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+//===--- 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 <system_error>
+
+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<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"};
+
+ 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(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_nogpulib);
+
+ 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<std::unique_ptr<llvm::MemoryBuffer>> 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<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, 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<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)
+ ? 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(std::make_unique<Command>(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<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));
+
+ // 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);
+ }
+
+ const char *Exec =
+ Args.MakeArgString(getToolChain().GetProgramPath("nvlink"));
+ C.addCommand(std::make_unique<Command>(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_nogpulib))
+ 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<StringRef, 8> 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<std::string> LibPath =
+ llvm::sys::Process::GetEnv("LIBRARY_PATH");
+ if (LibPath) {
+ SmallVector<StringRef, 8> 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<Arg> 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);
+}
generated by cgit v1.2.3 (git 2.25.1) at 2025-10-30 23:22:32 +0000