1 //===--- Cuda.cpp - Cuda Tool and ToolChain Implementations -----*- C++ -*-===//
2 //
3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
4 // See https://llvm.org/LICENSE.txt for license information.
5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
6 //
7 //===----------------------------------------------------------------------===//
8 
9 #include "Cuda.h"
10 #include "CommonArgs.h"
11 #include "clang/Basic/Cuda.h"
12 #include "clang/Config/config.h"
13 #include "clang/Driver/Compilation.h"
14 #include "clang/Driver/Distro.h"
15 #include "clang/Driver/Driver.h"
16 #include "clang/Driver/DriverDiagnostic.h"
17 #include "clang/Driver/InputInfo.h"
18 #include "clang/Driver/Options.h"
19 #include "llvm/ADT/StringExtras.h"
20 #include "llvm/Option/ArgList.h"
21 #include "llvm/Support/FileSystem.h"
22 #include "llvm/Support/FormatAdapters.h"
23 #include "llvm/Support/FormatVariadic.h"
24 #include "llvm/Support/Path.h"
25 #include "llvm/Support/Process.h"
26 #include "llvm/Support/Program.h"
27 #include "llvm/Support/VirtualFileSystem.h"
28 #include "llvm/TargetParser/Host.h"
29 #include "llvm/TargetParser/TargetParser.h"
30 #include <system_error>
31 
32 using namespace clang::driver;
33 using namespace clang::driver::toolchains;
34 using namespace clang::driver::tools;
35 using namespace clang;
36 using namespace llvm::opt;
37 
38 namespace {
39 
40 CudaVersion getCudaVersion(uint32_t raw_version) {
41   if (raw_version < 7050)
42     return CudaVersion::CUDA_70;
43   if (raw_version < 8000)
44     return CudaVersion::CUDA_75;
45   if (raw_version < 9000)
46     return CudaVersion::CUDA_80;
47   if (raw_version < 9010)
48     return CudaVersion::CUDA_90;
49   if (raw_version < 9020)
50     return CudaVersion::CUDA_91;
51   if (raw_version < 10000)
52     return CudaVersion::CUDA_92;
53   if (raw_version < 10010)
54     return CudaVersion::CUDA_100;
55   if (raw_version < 10020)
56     return CudaVersion::CUDA_101;
57   if (raw_version < 11000)
58     return CudaVersion::CUDA_102;
59   if (raw_version < 11010)
60     return CudaVersion::CUDA_110;
61   if (raw_version < 11020)
62     return CudaVersion::CUDA_111;
63   if (raw_version < 11030)
64     return CudaVersion::CUDA_112;
65   if (raw_version < 11040)
66     return CudaVersion::CUDA_113;
67   if (raw_version < 11050)
68     return CudaVersion::CUDA_114;
69   if (raw_version < 11060)
70     return CudaVersion::CUDA_115;
71   if (raw_version < 11070)
72     return CudaVersion::CUDA_116;
73   if (raw_version < 11080)
74     return CudaVersion::CUDA_117;
75   if (raw_version < 11090)
76     return CudaVersion::CUDA_118;
77   if (raw_version < 12010)
78     return CudaVersion::CUDA_120;
79   if (raw_version < 12020)
80     return CudaVersion::CUDA_121;
81   if (raw_version < 12030)
82     return CudaVersion::CUDA_122;
83   if (raw_version < 12040)
84     return CudaVersion::CUDA_123;
85   return CudaVersion::NEW;
86 }
87 
88 CudaVersion parseCudaHFile(llvm::StringRef Input) {
89   // Helper lambda which skips the words if the line starts with them or returns
90   // std::nullopt otherwise.
91   auto StartsWithWords =
92       [](llvm::StringRef Line,
93          const SmallVector<StringRef, 3> words) -> std::optional<StringRef> {
94     for (StringRef word : words) {
95       if (!Line.consume_front(word))
96         return {};
97       Line = Line.ltrim();
98     }
99     return Line;
100   };
101 
102   Input = Input.ltrim();
103   while (!Input.empty()) {
104     if (auto Line =
105             StartsWithWords(Input.ltrim(), {"#", "define", "CUDA_VERSION"})) {
106       uint32_t RawVersion;
107       Line->consumeInteger(10, RawVersion);
108       return getCudaVersion(RawVersion);
109     }
110     // Find next non-empty line.
111     Input = Input.drop_front(Input.find_first_of("\n\r")).ltrim();
112   }
113   return CudaVersion::UNKNOWN;
114 }
115 } // namespace
116 
117 void CudaInstallationDetector::WarnIfUnsupportedVersion() {
118   if (Version > CudaVersion::PARTIALLY_SUPPORTED) {
119     std::string VersionString = CudaVersionToString(Version);
120     if (!VersionString.empty())
121       VersionString.insert(0, " ");
122     D.Diag(diag::warn_drv_new_cuda_version)
123         << VersionString
124         << (CudaVersion::PARTIALLY_SUPPORTED != CudaVersion::FULLY_SUPPORTED)
125         << CudaVersionToString(CudaVersion::PARTIALLY_SUPPORTED);
126   } else if (Version > CudaVersion::FULLY_SUPPORTED)
127     D.Diag(diag::warn_drv_partially_supported_cuda_version)
128         << CudaVersionToString(Version);
129 }
130 
131 CudaInstallationDetector::CudaInstallationDetector(
132     const Driver &D, const llvm::Triple &HostTriple,
133     const llvm::opt::ArgList &Args)
134     : D(D) {
135   struct Candidate {
136     std::string Path;
137     bool StrictChecking;
138 
139     Candidate(std::string Path, bool StrictChecking = false)
140         : Path(Path), StrictChecking(StrictChecking) {}
141   };
142   SmallVector<Candidate, 4> Candidates;
143 
144   // In decreasing order so we prefer newer versions to older versions.
145   std::initializer_list<const char *> Versions = {"8.0", "7.5", "7.0"};
146   auto &FS = D.getVFS();
147 
148   if (Args.hasArg(clang::driver::options::OPT_cuda_path_EQ)) {
149     Candidates.emplace_back(
150         Args.getLastArgValue(clang::driver::options::OPT_cuda_path_EQ).str());
151   } else if (HostTriple.isOSWindows()) {
152     for (const char *Ver : Versions)
153       Candidates.emplace_back(
154           D.SysRoot + "/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v" +
155           Ver);
156   } else {
157     if (!Args.hasArg(clang::driver::options::OPT_cuda_path_ignore_env)) {
158       // Try to find ptxas binary. If the executable is located in a directory
159       // called 'bin/', its parent directory might be a good guess for a valid
160       // CUDA installation.
161       // However, some distributions might installs 'ptxas' to /usr/bin. In that
162       // case the candidate would be '/usr' which passes the following checks
163       // because '/usr/include' exists as well. To avoid this case, we always
164       // check for the directory potentially containing files for libdevice,
165       // even if the user passes -nocudalib.
166       if (llvm::ErrorOr<std::string> ptxas =
167               llvm::sys::findProgramByName("ptxas")) {
168         SmallString<256> ptxasAbsolutePath;
169         llvm::sys::fs::real_path(*ptxas, ptxasAbsolutePath);
170 
171         StringRef ptxasDir = llvm::sys::path::parent_path(ptxasAbsolutePath);
172         if (llvm::sys::path::filename(ptxasDir) == "bin")
173           Candidates.emplace_back(
174               std::string(llvm::sys::path::parent_path(ptxasDir)),
175               /*StrictChecking=*/true);
176       }
177     }
178 
179     Candidates.emplace_back(D.SysRoot + "/usr/local/cuda");
180     for (const char *Ver : Versions)
181       Candidates.emplace_back(D.SysRoot + "/usr/local/cuda-" + Ver);
182 
183     Distro Dist(FS, llvm::Triple(llvm::sys::getProcessTriple()));
184     if (Dist.IsDebian() || Dist.IsUbuntu())
185       // Special case for Debian to have nvidia-cuda-toolkit work
186       // out of the box. More info on http://bugs.debian.org/882505
187       Candidates.emplace_back(D.SysRoot + "/usr/lib/cuda");
188   }
189 
190   bool NoCudaLib = Args.hasArg(options::OPT_nogpulib);
191 
192   for (const auto &Candidate : Candidates) {
193     InstallPath = Candidate.Path;
194     if (InstallPath.empty() || !FS.exists(InstallPath))
195       continue;
196 
197     BinPath = InstallPath + "/bin";
198     IncludePath = InstallPath + "/include";
199     LibDevicePath = InstallPath + "/nvvm/libdevice";
200 
201     if (!(FS.exists(IncludePath) && FS.exists(BinPath)))
202       continue;
203     bool CheckLibDevice = (!NoCudaLib || Candidate.StrictChecking);
204     if (CheckLibDevice && !FS.exists(LibDevicePath))
205       continue;
206 
207     Version = CudaVersion::UNKNOWN;
208     if (auto CudaHFile = FS.getBufferForFile(InstallPath + "/include/cuda.h"))
209       Version = parseCudaHFile((*CudaHFile)->getBuffer());
210     // As the last resort, make an educated guess between CUDA-7.0, which had
211     // old-style libdevice bitcode, and an unknown recent CUDA version.
212     if (Version == CudaVersion::UNKNOWN) {
213       Version = FS.exists(LibDevicePath + "/libdevice.10.bc")
214                     ? CudaVersion::NEW
215                     : CudaVersion::CUDA_70;
216     }
217 
218     if (Version >= CudaVersion::CUDA_90) {
219       // CUDA-9+ uses single libdevice file for all GPU variants.
220       std::string FilePath = LibDevicePath + "/libdevice.10.bc";
221       if (FS.exists(FilePath)) {
222         for (int Arch = (int)CudaArch::SM_30, E = (int)CudaArch::LAST; Arch < E;
223              ++Arch) {
224           CudaArch GpuArch = static_cast<CudaArch>(Arch);
225           if (!IsNVIDIAGpuArch(GpuArch))
226             continue;
227           std::string GpuArchName(CudaArchToString(GpuArch));
228           LibDeviceMap[GpuArchName] = FilePath;
229         }
230       }
231     } else {
232       std::error_code EC;
233       for (llvm::vfs::directory_iterator LI = FS.dir_begin(LibDevicePath, EC),
234                                          LE;
235            !EC && LI != LE; LI = LI.increment(EC)) {
236         StringRef FilePath = LI->path();
237         StringRef FileName = llvm::sys::path::filename(FilePath);
238         // Process all bitcode filenames that look like
239         // libdevice.compute_XX.YY.bc
240         const StringRef LibDeviceName = "libdevice.";
241         if (!(FileName.starts_with(LibDeviceName) && FileName.ends_with(".bc")))
242           continue;
243         StringRef GpuArch = FileName.slice(
244             LibDeviceName.size(), FileName.find('.', LibDeviceName.size()));
245         LibDeviceMap[GpuArch] = FilePath.str();
246         // Insert map entries for specific devices with this compute
247         // capability. NVCC's choice of the libdevice library version is
248         // rather peculiar and depends on the CUDA version.
249         if (GpuArch == "compute_20") {
250           LibDeviceMap["sm_20"] = std::string(FilePath);
251           LibDeviceMap["sm_21"] = std::string(FilePath);
252           LibDeviceMap["sm_32"] = std::string(FilePath);
253         } else if (GpuArch == "compute_30") {
254           LibDeviceMap["sm_30"] = std::string(FilePath);
255           if (Version < CudaVersion::CUDA_80) {
256             LibDeviceMap["sm_50"] = std::string(FilePath);
257             LibDeviceMap["sm_52"] = std::string(FilePath);
258             LibDeviceMap["sm_53"] = std::string(FilePath);
259           }
260           LibDeviceMap["sm_60"] = std::string(FilePath);
261           LibDeviceMap["sm_61"] = std::string(FilePath);
262           LibDeviceMap["sm_62"] = std::string(FilePath);
263         } else if (GpuArch == "compute_35") {
264           LibDeviceMap["sm_35"] = std::string(FilePath);
265           LibDeviceMap["sm_37"] = std::string(FilePath);
266         } else if (GpuArch == "compute_50") {
267           if (Version >= CudaVersion::CUDA_80) {
268             LibDeviceMap["sm_50"] = std::string(FilePath);
269             LibDeviceMap["sm_52"] = std::string(FilePath);
270             LibDeviceMap["sm_53"] = std::string(FilePath);
271           }
272         }
273       }
274     }
275 
276     // Check that we have found at least one libdevice that we can link in if
277     // -nocudalib hasn't been specified.
278     if (LibDeviceMap.empty() && !NoCudaLib)
279       continue;
280 
281     IsValid = true;
282     break;
283   }
284 }
285 
286 void CudaInstallationDetector::AddCudaIncludeArgs(
287     const ArgList &DriverArgs, ArgStringList &CC1Args) const {
288   if (!DriverArgs.hasArg(options::OPT_nobuiltininc)) {
289     // Add cuda_wrappers/* to our system include path.  This lets us wrap
290     // standard library headers.
291     SmallString<128> P(D.ResourceDir);
292     llvm::sys::path::append(P, "include");
293     llvm::sys::path::append(P, "cuda_wrappers");
294     CC1Args.push_back("-internal-isystem");
295     CC1Args.push_back(DriverArgs.MakeArgString(P));
296   }
297 
298   if (DriverArgs.hasArg(options::OPT_nogpuinc))
299     return;
300 
301   if (!isValid()) {
302     D.Diag(diag::err_drv_no_cuda_installation);
303     return;
304   }
305 
306   CC1Args.push_back("-include");
307   CC1Args.push_back("__clang_cuda_runtime_wrapper.h");
308 }
309 
310 void CudaInstallationDetector::CheckCudaVersionSupportsArch(
311     CudaArch Arch) const {
312   if (Arch == CudaArch::UNKNOWN || Version == CudaVersion::UNKNOWN ||
313       ArchsWithBadVersion[(int)Arch])
314     return;
315 
316   auto MinVersion = MinVersionForCudaArch(Arch);
317   auto MaxVersion = MaxVersionForCudaArch(Arch);
318   if (Version < MinVersion || Version > MaxVersion) {
319     ArchsWithBadVersion[(int)Arch] = true;
320     D.Diag(diag::err_drv_cuda_version_unsupported)
321         << CudaArchToString(Arch) << CudaVersionToString(MinVersion)
322         << CudaVersionToString(MaxVersion) << InstallPath
323         << CudaVersionToString(Version);
324   }
325 }
326 
327 void CudaInstallationDetector::print(raw_ostream &OS) const {
328   if (isValid())
329     OS << "Found CUDA installation: " << InstallPath << ", version "
330        << CudaVersionToString(Version) << "\n";
331 }
332 
333 namespace {
334 /// Debug info level for the NVPTX devices. We may need to emit different debug
335 /// info level for the host and for the device itselfi. This type controls
336 /// emission of the debug info for the devices. It either prohibits disable info
337 /// emission completely, or emits debug directives only, or emits same debug
338 /// info as for the host.
339 enum DeviceDebugInfoLevel {
340   DisableDebugInfo,        /// Do not emit debug info for the devices.
341   DebugDirectivesOnly,     /// Emit only debug directives.
342   EmitSameDebugInfoAsHost, /// Use the same debug info level just like for the
343                            /// host.
344 };
345 } // anonymous namespace
346 
347 /// Define debug info level for the NVPTX devices. If the debug info for both
348 /// the host and device are disabled (-g0/-ggdb0 or no debug options at all). If
349 /// only debug directives are requested for the both host and device
350 /// (-gline-directvies-only), or the debug info only for the device is disabled
351 /// (optimization is on and --cuda-noopt-device-debug was not specified), the
352 /// debug directves only must be emitted for the device. Otherwise, use the same
353 /// debug info level just like for the host (with the limitations of only
354 /// supported DWARF2 standard).
355 static DeviceDebugInfoLevel mustEmitDebugInfo(const ArgList &Args) {
356   const Arg *A = Args.getLastArg(options::OPT_O_Group);
357   bool IsDebugEnabled = !A || A->getOption().matches(options::OPT_O0) ||
358                         Args.hasFlag(options::OPT_cuda_noopt_device_debug,
359                                      options::OPT_no_cuda_noopt_device_debug,
360                                      /*Default=*/false);
361   if (const Arg *A = Args.getLastArg(options::OPT_g_Group)) {
362     const Option &Opt = A->getOption();
363     if (Opt.matches(options::OPT_gN_Group)) {
364       if (Opt.matches(options::OPT_g0) || Opt.matches(options::OPT_ggdb0))
365         return DisableDebugInfo;
366       if (Opt.matches(options::OPT_gline_directives_only))
367         return DebugDirectivesOnly;
368     }
369     return IsDebugEnabled ? EmitSameDebugInfoAsHost : DebugDirectivesOnly;
370   }
371   return willEmitRemarks(Args) ? DebugDirectivesOnly : DisableDebugInfo;
372 }
373 
374 void NVPTX::Assembler::ConstructJob(Compilation &C, const JobAction &JA,
375                                     const InputInfo &Output,
376                                     const InputInfoList &Inputs,
377                                     const ArgList &Args,
378                                     const char *LinkingOutput) const {
379   const auto &TC =
380       static_cast<const toolchains::NVPTXToolChain &>(getToolChain());
381   assert(TC.getTriple().isNVPTX() && "Wrong platform");
382 
383   StringRef GPUArchName;
384   // If this is a CUDA action we need to extract the device architecture
385   // from the Job's associated architecture, otherwise use the -march=arch
386   // option. This option may come from -Xopenmp-target flag or the default
387   // value.
388   if (JA.isDeviceOffloading(Action::OFK_Cuda)) {
389     GPUArchName = JA.getOffloadingArch();
390   } else {
391     GPUArchName = Args.getLastArgValue(options::OPT_march_EQ);
392     assert(!GPUArchName.empty() && "Must have an architecture passed in.");
393   }
394 
395   // Obtain architecture from the action.
396   CudaArch gpu_arch = StringToCudaArch(GPUArchName);
397   assert(gpu_arch != CudaArch::UNKNOWN &&
398          "Device action expected to have an architecture.");
399 
400   // Check that our installation's ptxas supports gpu_arch.
401   if (!Args.hasArg(options::OPT_no_cuda_version_check)) {
402     TC.CudaInstallation.CheckCudaVersionSupportsArch(gpu_arch);
403   }
404 
405   ArgStringList CmdArgs;
406   CmdArgs.push_back(TC.getTriple().isArch64Bit() ? "-m64" : "-m32");
407   DeviceDebugInfoLevel DIKind = mustEmitDebugInfo(Args);
408   if (DIKind == EmitSameDebugInfoAsHost) {
409     // ptxas does not accept -g option if optimization is enabled, so
410     // we ignore the compiler's -O* options if we want debug info.
411     CmdArgs.push_back("-g");
412     CmdArgs.push_back("--dont-merge-basicblocks");
413     CmdArgs.push_back("--return-at-end");
414   } else if (Arg *A = Args.getLastArg(options::OPT_O_Group)) {
415     // Map the -O we received to -O{0,1,2,3}.
416     //
417     // TODO: Perhaps we should map host -O2 to ptxas -O3. -O3 is ptxas's
418     // default, so it may correspond more closely to the spirit of clang -O2.
419 
420     // -O3 seems like the least-bad option when -Osomething is specified to
421     // clang but it isn't handled below.
422     StringRef OOpt = "3";
423     if (A->getOption().matches(options::OPT_O4) ||
424         A->getOption().matches(options::OPT_Ofast))
425       OOpt = "3";
426     else if (A->getOption().matches(options::OPT_O0))
427       OOpt = "0";
428     else if (A->getOption().matches(options::OPT_O)) {
429       // -Os, -Oz, and -O(anything else) map to -O2, for lack of better options.
430       OOpt = llvm::StringSwitch<const char *>(A->getValue())
431                  .Case("1", "1")
432                  .Case("2", "2")
433                  .Case("3", "3")
434                  .Case("s", "2")
435                  .Case("z", "2")
436                  .Default("2");
437     }
438     CmdArgs.push_back(Args.MakeArgString(llvm::Twine("-O") + OOpt));
439   } else {
440     // If no -O was passed, pass -O0 to ptxas -- no opt flag should correspond
441     // to no optimizations, but ptxas's default is -O3.
442     CmdArgs.push_back("-O0");
443   }
444   if (DIKind == DebugDirectivesOnly)
445     CmdArgs.push_back("-lineinfo");
446 
447   // Pass -v to ptxas if it was passed to the driver.
448   if (Args.hasArg(options::OPT_v))
449     CmdArgs.push_back("-v");
450 
451   CmdArgs.push_back("--gpu-name");
452   CmdArgs.push_back(Args.MakeArgString(CudaArchToString(gpu_arch)));
453   CmdArgs.push_back("--output-file");
454   std::string OutputFileName = TC.getInputFilename(Output);
455 
456   // If we are invoking `nvlink` internally we need to output a `.cubin` file.
457   // FIXME: This should hopefully be removed if NVIDIA updates their tooling.
458   if (!C.getInputArgs().getLastArg(options::OPT_c)) {
459     SmallString<256> Filename(Output.getFilename());
460     llvm::sys::path::replace_extension(Filename, "cubin");
461     OutputFileName = Filename.str();
462   }
463   if (Output.isFilename() && OutputFileName != Output.getFilename())
464     C.addTempFile(Args.MakeArgString(OutputFileName));
465 
466   CmdArgs.push_back(Args.MakeArgString(OutputFileName));
467   for (const auto &II : Inputs)
468     CmdArgs.push_back(Args.MakeArgString(II.getFilename()));
469 
470   for (const auto &A : Args.getAllArgValues(options::OPT_Xcuda_ptxas))
471     CmdArgs.push_back(Args.MakeArgString(A));
472 
473   bool Relocatable;
474   if (JA.isOffloading(Action::OFK_OpenMP))
475     // In OpenMP we need to generate relocatable code.
476     Relocatable = Args.hasFlag(options::OPT_fopenmp_relocatable_target,
477                                options::OPT_fnoopenmp_relocatable_target,
478                                /*Default=*/true);
479   else if (JA.isOffloading(Action::OFK_Cuda))
480     // In CUDA we generate relocatable code by default.
481     Relocatable = Args.hasFlag(options::OPT_fgpu_rdc, options::OPT_fno_gpu_rdc,
482                                /*Default=*/false);
483   else
484     // Otherwise, we are compiling directly and should create linkable output.
485     Relocatable = true;
486 
487   if (Relocatable)
488     CmdArgs.push_back("-c");
489 
490   const char *Exec;
491   if (Arg *A = Args.getLastArg(options::OPT_ptxas_path_EQ))
492     Exec = A->getValue();
493   else
494     Exec = Args.MakeArgString(TC.GetProgramPath("ptxas"));
495   C.addCommand(std::make_unique<Command>(
496       JA, *this,
497       ResponseFileSupport{ResponseFileSupport::RF_Full, llvm::sys::WEM_UTF8,
498                           "--options-file"},
499       Exec, CmdArgs, Inputs, Output));
500 }
501 
502 static bool shouldIncludePTX(const ArgList &Args, const char *gpu_arch) {
503   bool includePTX = true;
504   for (Arg *A : Args) {
505     if (!(A->getOption().matches(options::OPT_cuda_include_ptx_EQ) ||
506           A->getOption().matches(options::OPT_no_cuda_include_ptx_EQ)))
507       continue;
508     A->claim();
509     const StringRef ArchStr = A->getValue();
510     if (ArchStr == "all" || ArchStr == gpu_arch) {
511       includePTX = A->getOption().matches(options::OPT_cuda_include_ptx_EQ);
512       continue;
513     }
514   }
515   return includePTX;
516 }
517 
518 // All inputs to this linker must be from CudaDeviceActions, as we need to look
519 // at the Inputs' Actions in order to figure out which GPU architecture they
520 // correspond to.
521 void NVPTX::FatBinary::ConstructJob(Compilation &C, const JobAction &JA,
522                                     const InputInfo &Output,
523                                     const InputInfoList &Inputs,
524                                     const ArgList &Args,
525                                     const char *LinkingOutput) const {
526   const auto &TC =
527       static_cast<const toolchains::CudaToolChain &>(getToolChain());
528   assert(TC.getTriple().isNVPTX() && "Wrong platform");
529 
530   ArgStringList CmdArgs;
531   if (TC.CudaInstallation.version() <= CudaVersion::CUDA_100)
532     CmdArgs.push_back("--cuda");
533   CmdArgs.push_back(TC.getTriple().isArch64Bit() ? "-64" : "-32");
534   CmdArgs.push_back(Args.MakeArgString("--create"));
535   CmdArgs.push_back(Args.MakeArgString(Output.getFilename()));
536   if (mustEmitDebugInfo(Args) == EmitSameDebugInfoAsHost)
537     CmdArgs.push_back("-g");
538 
539   for (const auto &II : Inputs) {
540     auto *A = II.getAction();
541     assert(A->getInputs().size() == 1 &&
542            "Device offload action is expected to have a single input");
543     const char *gpu_arch_str = A->getOffloadingArch();
544     assert(gpu_arch_str &&
545            "Device action expected to have associated a GPU architecture!");
546     CudaArch gpu_arch = StringToCudaArch(gpu_arch_str);
547 
548     if (II.getType() == types::TY_PP_Asm &&
549         !shouldIncludePTX(Args, gpu_arch_str))
550       continue;
551     // We need to pass an Arch of the form "sm_XX" for cubin files and
552     // "compute_XX" for ptx.
553     const char *Arch = (II.getType() == types::TY_PP_Asm)
554                            ? CudaArchToVirtualArchString(gpu_arch)
555                            : gpu_arch_str;
556     CmdArgs.push_back(
557         Args.MakeArgString(llvm::Twine("--image=profile=") + Arch +
558                            ",file=" + getToolChain().getInputFilename(II)));
559   }
560 
561   for (const auto &A : Args.getAllArgValues(options::OPT_Xcuda_fatbinary))
562     CmdArgs.push_back(Args.MakeArgString(A));
563 
564   const char *Exec = Args.MakeArgString(TC.GetProgramPath("fatbinary"));
565   C.addCommand(std::make_unique<Command>(
566       JA, *this,
567       ResponseFileSupport{ResponseFileSupport::RF_Full, llvm::sys::WEM_UTF8,
568                           "--options-file"},
569       Exec, CmdArgs, Inputs, Output));
570 }
571 
572 void NVPTX::Linker::ConstructJob(Compilation &C, const JobAction &JA,
573                                  const InputInfo &Output,
574                                  const InputInfoList &Inputs,
575                                  const ArgList &Args,
576                                  const char *LinkingOutput) const {
577   const auto &TC =
578       static_cast<const toolchains::NVPTXToolChain &>(getToolChain());
579   ArgStringList CmdArgs;
580 
581   assert(TC.getTriple().isNVPTX() && "Wrong platform");
582 
583   assert((Output.isFilename() || Output.isNothing()) && "Invalid output.");
584   if (Output.isFilename()) {
585     CmdArgs.push_back("-o");
586     CmdArgs.push_back(Output.getFilename());
587   }
588 
589   if (mustEmitDebugInfo(Args) == EmitSameDebugInfoAsHost)
590     CmdArgs.push_back("-g");
591 
592   if (Args.hasArg(options::OPT_v))
593     CmdArgs.push_back("-v");
594 
595   StringRef GPUArch = Args.getLastArgValue(options::OPT_march_EQ);
596   assert(!GPUArch.empty() && "At least one GPU Arch required for nvlink.");
597 
598   CmdArgs.push_back("-arch");
599   CmdArgs.push_back(Args.MakeArgString(GPUArch));
600 
601   // Add paths specified in LIBRARY_PATH environment variable as -L options.
602   addDirectoryList(Args, CmdArgs, "-L", "LIBRARY_PATH");
603 
604   // Add paths for the default clang library path.
605   SmallString<256> DefaultLibPath =
606       llvm::sys::path::parent_path(TC.getDriver().Dir);
607   llvm::sys::path::append(DefaultLibPath, CLANG_INSTALL_LIBDIR_BASENAME);
608   CmdArgs.push_back(Args.MakeArgString(Twine("-L") + DefaultLibPath));
609 
610   for (const auto &II : Inputs) {
611     if (II.getType() == types::TY_LLVM_IR || II.getType() == types::TY_LTO_IR ||
612         II.getType() == types::TY_LTO_BC || II.getType() == types::TY_LLVM_BC) {
613       C.getDriver().Diag(diag::err_drv_no_linker_llvm_support)
614           << getToolChain().getTripleString();
615       continue;
616     }
617 
618     // Currently, we only pass the input files to the linker, we do not pass
619     // any libraries that may be valid only for the host.
620     if (!II.isFilename())
621       continue;
622 
623     // The 'nvlink' application performs RDC-mode linking when given a '.o'
624     // file and device linking when given a '.cubin' file. We always want to
625     // perform device linking, so just rename any '.o' files.
626     // FIXME: This should hopefully be removed if NVIDIA updates their tooling.
627     auto InputFile = getToolChain().getInputFilename(II);
628     if (llvm::sys::path::extension(InputFile) != ".cubin") {
629       // If there are no actions above this one then this is direct input and we
630       // can copy it. Otherwise the input is internal so a `.cubin` file should
631       // exist.
632       if (II.getAction() && II.getAction()->getInputs().size() == 0) {
633         const char *CubinF =
634             Args.MakeArgString(getToolChain().getDriver().GetTemporaryPath(
635                 llvm::sys::path::stem(InputFile), "cubin"));
636         if (llvm::sys::fs::copy_file(InputFile, C.addTempFile(CubinF)))
637           continue;
638 
639         CmdArgs.push_back(CubinF);
640       } else {
641         SmallString<256> Filename(InputFile);
642         llvm::sys::path::replace_extension(Filename, "cubin");
643         CmdArgs.push_back(Args.MakeArgString(Filename));
644       }
645     } else {
646       CmdArgs.push_back(Args.MakeArgString(InputFile));
647     }
648   }
649 
650   C.addCommand(std::make_unique<Command>(
651       JA, *this,
652       ResponseFileSupport{ResponseFileSupport::RF_Full, llvm::sys::WEM_UTF8,
653                           "--options-file"},
654       Args.MakeArgString(getToolChain().GetProgramPath("nvlink")), CmdArgs,
655       Inputs, Output));
656 }
657 
658 void NVPTX::getNVPTXTargetFeatures(const Driver &D, const llvm::Triple &Triple,
659                                    const llvm::opt::ArgList &Args,
660                                    std::vector<StringRef> &Features) {
661   if (Args.hasArg(options::OPT_cuda_feature_EQ)) {
662     StringRef PtxFeature =
663         Args.getLastArgValue(options::OPT_cuda_feature_EQ, "+ptx42");
664     Features.push_back(Args.MakeArgString(PtxFeature));
665     return;
666   }
667   CudaInstallationDetector CudaInstallation(D, Triple, Args);
668 
669   // New CUDA versions often introduce new instructions that are only supported
670   // by new PTX version, so we need to raise PTX level to enable them in NVPTX
671   // back-end.
672   const char *PtxFeature = nullptr;
673   switch (CudaInstallation.version()) {
674 #define CASE_CUDA_VERSION(CUDA_VER, PTX_VER)                                   \
675   case CudaVersion::CUDA_##CUDA_VER:                                           \
676     PtxFeature = "+ptx" #PTX_VER;                                              \
677     break;
678     CASE_CUDA_VERSION(123, 83);
679     CASE_CUDA_VERSION(122, 82);
680     CASE_CUDA_VERSION(121, 81);
681     CASE_CUDA_VERSION(120, 80);
682     CASE_CUDA_VERSION(118, 78);
683     CASE_CUDA_VERSION(117, 77);
684     CASE_CUDA_VERSION(116, 76);
685     CASE_CUDA_VERSION(115, 75);
686     CASE_CUDA_VERSION(114, 74);
687     CASE_CUDA_VERSION(113, 73);
688     CASE_CUDA_VERSION(112, 72);
689     CASE_CUDA_VERSION(111, 71);
690     CASE_CUDA_VERSION(110, 70);
691     CASE_CUDA_VERSION(102, 65);
692     CASE_CUDA_VERSION(101, 64);
693     CASE_CUDA_VERSION(100, 63);
694     CASE_CUDA_VERSION(92, 61);
695     CASE_CUDA_VERSION(91, 61);
696     CASE_CUDA_VERSION(90, 60);
697 #undef CASE_CUDA_VERSION
698   default:
699     PtxFeature = "+ptx42";
700   }
701   Features.push_back(PtxFeature);
702 }
703 
704 /// NVPTX toolchain. Our assembler is ptxas, and our linker is nvlink. This
705 /// operates as a stand-alone version of the NVPTX tools without the host
706 /// toolchain.
707 NVPTXToolChain::NVPTXToolChain(const Driver &D, const llvm::Triple &Triple,
708                                const llvm::Triple &HostTriple,
709                                const ArgList &Args, bool Freestanding = false)
710     : ToolChain(D, Triple, Args), CudaInstallation(D, HostTriple, Args),
711       Freestanding(Freestanding) {
712   if (CudaInstallation.isValid())
713     getProgramPaths().push_back(std::string(CudaInstallation.getBinPath()));
714   // Lookup binaries into the driver directory, this is used to
715   // discover the 'nvptx-arch' executable.
716   getProgramPaths().push_back(getDriver().Dir);
717 }
718 
719 /// We only need the host triple to locate the CUDA binary utilities, use the
720 /// system's default triple if not provided.
721 NVPTXToolChain::NVPTXToolChain(const Driver &D, const llvm::Triple &Triple,
722                                const ArgList &Args)
723     : NVPTXToolChain(D, Triple, llvm::Triple(LLVM_HOST_TRIPLE), Args,
724                      /*Freestanding=*/true) {}
725 
726 llvm::opt::DerivedArgList *
727 NVPTXToolChain::TranslateArgs(const llvm::opt::DerivedArgList &Args,
728                               StringRef BoundArch,
729                               Action::OffloadKind DeviceOffloadKind) const {
730   DerivedArgList *DAL =
731       ToolChain::TranslateArgs(Args, BoundArch, DeviceOffloadKind);
732   if (!DAL)
733     DAL = new DerivedArgList(Args.getBaseArgs());
734 
735   const OptTable &Opts = getDriver().getOpts();
736 
737   for (Arg *A : Args)
738     if (!llvm::is_contained(*DAL, A))
739       DAL->append(A);
740 
741   if (!DAL->hasArg(options::OPT_march_EQ))
742     DAL->AddJoinedArg(nullptr, Opts.getOption(options::OPT_march_EQ),
743                       CudaArchToString(CudaArch::CudaDefault));
744 
745   return DAL;
746 }
747 
748 void NVPTXToolChain::addClangTargetOptions(
749     const llvm::opt::ArgList &DriverArgs, llvm::opt::ArgStringList &CC1Args,
750     Action::OffloadKind DeviceOffloadingKind) const {
751   // If we are compiling with a standalone NVPTX toolchain we want to try to
752   // mimic a standard environment as much as possible. So we enable lowering
753   // ctor / dtor functions to global symbols that can be registered.
754   if (Freestanding)
755     CC1Args.append({"-mllvm", "--nvptx-lower-global-ctor-dtor"});
756 }
757 
758 bool NVPTXToolChain::supportsDebugInfoOption(const llvm::opt::Arg *A) const {
759   const Option &O = A->getOption();
760   return (O.matches(options::OPT_gN_Group) &&
761           !O.matches(options::OPT_gmodules)) ||
762          O.matches(options::OPT_g_Flag) ||
763          O.matches(options::OPT_ggdbN_Group) || O.matches(options::OPT_ggdb) ||
764          O.matches(options::OPT_gdwarf) || O.matches(options::OPT_gdwarf_2) ||
765          O.matches(options::OPT_gdwarf_3) || O.matches(options::OPT_gdwarf_4) ||
766          O.matches(options::OPT_gdwarf_5) ||
767          O.matches(options::OPT_gcolumn_info);
768 }
769 
770 void NVPTXToolChain::adjustDebugInfoKind(
771     llvm::codegenoptions::DebugInfoKind &DebugInfoKind,
772     const ArgList &Args) const {
773   switch (mustEmitDebugInfo(Args)) {
774   case DisableDebugInfo:
775     DebugInfoKind = llvm::codegenoptions::NoDebugInfo;
776     break;
777   case DebugDirectivesOnly:
778     DebugInfoKind = llvm::codegenoptions::DebugDirectivesOnly;
779     break;
780   case EmitSameDebugInfoAsHost:
781     // Use same debug info level as the host.
782     break;
783   }
784 }
785 
786 /// CUDA toolchain.  Our assembler is ptxas, and our "linker" is fatbinary,
787 /// which isn't properly a linker but nonetheless performs the step of stitching
788 /// together object files from the assembler into a single blob.
789 
790 CudaToolChain::CudaToolChain(const Driver &D, const llvm::Triple &Triple,
791                              const ToolChain &HostTC, const ArgList &Args)
792     : NVPTXToolChain(D, Triple, HostTC.getTriple(), Args), HostTC(HostTC) {}
793 
794 void CudaToolChain::addClangTargetOptions(
795     const llvm::opt::ArgList &DriverArgs, llvm::opt::ArgStringList &CC1Args,
796     Action::OffloadKind DeviceOffloadingKind) const {
797   HostTC.addClangTargetOptions(DriverArgs, CC1Args, DeviceOffloadingKind);
798 
799   StringRef GpuArch = DriverArgs.getLastArgValue(options::OPT_march_EQ);
800   assert(!GpuArch.empty() && "Must have an explicit GPU arch.");
801   assert((DeviceOffloadingKind == Action::OFK_OpenMP ||
802           DeviceOffloadingKind == Action::OFK_Cuda) &&
803          "Only OpenMP or CUDA offloading kinds are supported for NVIDIA GPUs.");
804 
805   if (DeviceOffloadingKind == Action::OFK_Cuda) {
806     CC1Args.append(
807         {"-fcuda-is-device", "-mllvm", "-enable-memcpyopt-without-libcalls"});
808 
809     // Unsized function arguments used for variadics were introduced in CUDA-9.0
810     // We still do not support generating code that actually uses variadic
811     // arguments yet, but we do need to allow parsing them as recent CUDA
812     // headers rely on that. https://github.com/llvm/llvm-project/issues/58410
813     if (CudaInstallation.version() >= CudaVersion::CUDA_90)
814       CC1Args.push_back("-fcuda-allow-variadic-functions");
815   }
816 
817   if (DriverArgs.hasArg(options::OPT_nogpulib))
818     return;
819 
820   if (DeviceOffloadingKind == Action::OFK_OpenMP &&
821       DriverArgs.hasArg(options::OPT_S))
822     return;
823 
824   std::string LibDeviceFile = CudaInstallation.getLibDeviceFile(GpuArch);
825   if (LibDeviceFile.empty()) {
826     getDriver().Diag(diag::err_drv_no_cuda_libdevice) << GpuArch;
827     return;
828   }
829 
830   CC1Args.push_back("-mlink-builtin-bitcode");
831   CC1Args.push_back(DriverArgs.MakeArgString(LibDeviceFile));
832 
833   clang::CudaVersion CudaInstallationVersion = CudaInstallation.version();
834 
835   if (DriverArgs.hasFlag(options::OPT_fcuda_short_ptr,
836                          options::OPT_fno_cuda_short_ptr, false))
837     CC1Args.append({"-mllvm", "--nvptx-short-ptr"});
838 
839   if (CudaInstallationVersion >= CudaVersion::UNKNOWN)
840     CC1Args.push_back(
841         DriverArgs.MakeArgString(Twine("-target-sdk-version=") +
842                                  CudaVersionToString(CudaInstallationVersion)));
843 
844   if (DeviceOffloadingKind == Action::OFK_OpenMP) {
845     if (CudaInstallationVersion < CudaVersion::CUDA_92) {
846       getDriver().Diag(
847           diag::err_drv_omp_offload_target_cuda_version_not_support)
848           << CudaVersionToString(CudaInstallationVersion);
849       return;
850     }
851 
852     // Link the bitcode library late if we're using device LTO.
853     if (getDriver().isUsingLTO(/* IsOffload */ true))
854       return;
855 
856     addOpenMPDeviceRTL(getDriver(), DriverArgs, CC1Args, GpuArch.str(),
857                        getTriple());
858   }
859 }
860 
861 llvm::DenormalMode CudaToolChain::getDefaultDenormalModeForType(
862     const llvm::opt::ArgList &DriverArgs, const JobAction &JA,
863     const llvm::fltSemantics *FPType) const {
864   if (JA.getOffloadingDeviceKind() == Action::OFK_Cuda) {
865     if (FPType && FPType == &llvm::APFloat::IEEEsingle() &&
866         DriverArgs.hasFlag(options::OPT_fgpu_flush_denormals_to_zero,
867                            options::OPT_fno_gpu_flush_denormals_to_zero, false))
868       return llvm::DenormalMode::getPreserveSign();
869   }
870 
871   assert(JA.getOffloadingDeviceKind() != Action::OFK_Host);
872   return llvm::DenormalMode::getIEEE();
873 }
874 
875 void CudaToolChain::AddCudaIncludeArgs(const ArgList &DriverArgs,
876                                        ArgStringList &CC1Args) const {
877   // Check our CUDA version if we're going to include the CUDA headers.
878   if (!DriverArgs.hasArg(options::OPT_nogpuinc) &&
879       !DriverArgs.hasArg(options::OPT_no_cuda_version_check)) {
880     StringRef Arch = DriverArgs.getLastArgValue(options::OPT_march_EQ);
881     assert(!Arch.empty() && "Must have an explicit GPU arch.");
882     CudaInstallation.CheckCudaVersionSupportsArch(StringToCudaArch(Arch));
883   }
884   CudaInstallation.AddCudaIncludeArgs(DriverArgs, CC1Args);
885 }
886 
887 std::string CudaToolChain::getInputFilename(const InputInfo &Input) const {
888   // Only object files are changed, for example assembly files keep their .s
889   // extensions. If the user requested device-only compilation don't change it.
890   if (Input.getType() != types::TY_Object || getDriver().offloadDeviceOnly())
891     return ToolChain::getInputFilename(Input);
892 
893   // Replace extension for object files with cubin because nvlink relies on
894   // these particular file names.
895   SmallString<256> Filename(ToolChain::getInputFilename(Input));
896   llvm::sys::path::replace_extension(Filename, "cubin");
897   return std::string(Filename.str());
898 }
899 
900 llvm::opt::DerivedArgList *
901 CudaToolChain::TranslateArgs(const llvm::opt::DerivedArgList &Args,
902                              StringRef BoundArch,
903                              Action::OffloadKind DeviceOffloadKind) const {
904   DerivedArgList *DAL =
905       HostTC.TranslateArgs(Args, BoundArch, DeviceOffloadKind);
906   if (!DAL)
907     DAL = new DerivedArgList(Args.getBaseArgs());
908 
909   const OptTable &Opts = getDriver().getOpts();
910 
911   // For OpenMP device offloading, append derived arguments. Make sure
912   // flags are not duplicated.
913   // Also append the compute capability.
914   if (DeviceOffloadKind == Action::OFK_OpenMP) {
915     for (Arg *A : Args)
916       if (!llvm::is_contained(*DAL, A))
917         DAL->append(A);
918 
919     if (!DAL->hasArg(options::OPT_march_EQ)) {
920       StringRef Arch = BoundArch;
921       if (Arch.empty()) {
922         auto ArchsOrErr = getSystemGPUArchs(Args);
923         if (!ArchsOrErr) {
924           std::string ErrMsg =
925               llvm::formatv("{0}", llvm::fmt_consume(ArchsOrErr.takeError()));
926           getDriver().Diag(diag::err_drv_undetermined_gpu_arch)
927               << llvm::Triple::getArchTypeName(getArch()) << ErrMsg << "-march";
928           Arch = CudaArchToString(CudaArch::CudaDefault);
929         } else {
930           Arch = Args.MakeArgString(ArchsOrErr->front());
931         }
932       }
933       DAL->AddJoinedArg(nullptr, Opts.getOption(options::OPT_march_EQ), Arch);
934     }
935 
936     return DAL;
937   }
938 
939   for (Arg *A : Args) {
940     DAL->append(A);
941   }
942 
943   if (!BoundArch.empty()) {
944     DAL->eraseArg(options::OPT_march_EQ);
945     DAL->AddJoinedArg(nullptr, Opts.getOption(options::OPT_march_EQ),
946                       BoundArch);
947   }
948   return DAL;
949 }
950 
951 Expected<SmallVector<std::string>>
952 CudaToolChain::getSystemGPUArchs(const ArgList &Args) const {
953   // Detect NVIDIA GPUs availible on the system.
954   std::string Program;
955   if (Arg *A = Args.getLastArg(options::OPT_nvptx_arch_tool_EQ))
956     Program = A->getValue();
957   else
958     Program = GetProgramPath("nvptx-arch");
959 
960   auto StdoutOrErr = executeToolChainProgram(Program);
961   if (!StdoutOrErr)
962     return StdoutOrErr.takeError();
963 
964   SmallVector<std::string, 1> GPUArchs;
965   for (StringRef Arch : llvm::split((*StdoutOrErr)->getBuffer(), "\n"))
966     if (!Arch.empty())
967       GPUArchs.push_back(Arch.str());
968 
969   if (GPUArchs.empty())
970     return llvm::createStringError(std::error_code(),
971                                    "No NVIDIA GPU detected in the system");
972 
973   return std::move(GPUArchs);
974 }
975 
976 Tool *NVPTXToolChain::buildAssembler() const {
977   return new tools::NVPTX::Assembler(*this);
978 }
979 
980 Tool *NVPTXToolChain::buildLinker() const {
981   return new tools::NVPTX::Linker(*this);
982 }
983 
984 Tool *CudaToolChain::buildAssembler() const {
985   return new tools::NVPTX::Assembler(*this);
986 }
987 
988 Tool *CudaToolChain::buildLinker() const {
989   return new tools::NVPTX::FatBinary(*this);
990 }
991 
992 void CudaToolChain::addClangWarningOptions(ArgStringList &CC1Args) const {
993   HostTC.addClangWarningOptions(CC1Args);
994 }
995 
996 ToolChain::CXXStdlibType
997 CudaToolChain::GetCXXStdlibType(const ArgList &Args) const {
998   return HostTC.GetCXXStdlibType(Args);
999 }
1000 
1001 void CudaToolChain::AddClangSystemIncludeArgs(const ArgList &DriverArgs,
1002                                               ArgStringList &CC1Args) const {
1003   HostTC.AddClangSystemIncludeArgs(DriverArgs, CC1Args);
1004 
1005   if (!DriverArgs.hasArg(options::OPT_nogpuinc) && CudaInstallation.isValid())
1006     CC1Args.append(
1007         {"-internal-isystem",
1008          DriverArgs.MakeArgString(CudaInstallation.getIncludePath())});
1009 }
1010 
1011 void CudaToolChain::AddClangCXXStdlibIncludeArgs(const ArgList &Args,
1012                                                  ArgStringList &CC1Args) const {
1013   HostTC.AddClangCXXStdlibIncludeArgs(Args, CC1Args);
1014 }
1015 
1016 void CudaToolChain::AddIAMCUIncludeArgs(const ArgList &Args,
1017                                         ArgStringList &CC1Args) const {
1018   HostTC.AddIAMCUIncludeArgs(Args, CC1Args);
1019 }
1020 
1021 SanitizerMask CudaToolChain::getSupportedSanitizers() const {
1022   // The CudaToolChain only supports sanitizers in the sense that it allows
1023   // sanitizer arguments on the command line if they are supported by the host
1024   // toolchain. The CudaToolChain will actually ignore any command line
1025   // arguments for any of these "supported" sanitizers. That means that no
1026   // sanitization of device code is actually supported at this time.
1027   //
1028   // This behavior is necessary because the host and device toolchains
1029   // invocations often share the command line, so the device toolchain must
1030   // tolerate flags meant only for the host toolchain.
1031   return HostTC.getSupportedSanitizers();
1032 }
1033 
1034 VersionTuple CudaToolChain::computeMSVCVersion(const Driver *D,
1035                                                const ArgList &Args) const {
1036   return HostTC.computeMSVCVersion(D, Args);
1037 }
1038