LibraryPaths.emplace_back(DefaultLibPath.c_str()); 694 695 std::string LibOmpTargetName = 696 "libomptarget-nvptx-" + GpuArch.str() + ".bc"; 697 bool FoundBCLibrary = false; 698 for (StringRef LibraryPath : LibraryPaths) { 699 SmallString<128> LibOmpTargetFile(LibraryPath); 700 llvm::sys::path::append(LibOmpTargetFile, LibOmpTargetName); 701 if (llvm::sys::fs::exists(LibOmpTargetFile)) { 702 CC1Args.push_back("-mlink-builtin-bitcode"); 703 CC1Args.push_back(DriverArgs.MakeArgString(LibOmpTargetFile)); 704 FoundBCLibrary = true; 705 break; 706 } 707 } 708 if (!FoundBCLibrary) 709 getDriver().Diag(diag::warn_drv_omp_offload_target_missingbcruntime) 710 << LibOmpTargetName; 711 } 712 } 713 714 bool CudaToolChain::supportsDebugInfoOption(const llvm::opt::Arg *A) const { 715 const Option &O = A->getOption(); 716 return (O.matches(options::OPT_gN_Group) && 717 !O.matches(options::OPT_gmodules)) || 718 O.matches(options::OPT_g_Flag) || 719 O.matches(options::OPT_ggdbN_Group) || O.matches(options::OPT_ggdb) || 720 O.matches(options::OPT_gdwarf) || O.matches(options::OPT_gdwarf_2) || 721 O.matches(options::OPT_gdwarf_3) || O.matches(options::OPT_gdwarf_4) || 722 O.matches(options::OPT_gdwarf_5) || 723 O.matches(options::OPT_gcolumn_info); 724 } 725 726 void CudaToolChain::adjustDebugInfoKind( 727 codegenoptions::DebugInfoKind &DebugInfoKind, const ArgList &Args) const { 728 switch (mustEmitDebugInfo(Args)) { 729 case DisableDebugInfo: 730 DebugInfoKind = codegenoptions::NoDebugInfo; 731 break; 732 case DebugDirectivesOnly: 733 DebugInfoKind = codegenoptions::DebugDirectivesOnly; 734 break; 735 case EmitSameDebugInfoAsHost: 736 // Use same debug info level as the host. 737 break; 738 } 739 } 740 741 void CudaToolChain::AddCudaIncludeArgs(const ArgList &DriverArgs, 742 ArgStringList &CC1Args) const { 743 // Check our CUDA version if we're going to include the CUDA headers. 744 if (!DriverArgs.hasArg(options::OPT_nocudainc) && 745 !DriverArgs.hasArg(options::OPT_no_cuda_version_check)) { 746 StringRef Arch = DriverArgs.getLastArgValue(options::OPT_march_EQ); 747 assert(!Arch.empty() && "Must have an explicit GPU arch."); 748 CudaInstallation.CheckCudaVersionSupportsArch(StringToCudaArch(Arch)); 749 } 750 CudaInstallation.AddCudaIncludeArgs(DriverArgs, CC1Args); 751 } 752 753 llvm::opt::DerivedArgList * 754 CudaToolChain::TranslateArgs(const llvm::opt::DerivedArgList &Args, 755 StringRef BoundArch, 756 Action::OffloadKind DeviceOffloadKind) const { 757 DerivedArgList *DAL = 758 HostTC.TranslateArgs(Args, BoundArch, DeviceOffloadKind); 759 if (!DAL) 760 DAL = new DerivedArgList(Args.getBaseArgs()); 761 762 const OptTable &Opts = getDriver().getOpts(); 763 764 // For OpenMP device offloading, append derived arguments. Make sure 765 // flags are not duplicated. 766 // Also append the compute capability. 767 if (DeviceOffloadKind == Action::OFK_OpenMP) { 768 for (Arg *A : Args) { 769 bool IsDuplicate = false; 770 for (Arg *DALArg : *DAL) { 771 if (A == DALArg) { 772 IsDuplicate = true; 773 break; 774 } 775 } 776 if (!IsDuplicate) 777 DAL->append(A); 778 } 779 780 StringRef Arch = DAL->getLastArgValue(options::OPT_march_EQ); 781 if (Arch.empty()) 782 DAL->AddJoinedArg(nullptr, Opts.getOption(options::OPT_march_EQ), 783 CLANG_OPENMP_NVPTX_DEFAULT_ARCH); 784 785 return DAL; 786 } 787 788 for (Arg *A : Args) { 789 if (A->getOption().matches(options::OPT_Xarch__)) { 790 // Skip this argument unless the architecture matches BoundArch 791 if (BoundArch.empty() || A->getValue(0) != BoundArch) 792 continue; 793 794 unsigned Index = Args.getBaseArgs().MakeIndex(A->getValue(1)); 795 unsigned Prev = Index; 796 std::unique_ptr<Arg> XarchArg(Opts.ParseOneArg(Args, Index)); 797 798 // If the argument parsing failed or more than one argument was 799 // consumed, the -Xarch_ argument's parameter tried to consume 800 // extra arguments. Emit an error and ignore. 801 // 802 // We also want to disallow any options which would alter the 803 // driver behavior; that isn't going to work in our model. We 804 // use isDriverOption() as an approximation, although things 805 // like -O4 are going to slip through. 806 if (!XarchArg || Index > Prev + 1) { 807 getDriver().Diag(diag::err_drv_invalid_Xarch_argument_with_args) 808 << A->getAsString(Args); 809 continue; 810 } else if (XarchArg->getOption().hasFlag(options::DriverOption)) { 811 getDriver().Diag(diag::err_drv_invalid_Xarch_argument_isdriver) 812 << A->getAsString(Args); 813 continue; 814 } 815 XarchArg->setBaseArg(A); 816 A = XarchArg.release(); 817 DAL->AddSynthesizedArg(A); 818 } 819 DAL->append(A); 820 } 821 822 if (!BoundArch.empty()) { 823 DAL->eraseArg(options::OPT_march_EQ); 824 DAL->AddJoinedArg(nullptr, Opts.getOption(options::OPT_march_EQ), BoundArch); 825 } 826 return DAL; 827 } 828 829 Tool *CudaToolChain::buildAssembler() const { 830 return new tools::NVPTX::Assembler(*this); 831 } 832 833 Tool *CudaToolChain::buildLinker() const { 834 if (OK == Action::OFK_OpenMP) 835 return new tools::NVPTX::OpenMPLinker(*this); 836 return new tools::NVPTX::Linker(*this); 837 } 838 839 void CudaToolChain::addClangWarningOptions(ArgStringList &CC1Args) const { 840 HostTC.addClangWarningOptions(CC1Args); 841 } 842 843 ToolChain::CXXStdlibType 844 CudaToolChain::GetCXXStdlibType(const ArgList &Args) const { 845 return HostTC.GetCXXStdlibType(Args); 846 } 847 848 void CudaToolChain::AddClangSystemIncludeArgs(const ArgList &DriverArgs, 849 ArgStringList &CC1Args) const { 850 HostTC.AddClangSystemIncludeArgs(DriverArgs, CC1Args); 851 } 852 853 void CudaToolChain::AddClangCXXStdlibIncludeArgs(const ArgList &Args, 854 ArgStringList &CC1Args) const { 855 HostTC.AddClangCXXStdlibIncludeArgs(Args, CC1Args); 856 } 857 858 void CudaToolChain::AddIAMCUIncludeArgs(const ArgList &Args, 859 ArgStringList &CC1Args) const { 860 HostTC.AddIAMCUIncludeArgs(Args, CC1Args); 861 } 862 863 SanitizerMask CudaToolChain::getSupportedSanitizers() const { 864 // The CudaToolChain only supports sanitizers in the sense that it allows 865 // sanitizer arguments on the command line if they are supported by the host 866 // toolchain. The CudaToolChain will actually ignore any command line 867 // arguments for any of these "supported" sanitizers. That means that no 868 // sanitization of device code is actually supported at this time. 869 // 870 // This behavior is necessary because the host and device toolchains 871 // invocations often share the command line, so the device toolchain must 872 // tolerate flags meant only for the host toolchain. 873 return HostTC.getSupportedSanitizers(); 874 } 875 876 VersionTuple CudaToolChain::computeMSVCVersion(const Driver *D, 877 const ArgList &Args) const { 878 return HostTC.computeMSVCVersion(D, Args); 879 } 880