//===--- 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 "InputInfo.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/Options.h" #include "llvm/Option/ArgList.h" #include "llvm/Support/FileSystem.h" #include "llvm/Support/Path.h" #include "llvm/Support/Process.h" #include "llvm/Support/Program.h" #include "llvm/Support/VirtualFileSystem.h" #include using namespace clang::driver; using namespace clang::driver::toolchains; using namespace clang::driver::tools; using namespace clang; using namespace llvm::opt; // Parses the contents of version.txt in an CUDA installation. It should // contain one line of the from e.g. "CUDA Version 7.5.2". static CudaVersion ParseCudaVersionFile(llvm::StringRef V) { if (!V.startswith("CUDA Version ")) return CudaVersion::UNKNOWN; V = V.substr(strlen("CUDA Version ")); int Major = -1, Minor = -1; auto First = V.split('.'); auto Second = First.second.split('.'); if (First.first.getAsInteger(10, Major) || Second.first.getAsInteger(10, Minor)) return CudaVersion::UNKNOWN; if (Major == 7 && Minor == 0) { // This doesn't appear to ever happen -- version.txt doesn't exist in the // CUDA 7 installs I've seen. But no harm in checking. return CudaVersion::CUDA_70; } if (Major == 7 && Minor == 5) return CudaVersion::CUDA_75; if (Major == 8 && Minor == 0) return CudaVersion::CUDA_80; if (Major == 9 && Minor == 0) return CudaVersion::CUDA_90; if (Major == 9 && Minor == 1) return CudaVersion::CUDA_91; if (Major == 9 && Minor == 2) return CudaVersion::CUDA_92; if (Major == 10 && Minor == 0) return CudaVersion::CUDA_100; if (Major == 10 && Minor == 1) return CudaVersion::CUDA_101; return CudaVersion::UNKNOWN; } 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 Candidates; // In decreasing order so we prefer newer versions to older versions. std::initializer_list Versions = {"8.0", "7.5", "7.0"}; 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 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(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); if (Distro(D.getVFS()).IsDebian() || Distro(D.getVFS()).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_nocudalib); for (const auto &Candidate : Candidates) { InstallPath = Candidate.Path; if (InstallPath.empty() || !D.getVFS().exists(InstallPath)) continue; BinPath = InstallPath + "/bin"; IncludePath = InstallPath + "/include"; LibDevicePath = InstallPath + "/nvvm/libdevice"; auto &FS = D.getVFS(); 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; llvm::ErrorOr> VersionFile = FS.getBufferForFile(InstallPath + "/version.txt"); if (!VersionFile) { // CUDA 7.0 doesn't have a version.txt, so guess that's our version if // version.txt isn't present. Version = CudaVersion::CUDA_70; } else { Version = ParseCudaVersionFile((*VersionFile)->getBuffer()); } 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 (const char *GpuArchName : {"sm_30", "sm_32", "sm_35", "sm_37", "sm_50", "sm_52", "sm_53", "sm_60", "sm_61", "sm_62", "sm_70", "sm_72", "sm_75"}) { const CudaArch GpuArch = StringToCudaArch(GpuArchName); if (Version >= MinVersionForCudaArch(GpuArch) && Version <= MaxVersionForCudaArch(GpuArch)) LibDeviceMap[GpuArchName] = FilePath; } } } else { std::error_code EC; for (llvm::sys::fs::directory_iterator LI(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"] = FilePath; LibDeviceMap["sm_21"] = FilePath; LibDeviceMap["sm_32"] = FilePath; } else if (GpuArch == "compute_30") { LibDeviceMap["sm_30"] = FilePath; if (Version < CudaVersion::CUDA_80) { LibDeviceMap["sm_50"] = FilePath; LibDeviceMap["sm_52"] = FilePath; LibDeviceMap["sm_53"] = FilePath; } LibDeviceMap["sm_60"] = FilePath; LibDeviceMap["sm_61"] = FilePath; LibDeviceMap["sm_62"] = FilePath; } else if (GpuArch == "compute_35") { LibDeviceMap["sm_35"] = FilePath; LibDeviceMap["sm_37"] = FilePath; } else if (GpuArch == "compute_50") { if (Version >= CudaVersion::CUDA_80) { LibDeviceMap["sm_50"] = FilePath; LibDeviceMap["sm_52"] = FilePath; LibDeviceMap["sm_53"] = 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_nocudainc)) return; if (!isValid()) { D.Diag(diag::err_drv_no_cuda_installation); return; } CC1Args.push_back("-internal-isystem"); CC1Args.push_back(DriverArgs.MakeArgString(getIncludePath())); 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.count(Arch) > 0) return; auto MinVersion = MinVersionForCudaArch(Arch); auto MaxVersion = MaxVersionForCudaArch(Arch); if (Version < MinVersion || Version > MaxVersion) { ArchsWithBadVersion.insert(Arch); 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 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(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(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(llvm::make_unique(JA, *this, Exec, CmdArgs, Inputs)); } 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(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) ? CudaVirtualArchToString(VirtualArchForCudaArch(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(llvm::make_unique(JA, *this, Exec, CmdArgs, Inputs)); } 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(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)); // Assume that the directory specified with --libomptarget_nvptx_path // contains the static library libomptarget-nvptx.a. if (const Arg *A = Args.getLastArg(options::OPT_libomptarget_nvptx_path_EQ)) CmdArgs.push_back(Args.MakeArgString(Twine("-L") + A->getValue())); // 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)); // Add linking against library implementing OpenMP calls on NVPTX target. CmdArgs.push_back("-lomptarget-nvptx"); 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); } AddOpenMPLinkerScript(getToolChain(), C, Output, Inputs, Args, CmdArgs, JA); const char *Exec = Args.MakeArgString(getToolChain().GetProgramPath("nvlink")); C.addCommand(llvm::make_unique(JA, *this, Exec, CmdArgs, Inputs)); } /// 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()) getProgramPaths().push_back(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 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.push_back("-fcuda-is-device"); if (DriverArgs.hasFlag(options::OPT_fcuda_flush_denormals_to_zero, options::OPT_fno_cuda_flush_denormals_to_zero, false)) CC1Args.push_back("-fcuda-flush-denormals-to-zero"); if (DriverArgs.hasFlag(options::OPT_fcuda_approx_transcendentals, options::OPT_fno_cuda_approx_transcendentals, false)) CC1Args.push_back("-fcuda-approx-transcendentals"); if (DriverArgs.hasFlag(options::OPT_fgpu_rdc, options::OPT_fno_gpu_rdc, false)) CC1Args.push_back("-fgpu-rdc"); } if (DriverArgs.hasArg(options::OPT_nocudalib)) return; std::string LibDeviceFile = CudaInstallation.getLibDeviceFile(GpuArch); if (LibDeviceFile.empty()) { if (DeviceOffloadingKind == Action::OFK_OpenMP && DriverArgs.hasArg(options::OPT_S)) return; getDriver().Diag(diag::err_drv_no_cuda_libdevice) << GpuArch; return; } CC1Args.push_back("-mlink-builtin-bitcode"); CC1Args.push_back(DriverArgs.MakeArgString(LibDeviceFile)); // 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(CudaInstallation.version()) { case CudaVersion::CUDA_101: PtxFeature = "+ptx64"; break; case CudaVersion::CUDA_100: PtxFeature = "+ptx63"; break; case CudaVersion::CUDA_92: PtxFeature = "+ptx61"; break; case CudaVersion::CUDA_91: PtxFeature = "+ptx61"; break; case CudaVersion::CUDA_90: PtxFeature = "+ptx60"; break; 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 (CudaInstallation.version() >= CudaVersion::UNKNOWN) CC1Args.push_back(DriverArgs.MakeArgString( Twine("-target-sdk-version=") + CudaVersionToString(CudaInstallation.version()))); if (DeviceOffloadingKind == Action::OFK_OpenMP) { SmallVector LibraryPaths; if (const Arg *A = DriverArgs.getLastArg(options::OPT_libomptarget_nvptx_path_EQ)) LibraryPaths.push_back(A->getValue()); // Add user defined library paths from LIBRARY_PATH. llvm::Optional LibPath = llvm::sys::Process::GetEnv("LIBRARY_PATH"); if (LibPath) { SmallVector Frags; const char EnvPathSeparatorStr[] = {llvm::sys::EnvPathSeparator, '\0'}; llvm::SplitString(*LibPath, Frags, EnvPathSeparatorStr); for (StringRef Path : Frags) LibraryPaths.emplace_back(Path.trim()); } // Add path to lib / lib64 folder. SmallString<256> DefaultLibPath = llvm::sys::path::parent_path(getDriver().Dir); llvm::sys::path::append(DefaultLibPath, Twine("lib") + CLANG_LIBDIR_SUFFIX); LibraryPaths.emplace_back(DefaultLibPath.c_str()); std::string LibOmpTargetName = "libomptarget-nvptx-" + GpuArch.str() + ".bc"; bool FoundBCLibrary = false; for (StringRef LibraryPath : LibraryPaths) { SmallString<128> LibOmpTargetFile(LibraryPath); llvm::sys::path::append(LibOmpTargetFile, LibOmpTargetName); if (llvm::sys::fs::exists(LibOmpTargetFile)) { CC1Args.push_back("-mlink-builtin-bitcode"); CC1Args.push_back(DriverArgs.MakeArgString(LibOmpTargetFile)); FoundBCLibrary = true; break; } } if (!FoundBCLibrary) getDriver().Diag(diag::warn_drv_omp_offload_target_missingbcruntime) << LibOmpTargetName; } } 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_nocudainc) && !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) { bool IsDuplicate = false; for (Arg *DALArg : *DAL) { if (A == DALArg) { IsDuplicate = true; break; } } if (!IsDuplicate) 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) { if (A->getOption().matches(options::OPT_Xarch__)) { // Skip this argument unless the architecture matches BoundArch if (BoundArch.empty() || A->getValue(0) != BoundArch) continue; unsigned Index = Args.getBaseArgs().MakeIndex(A->getValue(1)); unsigned Prev = Index; std::unique_ptr XarchArg(Opts.ParseOneArg(Args, Index)); // If the argument parsing failed or more than one argument was // consumed, the -Xarch_ argument's parameter tried to consume // extra arguments. Emit an error and ignore. // // We also want to disallow any options which would alter the // driver behavior; that isn't going to work in our model. We // use isDriverOption() as an approximation, although things // like -O4 are going to slip through. if (!XarchArg || Index > Prev + 1) { getDriver().Diag(diag::err_drv_invalid_Xarch_argument_with_args) << A->getAsString(Args); continue; } else if (XarchArg->getOption().hasFlag(options::DriverOption)) { getDriver().Diag(diag::err_drv_invalid_Xarch_argument_isdriver) << A->getAsString(Args); continue; } XarchArg->setBaseArg(A); A = XarchArg.release(); DAL->AddSynthesizedArg(A); } 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); } 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); }