| //===--- Cuda.cpp - Cuda Tool and ToolChain Implementations -----*- C++ -*-===// |
| // |
| // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
| // See https://llvm.org/LICENSE.txt for license information. |
| // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
| // |
| //===----------------------------------------------------------------------===// |
| |
| #include "Cuda.h" |
| #include "CommonArgs.h" |
| #include "clang/Basic/Cuda.h" |
| #include "clang/Config/config.h" |
| #include "clang/Driver/Compilation.h" |
| #include "clang/Driver/Distro.h" |
| #include "clang/Driver/Driver.h" |
| #include "clang/Driver/DriverDiagnostic.h" |
| #include "clang/Driver/InputInfo.h" |
| #include "clang/Driver/Options.h" |
| #include "llvm/ADT/Optional.h" |
| #include "llvm/ADT/StringExtras.h" |
| #include "llvm/Option/ArgList.h" |
| #include "llvm/Support/FileSystem.h" |
| #include "llvm/Support/Host.h" |
| #include "llvm/Support/Path.h" |
| #include "llvm/Support/Process.h" |
| #include "llvm/Support/Program.h" |
| #include "llvm/Support/TargetParser.h" |
| #include "llvm/Support/VirtualFileSystem.h" |
| #include <system_error> |
| |
| using namespace clang::driver; |
| using namespace clang::driver::toolchains; |
| using namespace clang::driver::tools; |
| using namespace clang; |
| using namespace llvm::opt; |
| |
| namespace { |
| |
| CudaVersion getCudaVersion(uint32_t raw_version) { |
| if (raw_version < 7050) |
| return CudaVersion::CUDA_70; |
| if (raw_version < 8000) |
| return CudaVersion::CUDA_75; |
| if (raw_version < 9000) |
| return CudaVersion::CUDA_80; |
| if (raw_version < 9010) |
| return CudaVersion::CUDA_90; |
| if (raw_version < 9020) |
| return CudaVersion::CUDA_91; |
| if (raw_version < 10000) |
| return CudaVersion::CUDA_92; |
| if (raw_version < 10010) |
| return CudaVersion::CUDA_100; |
| if (raw_version < 10020) |
| return CudaVersion::CUDA_101; |
| if (raw_version < 11000) |
| return CudaVersion::CUDA_102; |
| if (raw_version < 11010) |
| return CudaVersion::CUDA_110; |
| if (raw_version < 11020) |
| return CudaVersion::CUDA_111; |
| if (raw_version < 11030) |
| return CudaVersion::CUDA_112; |
| if (raw_version < 11040) |
| return CudaVersion::CUDA_113; |
| if (raw_version < 11050) |
| return CudaVersion::CUDA_114; |
| if (raw_version < 11060) |
| return CudaVersion::CUDA_115; |
| return CudaVersion::NEW; |
| } |
| |
| CudaVersion parseCudaHFile(llvm::StringRef Input) { |
| // Helper lambda which skips the words if the line starts with them or returns |
| // None otherwise. |
| auto StartsWithWords = |
| [](llvm::StringRef Line, |
| const SmallVector<StringRef, 3> words) -> llvm::Optional<StringRef> { |
| for (StringRef word : words) { |
| if (!Line.consume_front(word)) |
| return {}; |
| Line = Line.ltrim(); |
| } |
| return Line; |
| }; |
| |
| Input = Input.ltrim(); |
| while (!Input.empty()) { |
| if (auto Line = |
| StartsWithWords(Input.ltrim(), {"#", "define", "CUDA_VERSION"})) { |
| uint32_t RawVersion; |
| Line->consumeInteger(10, RawVersion); |
| return getCudaVersion(RawVersion); |
| } |
| // Find next non-empty line. |
| Input = Input.drop_front(Input.find_first_of("\n\r")).ltrim(); |
| } |
| return CudaVersion::UNKNOWN; |
| } |
| } // namespace |
| |
| void CudaInstallationDetector::WarnIfUnsupportedVersion() { |
| if (Version > CudaVersion::PARTIALLY_SUPPORTED) { |
| std::string VersionString = CudaVersionToString(Version); |
| if (!VersionString.empty()) |
| VersionString.insert(0, " "); |
| D.Diag(diag::warn_drv_new_cuda_version) |
| << VersionString |
| << (CudaVersion::PARTIALLY_SUPPORTED != CudaVersion::FULLY_SUPPORTED) |
| << CudaVersionToString(CudaVersion::PARTIALLY_SUPPORTED); |
| } else if (Version > CudaVersion::FULLY_SUPPORTED) |
| D.Diag(diag::warn_drv_partially_supported_cuda_version) |
| << CudaVersionToString(Version); |
| } |
| |
| CudaInstallationDetector::CudaInstallationDetector( |
| const Driver &D, const llvm::Triple &HostTriple, |
| const llvm::opt::ArgList &Args) |
| : D(D) { |
| struct Candidate { |
| std::string Path; |
| bool StrictChecking; |
| |
| Candidate(std::string Path, bool StrictChecking = false) |
| : Path(Path), StrictChecking(StrictChecking) {} |
| }; |
| SmallVector<Candidate, 4> Candidates; |
| |
| // In decreasing order so we prefer newer versions to older versions. |
| std::initializer_list<const char *> Versions = {"8.0", "7.5", "7.0"}; |
| auto &FS = D.getVFS(); |
| |
| if (Args.hasArg(clang::driver::options::OPT_cuda_path_EQ)) { |
| Candidates.emplace_back( |
| Args.getLastArgValue(clang::driver::options::OPT_cuda_path_EQ).str()); |
| } else if (HostTriple.isOSWindows()) { |
| for (const char *Ver : Versions) |
| Candidates.emplace_back( |
| D.SysRoot + "/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v" + |
| Ver); |
| } else { |
| if (!Args.hasArg(clang::driver::options::OPT_cuda_path_ignore_env)) { |
| // Try to find ptxas binary. If the executable is located in a directory |
| // called 'bin/', its parent directory might be a good guess for a valid |
| // CUDA installation. |
| // However, some distributions might installs 'ptxas' to /usr/bin. In that |
| // case the candidate would be '/usr' which passes the following checks |
| // because '/usr/include' exists as well. To avoid this case, we always |
| // check for the directory potentially containing files for libdevice, |
| // even if the user passes -nocudalib. |
| if (llvm::ErrorOr<std::string> ptxas = |
| llvm::sys::findProgramByName("ptxas")) { |
| SmallString<256> ptxasAbsolutePath; |
| llvm::sys::fs::real_path(*ptxas, ptxasAbsolutePath); |
| |
| StringRef ptxasDir = llvm::sys::path::parent_path(ptxasAbsolutePath); |
| if (llvm::sys::path::filename(ptxasDir) == "bin") |
| Candidates.emplace_back( |
| std::string(llvm::sys::path::parent_path(ptxasDir)), |
| /*StrictChecking=*/true); |
| } |
| } |
| |
| Candidates.emplace_back(D.SysRoot + "/usr/local/cuda"); |
| for (const char *Ver : Versions) |
| Candidates.emplace_back(D.SysRoot + "/usr/local/cuda-" + Ver); |
| |
| Distro Dist(FS, llvm::Triple(llvm::sys::getProcessTriple())); |
| if (Dist.IsDebian() || Dist.IsUbuntu()) |
| // Special case for Debian to have nvidia-cuda-toolkit work |
| // out of the box. More info on http://bugs.debian.org/882505 |
| Candidates.emplace_back(D.SysRoot + "/usr/lib/cuda"); |
| } |
| |
| bool NoCudaLib = Args.hasArg(options::OPT_nogpulib); |
| |
| for (const auto &Candidate : Candidates) { |
| InstallPath = Candidate.Path; |
| if (InstallPath.empty() || !FS.exists(InstallPath)) |
| continue; |
| |
| BinPath = InstallPath + "/bin"; |
| IncludePath = InstallPath + "/include"; |
| LibDevicePath = InstallPath + "/nvvm/libdevice"; |
| |
| if (!(FS.exists(IncludePath) && FS.exists(BinPath))) |
| continue; |
| bool CheckLibDevice = (!NoCudaLib || Candidate.StrictChecking); |
| if (CheckLibDevice && !FS.exists(LibDevicePath)) |
| continue; |
| |
| // On Linux, we have both lib and lib64 directories, and we need to choose |
| // based on our triple. On MacOS, we have only a lib directory. |
| // |
| // It's sufficient for our purposes to be flexible: If both lib and lib64 |
| // exist, we choose whichever one matches our triple. Otherwise, if only |
| // lib exists, we use it. |
| if (HostTriple.isArch64Bit() && FS.exists(InstallPath + "/lib64")) |
| LibPath = InstallPath + "/lib64"; |
| else if (FS.exists(InstallPath + "/lib")) |
| LibPath = InstallPath + "/lib"; |
| else |
| continue; |
| |
| Version = CudaVersion::UNKNOWN; |
| if (auto CudaHFile = FS.getBufferForFile(InstallPath + "/include/cuda.h")) |
| Version = parseCudaHFile((*CudaHFile)->getBuffer()); |
| // As the last resort, make an educated guess between CUDA-7.0, which had |
| // old-style libdevice bitcode, and an unknown recent CUDA version. |
| if (Version == CudaVersion::UNKNOWN) { |
| Version = FS.exists(LibDevicePath + "/libdevice.10.bc") |
| ? CudaVersion::NEW |
| : CudaVersion::CUDA_70; |
| } |
| |
| if (Version >= CudaVersion::CUDA_90) { |
| // CUDA-9+ uses single libdevice file for all GPU variants. |
| std::string FilePath = LibDevicePath + "/libdevice.10.bc"; |
| if (FS.exists(FilePath)) { |
| for (int Arch = (int)CudaArch::SM_30, E = (int)CudaArch::LAST; Arch < E; |
| ++Arch) { |
| CudaArch GpuArch = static_cast<CudaArch>(Arch); |
| if (!IsNVIDIAGpuArch(GpuArch)) |
| continue; |
| std::string GpuArchName(CudaArchToString(GpuArch)); |
| LibDeviceMap[GpuArchName] = FilePath; |
| } |
| } |
| } else { |
| std::error_code EC; |
| for (llvm::vfs::directory_iterator LI = FS.dir_begin(LibDevicePath, EC), |
| LE; |
| !EC && LI != LE; LI = LI.increment(EC)) { |
| StringRef FilePath = LI->path(); |
| StringRef FileName = llvm::sys::path::filename(FilePath); |
| // Process all bitcode filenames that look like |
| // libdevice.compute_XX.YY.bc |
| const StringRef LibDeviceName = "libdevice."; |
| if (!(FileName.startswith(LibDeviceName) && FileName.endswith(".bc"))) |
| continue; |
| StringRef GpuArch = FileName.slice( |
| LibDeviceName.size(), FileName.find('.', LibDeviceName.size())); |
| LibDeviceMap[GpuArch] = FilePath.str(); |
| // Insert map entries for specific devices with this compute |
| // capability. NVCC's choice of the libdevice library version is |
| // rather peculiar and depends on the CUDA version. |
| if (GpuArch == "compute_20") { |
| LibDeviceMap["sm_20"] = std::string(FilePath); |
| LibDeviceMap["sm_21"] = std::string(FilePath); |
| LibDeviceMap["sm_32"] = std::string(FilePath); |
| } else if (GpuArch == "compute_30") { |
| LibDeviceMap["sm_30"] = std::string(FilePath); |
| if (Version < CudaVersion::CUDA_80) { |
| LibDeviceMap["sm_50"] = std::string(FilePath); |
| LibDeviceMap["sm_52"] = std::string(FilePath); |
| LibDeviceMap["sm_53"] = std::string(FilePath); |
| } |
| LibDeviceMap["sm_60"] = std::string(FilePath); |
| LibDeviceMap["sm_61"] = std::string(FilePath); |
| LibDeviceMap["sm_62"] = std::string(FilePath); |
| } else if (GpuArch == "compute_35") { |
| LibDeviceMap["sm_35"] = std::string(FilePath); |
| LibDeviceMap["sm_37"] = std::string(FilePath); |
| } else if (GpuArch == "compute_50") { |
| if (Version >= CudaVersion::CUDA_80) { |
| LibDeviceMap["sm_50"] = std::string(FilePath); |
| LibDeviceMap["sm_52"] = std::string(FilePath); |
| LibDeviceMap["sm_53"] = std::string(FilePath); |
| } |
| } |
| } |
| } |
| |
| // Check that we have found at least one libdevice that we can link in if |
| // -nocudalib hasn't been specified. |
| if (LibDeviceMap.empty() && !NoCudaLib) |
| continue; |
| |
| IsValid = true; |
| break; |
| } |
| } |
| |
| void CudaInstallationDetector::AddCudaIncludeArgs( |
| const ArgList &DriverArgs, ArgStringList &CC1Args) const { |
| if (!DriverArgs.hasArg(options::OPT_nobuiltininc)) { |
| // Add cuda_wrappers/* to our system include path. This lets us wrap |
| // standard library headers. |
| SmallString<128> P(D.ResourceDir); |
| llvm::sys::path::append(P, "include"); |
| llvm::sys::path::append(P, "cuda_wrappers"); |
| CC1Args.push_back("-internal-isystem"); |
| CC1Args.push_back(DriverArgs.MakeArgString(P)); |
| } |
| |
| if (DriverArgs.hasArg(options::OPT_nogpuinc)) |
| return; |
| |
| if (!isValid()) { |
| D.Diag(diag::err_drv_no_cuda_installation); |
| return; |
| } |
| |
| CC1Args.push_back("-include"); |
| CC1Args.push_back("__clang_cuda_runtime_wrapper.h"); |
| } |
| |
| void CudaInstallationDetector::CheckCudaVersionSupportsArch( |
| CudaArch Arch) const { |
| if (Arch == CudaArch::UNKNOWN || Version == CudaVersion::UNKNOWN || |
| ArchsWithBadVersion[(int)Arch]) |
| return; |
| |
| auto MinVersion = MinVersionForCudaArch(Arch); |
| auto MaxVersion = MaxVersionForCudaArch(Arch); |
| if (Version < MinVersion || Version > MaxVersion) { |
| ArchsWithBadVersion[(int)Arch] = true; |
| D.Diag(diag::err_drv_cuda_version_unsupported) |
| << CudaArchToString(Arch) << CudaVersionToString(MinVersion) |
| << CudaVersionToString(MaxVersion) << InstallPath |
| << CudaVersionToString(Version); |
| } |
| } |
| |
| void CudaInstallationDetector::print(raw_ostream &OS) const { |
| if (isValid()) |
| OS << "Found CUDA installation: " << InstallPath << ", version " |
| << CudaVersionToString(Version) << "\n"; |
| } |
| |
| namespace { |
| /// Debug info level for the NVPTX devices. We may need to emit different debug |
| /// info level for the host and for the device itselfi. This type controls |
| /// emission of the debug info for the devices. It either prohibits disable info |
| /// emission completely, or emits debug directives only, or emits same debug |
| /// info as for the host. |
| enum DeviceDebugInfoLevel { |
| DisableDebugInfo, /// Do not emit debug info for the devices. |
| DebugDirectivesOnly, /// Emit only debug directives. |
| EmitSameDebugInfoAsHost, /// Use the same debug info level just like for the |
| /// host. |
| }; |
| } // anonymous namespace |
| |
| /// Define debug info level for the NVPTX devices. If the debug info for both |
| /// the host and device are disabled (-g0/-ggdb0 or no debug options at all). If |
| /// only debug directives are requested for the both host and device |
| /// (-gline-directvies-only), or the debug info only for the device is disabled |
| /// (optimization is on and --cuda-noopt-device-debug was not specified), the |
| /// debug directves only must be emitted for the device. Otherwise, use the same |
| /// debug info level just like for the host (with the limitations of only |
| /// supported DWARF2 standard). |
| static DeviceDebugInfoLevel mustEmitDebugInfo(const ArgList &Args) { |
| const Arg *A = Args.getLastArg(options::OPT_O_Group); |
| bool IsDebugEnabled = !A || A->getOption().matches(options::OPT_O0) || |
| Args.hasFlag(options::OPT_cuda_noopt_device_debug, |
| options::OPT_no_cuda_noopt_device_debug, |
| /*Default=*/false); |
| if (const Arg *A = Args.getLastArg(options::OPT_g_Group)) { |
| const Option &Opt = A->getOption(); |
| if (Opt.matches(options::OPT_gN_Group)) { |
| if (Opt.matches(options::OPT_g0) || Opt.matches(options::OPT_ggdb0)) |
| return DisableDebugInfo; |
| if (Opt.matches(options::OPT_gline_directives_only)) |
| return DebugDirectivesOnly; |
| } |
| return IsDebugEnabled ? EmitSameDebugInfoAsHost : DebugDirectivesOnly; |
| } |
| return willEmitRemarks(Args) ? DebugDirectivesOnly : DisableDebugInfo; |
| } |
| |
| void NVPTX::Assembler::ConstructJob(Compilation &C, const JobAction &JA, |
| const InputInfo &Output, |
| const InputInfoList &Inputs, |
| const ArgList &Args, |
| const char *LinkingOutput) const { |
| const auto &TC = |
| static_cast<const toolchains::CudaToolChain &>(getToolChain()); |
| assert(TC.getTriple().isNVPTX() && "Wrong platform"); |
| |
| StringRef GPUArchName; |
| // If this is an OpenMP action we need to extract the device architecture |
| // from the -march=arch option. This option may come from -Xopenmp-target |
| // flag or the default value. |
| if (JA.isDeviceOffloading(Action::OFK_OpenMP)) { |
| GPUArchName = Args.getLastArgValue(options::OPT_march_EQ); |
| assert(!GPUArchName.empty() && "Must have an architecture passed in."); |
| } else |
| GPUArchName = JA.getOffloadingArch(); |
| |
| // Obtain architecture from the action. |
| CudaArch gpu_arch = StringToCudaArch(GPUArchName); |
| assert(gpu_arch != CudaArch::UNKNOWN && |
| "Device action expected to have an architecture."); |
| |
| // Check that our installation's ptxas supports gpu_arch. |
| if (!Args.hasArg(options::OPT_no_cuda_version_check)) { |
| TC.CudaInstallation.CheckCudaVersionSupportsArch(gpu_arch); |
| } |
| |
| ArgStringList CmdArgs; |
| CmdArgs.push_back(TC.getTriple().isArch64Bit() ? "-m64" : "-m32"); |
| DeviceDebugInfoLevel DIKind = mustEmitDebugInfo(Args); |
| if (DIKind == EmitSameDebugInfoAsHost) { |
| // ptxas does not accept -g option if optimization is enabled, so |
| // we ignore the compiler's -O* options if we want debug info. |
| CmdArgs.push_back("-g"); |
| CmdArgs.push_back("--dont-merge-basicblocks"); |
| CmdArgs.push_back("--return-at-end"); |
| } else if (Arg *A = Args.getLastArg(options::OPT_O_Group)) { |
| // Map the -O we received to -O{0,1,2,3}. |
| // |
| // TODO: Perhaps we should map host -O2 to ptxas -O3. -O3 is ptxas's |
| // default, so it may correspond more closely to the spirit of clang -O2. |
| |
| // -O3 seems like the least-bad option when -Osomething is specified to |
| // clang but it isn't handled below. |
| StringRef OOpt = "3"; |
| if (A->getOption().matches(options::OPT_O4) || |
| A->getOption().matches(options::OPT_Ofast)) |
| OOpt = "3"; |
| else if (A->getOption().matches(options::OPT_O0)) |
| OOpt = "0"; |
| else if (A->getOption().matches(options::OPT_O)) { |
| // -Os, -Oz, and -O(anything else) map to -O2, for lack of better options. |
| OOpt = llvm::StringSwitch<const char *>(A->getValue()) |
| .Case("1", "1") |
| .Case("2", "2") |
| .Case("3", "3") |
| .Case("s", "2") |
| .Case("z", "2") |
| .Default("2"); |
| } |
| CmdArgs.push_back(Args.MakeArgString(llvm::Twine("-O") + OOpt)); |
| } else { |
| // If no -O was passed, pass -O0 to ptxas -- no opt flag should correspond |
| // to no optimizations, but ptxas's default is -O3. |
| CmdArgs.push_back("-O0"); |
| } |
| if (DIKind == DebugDirectivesOnly) |
| CmdArgs.push_back("-lineinfo"); |
| |
| // Pass -v to ptxas if it was passed to the driver. |
| if (Args.hasArg(options::OPT_v)) |
| CmdArgs.push_back("-v"); |
| |
| CmdArgs.push_back("--gpu-name"); |
| CmdArgs.push_back(Args.MakeArgString(CudaArchToString(gpu_arch))); |
| CmdArgs.push_back("--output-file"); |
| CmdArgs.push_back(Args.MakeArgString(TC.getInputFilename(Output))); |
| for (const auto& II : Inputs) |
| CmdArgs.push_back(Args.MakeArgString(II.getFilename())); |
| |
| for (const auto& A : Args.getAllArgValues(options::OPT_Xcuda_ptxas)) |
| CmdArgs.push_back(Args.MakeArgString(A)); |
| |
| bool Relocatable = false; |
| if (JA.isOffloading(Action::OFK_OpenMP)) |
| // In OpenMP we need to generate relocatable code. |
| Relocatable = Args.hasFlag(options::OPT_fopenmp_relocatable_target, |
| options::OPT_fnoopenmp_relocatable_target, |
| /*Default=*/true); |
| else if (JA.isOffloading(Action::OFK_Cuda)) |
| Relocatable = Args.hasFlag(options::OPT_fgpu_rdc, |
| options::OPT_fno_gpu_rdc, /*Default=*/false); |
| |
| if (Relocatable) |
| CmdArgs.push_back("-c"); |
| |
| const char *Exec; |
| if (Arg *A = Args.getLastArg(options::OPT_ptxas_path_EQ)) |
| Exec = A->getValue(); |
| else |
| Exec = Args.MakeArgString(TC.GetProgramPath("ptxas")); |
| C.addCommand(std::make_unique<Command>( |
| JA, *this, |
| ResponseFileSupport{ResponseFileSupport::RF_Full, llvm::sys::WEM_UTF8, |
| "--options-file"}, |
| Exec, CmdArgs, Inputs, Output)); |
| } |
| |
| static bool shouldIncludePTX(const ArgList &Args, const char *gpu_arch) { |
| bool includePTX = true; |
| for (Arg *A : Args) { |
| if (!(A->getOption().matches(options::OPT_cuda_include_ptx_EQ) || |
| A->getOption().matches(options::OPT_no_cuda_include_ptx_EQ))) |
| continue; |
| A->claim(); |
| const StringRef ArchStr = A->getValue(); |
| if (ArchStr == "all" || ArchStr == gpu_arch) { |
| includePTX = A->getOption().matches(options::OPT_cuda_include_ptx_EQ); |
| continue; |
| } |
| } |
| return includePTX; |
| } |
| |
| // All inputs to this linker must be from CudaDeviceActions, as we need to look |
| // at the Inputs' Actions in order to figure out which GPU architecture they |
| // correspond to. |
| void NVPTX::Linker::ConstructJob(Compilation &C, const JobAction &JA, |
| const InputInfo &Output, |
| const InputInfoList &Inputs, |
| const ArgList &Args, |
| const char *LinkingOutput) const { |
| const auto &TC = |
| static_cast<const toolchains::CudaToolChain &>(getToolChain()); |
| assert(TC.getTriple().isNVPTX() && "Wrong platform"); |
| |
| ArgStringList CmdArgs; |
| if (TC.CudaInstallation.version() <= CudaVersion::CUDA_100) |
| CmdArgs.push_back("--cuda"); |
| CmdArgs.push_back(TC.getTriple().isArch64Bit() ? "-64" : "-32"); |
| CmdArgs.push_back(Args.MakeArgString("--create")); |
| CmdArgs.push_back(Args.MakeArgString(Output.getFilename())); |
| if (mustEmitDebugInfo(Args) == EmitSameDebugInfoAsHost) |
| CmdArgs.push_back("-g"); |
| |
| for (const auto& II : Inputs) { |
| auto *A = II.getAction(); |
| assert(A->getInputs().size() == 1 && |
| "Device offload action is expected to have a single input"); |
| const char *gpu_arch_str = A->getOffloadingArch(); |
| assert(gpu_arch_str && |
| "Device action expected to have associated a GPU architecture!"); |
| CudaArch gpu_arch = StringToCudaArch(gpu_arch_str); |
| |
| if (II.getType() == types::TY_PP_Asm && |
| !shouldIncludePTX(Args, gpu_arch_str)) |
| continue; |
| // We need to pass an Arch of the form "sm_XX" for cubin files and |
| // "compute_XX" for ptx. |
| const char *Arch = (II.getType() == types::TY_PP_Asm) |
| ? CudaArchToVirtualArchString(gpu_arch) |
| : gpu_arch_str; |
| CmdArgs.push_back(Args.MakeArgString(llvm::Twine("--image=profile=") + |
| Arch + ",file=" + II.getFilename())); |
| } |
| |
| for (const auto& A : Args.getAllArgValues(options::OPT_Xcuda_fatbinary)) |
| CmdArgs.push_back(Args.MakeArgString(A)); |
| |
| const char *Exec = Args.MakeArgString(TC.GetProgramPath("fatbinary")); |
| C.addCommand(std::make_unique<Command>( |
| JA, *this, |
| ResponseFileSupport{ResponseFileSupport::RF_Full, llvm::sys::WEM_UTF8, |
| "--options-file"}, |
| Exec, CmdArgs, Inputs, Output)); |
| } |
| |
| void NVPTX::OpenMPLinker::ConstructJob(Compilation &C, const JobAction &JA, |
| const InputInfo &Output, |
| const InputInfoList &Inputs, |
| const ArgList &Args, |
| const char *LinkingOutput) const { |
| const auto &TC = |
| static_cast<const toolchains::CudaToolChain &>(getToolChain()); |
| assert(TC.getTriple().isNVPTX() && "Wrong platform"); |
| |
| ArgStringList CmdArgs; |
| |
| // OpenMP uses nvlink to link cubin files. The result will be embedded in the |
| // host binary by the host linker. |
| assert(!JA.isHostOffloading(Action::OFK_OpenMP) && |
| "CUDA toolchain not expected for an OpenMP host device."); |
| |
| if (Output.isFilename()) { |
| CmdArgs.push_back("-o"); |
| CmdArgs.push_back(Output.getFilename()); |
| } else |
| assert(Output.isNothing() && "Invalid output."); |
| if (mustEmitDebugInfo(Args) == EmitSameDebugInfoAsHost) |
| CmdArgs.push_back("-g"); |
| |
| if (Args.hasArg(options::OPT_v)) |
| CmdArgs.push_back("-v"); |
| |
| StringRef GPUArch = |
| Args.getLastArgValue(options::OPT_march_EQ); |
| assert(!GPUArch.empty() && "At least one GPU Arch required for ptxas."); |
| |
| CmdArgs.push_back("-arch"); |
| CmdArgs.push_back(Args.MakeArgString(GPUArch)); |
| |
| // Add paths specified in LIBRARY_PATH environment variable as -L options. |
| addDirectoryList(Args, CmdArgs, "-L", "LIBRARY_PATH"); |
| |
| // Add paths for the default clang library path. |
| SmallString<256> DefaultLibPath = |
| llvm::sys::path::parent_path(TC.getDriver().Dir); |
| llvm::sys::path::append(DefaultLibPath, "lib" CLANG_LIBDIR_SUFFIX); |
| CmdArgs.push_back(Args.MakeArgString(Twine("-L") + DefaultLibPath)); |
| |
| for (const auto &II : Inputs) { |
| if (II.getType() == types::TY_LLVM_IR || |
| II.getType() == types::TY_LTO_IR || |
| II.getType() == types::TY_LTO_BC || |
| II.getType() == types::TY_LLVM_BC) { |
| C.getDriver().Diag(diag::err_drv_no_linker_llvm_support) |
| << getToolChain().getTripleString(); |
| continue; |
| } |
| |
| // Currently, we only pass the input files to the linker, we do not pass |
| // any libraries that may be valid only for the host. |
| if (!II.isFilename()) |
| continue; |
| |
| const char *CubinF = C.addTempFile( |
| C.getArgs().MakeArgString(getToolChain().getInputFilename(II))); |
| |
| CmdArgs.push_back(CubinF); |
| } |
| |
| AddStaticDeviceLibsLinking(C, *this, JA, Inputs, Args, CmdArgs, "nvptx", GPUArch, |
| false, false); |
| |
| // Find nvlink and pass it as "--nvlink-path=" argument of |
| // clang-nvlink-wrapper. |
| CmdArgs.push_back(Args.MakeArgString( |
| Twine("--nvlink-path=" + getToolChain().GetProgramPath("nvlink")))); |
| |
| const char *Exec = |
| Args.MakeArgString(getToolChain().GetProgramPath("clang-nvlink-wrapper")); |
| C.addCommand(std::make_unique<Command>( |
| JA, *this, |
| ResponseFileSupport{ResponseFileSupport::RF_Full, llvm::sys::WEM_UTF8, |
| "--options-file"}, |
| Exec, CmdArgs, Inputs, Output)); |
| } |
| |
| /// CUDA toolchain. Our assembler is ptxas, and our "linker" is fatbinary, |
| /// which isn't properly a linker but nonetheless performs the step of stitching |
| /// together object files from the assembler into a single blob. |
| |
| CudaToolChain::CudaToolChain(const Driver &D, const llvm::Triple &Triple, |
| const ToolChain &HostTC, const ArgList &Args, |
| const Action::OffloadKind OK) |
| : ToolChain(D, Triple, Args), HostTC(HostTC), |
| CudaInstallation(D, HostTC.getTriple(), Args), OK(OK) { |
| if (CudaInstallation.isValid()) { |
| CudaInstallation.WarnIfUnsupportedVersion(); |
| getProgramPaths().push_back(std::string(CudaInstallation.getBinPath())); |
| } |
| // Lookup binaries into the driver directory, this is used to |
| // discover the clang-offload-bundler executable. |
| getProgramPaths().push_back(getDriver().Dir); |
| } |
| |
| std::string CudaToolChain::getInputFilename(const InputInfo &Input) const { |
| // Only object files are changed, for example assembly files keep their .s |
| // extensions. CUDA also continues to use .o as they don't use nvlink but |
| // fatbinary. |
| if (!(OK == Action::OFK_OpenMP && Input.getType() == types::TY_Object)) |
| return ToolChain::getInputFilename(Input); |
| |
| // Replace extension for object files with cubin because nvlink relies on |
| // these particular file names. |
| SmallString<256> Filename(ToolChain::getInputFilename(Input)); |
| llvm::sys::path::replace_extension(Filename, "cubin"); |
| return std::string(Filename.str()); |
| } |
| |
| void CudaToolChain::addClangTargetOptions( |
| const llvm::opt::ArgList &DriverArgs, |
| llvm::opt::ArgStringList &CC1Args, |
| Action::OffloadKind DeviceOffloadingKind) const { |
| HostTC.addClangTargetOptions(DriverArgs, CC1Args, DeviceOffloadingKind); |
| |
| StringRef GpuArch = DriverArgs.getLastArgValue(options::OPT_march_EQ); |
| assert(!GpuArch.empty() && "Must have an explicit GPU arch."); |
| assert((DeviceOffloadingKind == Action::OFK_OpenMP || |
| DeviceOffloadingKind == Action::OFK_Cuda) && |
| "Only OpenMP or CUDA offloading kinds are supported for NVIDIA GPUs."); |
| |
| if (DeviceOffloadingKind == Action::OFK_Cuda) { |
| CC1Args.append( |
| {"-fcuda-is-device", "-mllvm", "-enable-memcpyopt-without-libcalls"}); |
| |
| if (DriverArgs.hasFlag(options::OPT_fcuda_approx_transcendentals, |
| options::OPT_fno_cuda_approx_transcendentals, false)) |
| CC1Args.push_back("-fcuda-approx-transcendentals"); |
| } |
| |
| if (DriverArgs.hasArg(options::OPT_nogpulib)) |
| return; |
| |
| if (DeviceOffloadingKind == Action::OFK_OpenMP && |
| DriverArgs.hasArg(options::OPT_S)) |
| return; |
| |
| std::string LibDeviceFile = CudaInstallation.getLibDeviceFile(GpuArch); |
| if (LibDeviceFile.empty()) { |
| getDriver().Diag(diag::err_drv_no_cuda_libdevice) << GpuArch; |
| return; |
| } |
| |
| CC1Args.push_back("-mlink-builtin-bitcode"); |
| CC1Args.push_back(DriverArgs.MakeArgString(LibDeviceFile)); |
| |
| clang::CudaVersion CudaInstallationVersion = CudaInstallation.version(); |
| |
| // New CUDA versions often introduce new instructions that are only supported |
| // by new PTX version, so we need to raise PTX level to enable them in NVPTX |
| // back-end. |
| const char *PtxFeature = nullptr; |
| switch (CudaInstallationVersion) { |
| #define CASE_CUDA_VERSION(CUDA_VER, PTX_VER) \ |
| case CudaVersion::CUDA_##CUDA_VER: \ |
| PtxFeature = "+ptx" #PTX_VER; \ |
| break; |
| CASE_CUDA_VERSION(115, 75); |
| CASE_CUDA_VERSION(114, 74); |
| CASE_CUDA_VERSION(113, 73); |
| CASE_CUDA_VERSION(112, 72); |
| CASE_CUDA_VERSION(111, 71); |
| CASE_CUDA_VERSION(110, 70); |
| CASE_CUDA_VERSION(102, 65); |
| CASE_CUDA_VERSION(101, 64); |
| CASE_CUDA_VERSION(100, 63); |
| CASE_CUDA_VERSION(92, 61); |
| CASE_CUDA_VERSION(91, 61); |
| CASE_CUDA_VERSION(90, 60); |
| #undef CASE_CUDA_VERSION |
| default: |
| PtxFeature = "+ptx42"; |
| } |
| CC1Args.append({"-target-feature", PtxFeature}); |
| if (DriverArgs.hasFlag(options::OPT_fcuda_short_ptr, |
| options::OPT_fno_cuda_short_ptr, false)) |
| CC1Args.append({"-mllvm", "--nvptx-short-ptr"}); |
| |
| if (CudaInstallationVersion >= CudaVersion::UNKNOWN) |
| CC1Args.push_back( |
| DriverArgs.MakeArgString(Twine("-target-sdk-version=") + |
| CudaVersionToString(CudaInstallationVersion))); |
| |
| if (DeviceOffloadingKind == Action::OFK_OpenMP) { |
| if (CudaInstallationVersion < CudaVersion::CUDA_92) { |
| getDriver().Diag( |
| diag::err_drv_omp_offload_target_cuda_version_not_support) |
| << CudaVersionToString(CudaInstallationVersion); |
| return; |
| } |
| |
| std::string BitcodeSuffix; |
| if (DriverArgs.hasFlag(options::OPT_fopenmp_target_new_runtime, |
| options::OPT_fno_openmp_target_new_runtime, false)) |
| BitcodeSuffix = "new-nvptx-" + GpuArch.str(); |
| else |
| BitcodeSuffix = "nvptx-" + GpuArch.str(); |
| |
| addOpenMPDeviceRTL(getDriver(), DriverArgs, CC1Args, BitcodeSuffix, |
| getTriple()); |
| AddStaticDeviceLibsPostLinking(getDriver(), DriverArgs, CC1Args, "nvptx", GpuArch, |
| /* bitcode SDL?*/ true, /* PostClang Link? */ true); |
| } |
| } |
| |
| llvm::DenormalMode CudaToolChain::getDefaultDenormalModeForType( |
| const llvm::opt::ArgList &DriverArgs, const JobAction &JA, |
| const llvm::fltSemantics *FPType) const { |
| if (JA.getOffloadingDeviceKind() == Action::OFK_Cuda) { |
| if (FPType && FPType == &llvm::APFloat::IEEEsingle() && |
| DriverArgs.hasFlag(options::OPT_fgpu_flush_denormals_to_zero, |
| options::OPT_fno_gpu_flush_denormals_to_zero, false)) |
| return llvm::DenormalMode::getPreserveSign(); |
| } |
| |
| assert(JA.getOffloadingDeviceKind() != Action::OFK_Host); |
| return llvm::DenormalMode::getIEEE(); |
| } |
| |
| bool CudaToolChain::supportsDebugInfoOption(const llvm::opt::Arg *A) const { |
| const Option &O = A->getOption(); |
| return (O.matches(options::OPT_gN_Group) && |
| !O.matches(options::OPT_gmodules)) || |
| O.matches(options::OPT_g_Flag) || |
| O.matches(options::OPT_ggdbN_Group) || O.matches(options::OPT_ggdb) || |
| O.matches(options::OPT_gdwarf) || O.matches(options::OPT_gdwarf_2) || |
| O.matches(options::OPT_gdwarf_3) || O.matches(options::OPT_gdwarf_4) || |
| O.matches(options::OPT_gdwarf_5) || |
| O.matches(options::OPT_gcolumn_info); |
| } |
| |
| void CudaToolChain::adjustDebugInfoKind( |
| codegenoptions::DebugInfoKind &DebugInfoKind, const ArgList &Args) const { |
| switch (mustEmitDebugInfo(Args)) { |
| case DisableDebugInfo: |
| DebugInfoKind = codegenoptions::NoDebugInfo; |
| break; |
| case DebugDirectivesOnly: |
| DebugInfoKind = codegenoptions::DebugDirectivesOnly; |
| break; |
| case EmitSameDebugInfoAsHost: |
| // Use same debug info level as the host. |
| break; |
| } |
| } |
| |
| void CudaToolChain::AddCudaIncludeArgs(const ArgList &DriverArgs, |
| ArgStringList &CC1Args) const { |
| // Check our CUDA version if we're going to include the CUDA headers. |
| if (!DriverArgs.hasArg(options::OPT_nogpuinc) && |
| !DriverArgs.hasArg(options::OPT_no_cuda_version_check)) { |
| StringRef Arch = DriverArgs.getLastArgValue(options::OPT_march_EQ); |
| assert(!Arch.empty() && "Must have an explicit GPU arch."); |
| CudaInstallation.CheckCudaVersionSupportsArch(StringToCudaArch(Arch)); |
| } |
| CudaInstallation.AddCudaIncludeArgs(DriverArgs, CC1Args); |
| } |
| |
| llvm::opt::DerivedArgList * |
| CudaToolChain::TranslateArgs(const llvm::opt::DerivedArgList &Args, |
| StringRef BoundArch, |
| Action::OffloadKind DeviceOffloadKind) const { |
| DerivedArgList *DAL = |
| HostTC.TranslateArgs(Args, BoundArch, DeviceOffloadKind); |
| if (!DAL) |
| DAL = new DerivedArgList(Args.getBaseArgs()); |
| |
| const OptTable &Opts = getDriver().getOpts(); |
| |
| // For OpenMP device offloading, append derived arguments. Make sure |
| // flags are not duplicated. |
| // Also append the compute capability. |
| if (DeviceOffloadKind == Action::OFK_OpenMP) { |
| for (Arg *A : Args) |
| if (!llvm::is_contained(*DAL, A)) |
| DAL->append(A); |
| |
| StringRef Arch = DAL->getLastArgValue(options::OPT_march_EQ); |
| if (Arch.empty()) |
| DAL->AddJoinedArg(nullptr, Opts.getOption(options::OPT_march_EQ), |
| CLANG_OPENMP_NVPTX_DEFAULT_ARCH); |
| |
| return DAL; |
| } |
| |
| for (Arg *A : Args) { |
| DAL->append(A); |
| } |
| |
| if (!BoundArch.empty()) { |
| DAL->eraseArg(options::OPT_march_EQ); |
| DAL->AddJoinedArg(nullptr, Opts.getOption(options::OPT_march_EQ), BoundArch); |
| } |
| return DAL; |
| } |
| |
| Tool *CudaToolChain::buildAssembler() const { |
| return new tools::NVPTX::Assembler(*this); |
| } |
| |
| Tool *CudaToolChain::buildLinker() const { |
| if (OK == Action::OFK_OpenMP) |
| return new tools::NVPTX::OpenMPLinker(*this); |
| return new tools::NVPTX::Linker(*this); |
| } |
| |
| void CudaToolChain::addClangWarningOptions(ArgStringList &CC1Args) const { |
| HostTC.addClangWarningOptions(CC1Args); |
| } |
| |
| ToolChain::CXXStdlibType |
| CudaToolChain::GetCXXStdlibType(const ArgList &Args) const { |
| return HostTC.GetCXXStdlibType(Args); |
| } |
| |
| void CudaToolChain::AddClangSystemIncludeArgs(const ArgList &DriverArgs, |
| ArgStringList &CC1Args) const { |
| HostTC.AddClangSystemIncludeArgs(DriverArgs, CC1Args); |
| |
| if (!DriverArgs.hasArg(options::OPT_nogpuinc) && CudaInstallation.isValid()) |
| CC1Args.append( |
| {"-internal-isystem", |
| DriverArgs.MakeArgString(CudaInstallation.getIncludePath())}); |
| } |
| |
| void CudaToolChain::AddClangCXXStdlibIncludeArgs(const ArgList &Args, |
| ArgStringList &CC1Args) const { |
| HostTC.AddClangCXXStdlibIncludeArgs(Args, CC1Args); |
| } |
| |
| void CudaToolChain::AddIAMCUIncludeArgs(const ArgList &Args, |
| ArgStringList &CC1Args) const { |
| HostTC.AddIAMCUIncludeArgs(Args, CC1Args); |
| } |
| |
| SanitizerMask CudaToolChain::getSupportedSanitizers() const { |
| // The CudaToolChain only supports sanitizers in the sense that it allows |
| // sanitizer arguments on the command line if they are supported by the host |
| // toolchain. The CudaToolChain will actually ignore any command line |
| // arguments for any of these "supported" sanitizers. That means that no |
| // sanitization of device code is actually supported at this time. |
| // |
| // This behavior is necessary because the host and device toolchains |
| // invocations often share the command line, so the device toolchain must |
| // tolerate flags meant only for the host toolchain. |
| return HostTC.getSupportedSanitizers(); |
| } |
| |
| VersionTuple CudaToolChain::computeMSVCVersion(const Driver *D, |
| const ArgList &Args) const { |
| return HostTC.computeMSVCVersion(D, Args); |
| } |
