[ThreadPool] On Windows, extend usage to all CPU sockets and all NUMA groups

[aganea]

Summary

TL;DR: This patches ensures that, on Windows, all CPU sockets and all NUMA nodes are used by the ThreadPool. The goal was to have LLD/ThinLTO use all hardware threads in the system, which isn't the case currently on multi-socket or large CPU count systems.

(this could possibly be split into a few patches, but I just wanted an overall opinion)

Background

Windows doesn't have a flat cpu_set_t like Linux. Instead, it projects hardware CPUs (or NUMA nodes) to applications through a concept of "processor groups". A "processor" is the smallest unit of execution on a CPU, that is, an hyper-thread if SMT is active; a core otherwise. There's a limit of 32-bit processors on older 32-bit versions of Windows, which later was raised to 64-processors with 64-bit versions of Windows. This limit comes from the affinity mask, which historically was represented by the sizeof(void*) (still is that way). Consequently, the concept of "processor groups" was introduced for dealing with systems with more than 64 hyper-threads.

By default, the Windows OS assigns only one "processor group" to each starting application, in a round-robin manner. If the application wants to use more processors, it needs to programmatically enable it, by assigning threads to other "processor groups". This also means that affinity cannot cross "processor group" boundaries; one can only specify a "preferred" group on startup, but the application is free to allocate more groups if it wants to.

This creates a peculiar situation, where newer CPUs like the AMD EPYC 7702P (64-cores, 128-hyperthreads) are projected by the OS as two (2) "processor groups". This means that by default, an application can only use half of the cores. This situation will only get worse in the years to come, as dies with more cores will appear on the market.

The changes in this patch

Previously, the problem was that heavyweight_hardware_concurrency() API was introduced so that only one hardware thread per core was used. Once that API returns, that original intention is lost. Consider a situation, on Windows, where the system has 2 CPU sockets, 18 cores each, each core having 2 hyper-threads, for a total of 72 hyper-threads. Both heavyweight_hardware_concurrency() and hardware_concurrency() currently return 36, because on Windows they are simply wrappers over std::thread::hardware_concurrency() -- which returns only processors from the current "processor group".

What if we wanted to use all "processor groups" ? Even if we implemented properly heavyweight_hardware_concurrency(), what should it then return ? 18 or 36 ?
What if the user specified /opt:lldltojobs=36 ? Should we assign 36 threads on the current "processor group" or should we dispatch extra threads on the second "processor groups" ?

To solve this situation, we capture (and retain) the initial intention until the point of usage, through a new ThreadPoolStrategy class. The number of threads to use is deferred as late as possible, until the moment where the std::threads are created (ThreadPool in the case of ThinLTO).

Discussion

Ideally, we should consider all "processors" (on Windows) or all "CPUs" (Linux) as all equal, in which case heavyweight_hardware_concurrency() wouldn't be needed. I'm not sure how micro-managing threads, cores and NUMA nodes will scale in the years to come (probably not well). Will it make sense to say "I don't want hyper-threads" ? Or saying /opt:lldltojobs=whatever when you have a thousand(s)-core system ? How would that work with NUMA affinity ? For example the Fujitsu A64FX has 4x "12-core tiles" on the same die, each tile being connected to an internal 8-GB HBM2 memory (each located internally on the CPU die). How would we dispatch threads in that case ? The AMD EPYC uses the same concept of "tiles", however it doesn't have internal memory yet, but most likely the EPYC v3 will use the same architecture.

@tejohnson : Teresa, since you added heavyweight_hardware_concurrency(), do you have a benchmark which compares ThinLTO running with heavyweight_hardware_concurrency() or with hardware_concurrency() ? (I haven't done that test yet)
It would make things a lot simpler if we didn't have that API, and in general considered that we could use all hardware threads in the system; and that they can perform equally.

NOTE: For full effect, this patch needs rpmalloc (D71786)

[merge_guards_bot]

Unit tests: pass. 61057 tests passed, 0 failed and 728 were skipped.

clang-tidy: fail. Please fix clang-tidy findings.

clang-format: fail. Please format your changes with clang-format by running git-clang-format HEAD^ or applying this patch.

Build artifacts: diff.json, clang-tidy.txt, clang-format.patch, CMakeCache.txt, console-log.txt, test-results.xml

[mehdi_amini]

Will it make sense to say "I don't want hyper-threads" ?

Not sure I remember correctly, but I believe one motivation behind avoiding "hyper-threads" and other virtual cores was that while they improve slightly the performance, they also increase the peak memory requirements: using heavyweight_hardware_concurrency() seemed like a good default tradeoff for most end-users.

[mehdi_amini]

Also: using heavyweight_hardware_concurrency() in the linker but having multiple linker jobs schedules by the build system was another reason (I think LLVM CMake default to 2 parallel link jobs when using ThinLTO for instance).

[aganea]

In D71775#1793767, @mehdi_amini wrote:

Will it make sense to say "I don't want hyper-threads" ?

Not sure I remember correctly, but I believe one motivation behind avoiding "hyper-threads" and other virtual cores was that while they improve slightly the performance, they also increase the peak memory requirements: using heavyweight_hardware_concurrency() seemed like a good default tradeoff for most end-users.

It all makes sense. After this patch, the memory consumption is doubled when using both CPU sockets. Evidently then there's also a discussion about memory bandwidth, which doesn't scale in my case, when using both sockets (possibly on a AMD Epyc it could be better because is has more memory channels.). This is also why enabling the second socket only marginally decrease the timings.

In Ubisoft's case, time is immensely more valuable (both compute and human) than memory sticks. Historically we didn't really use LTO on game productions because it was really slow, and often introduced undesirable bugs or side-effects. The graphs in D71786 are for Rainbow 6: Siege, which is a "smaller" codebase. For larger games, LTO link time is more in the range of 1h 20min, both for MSVC and previous versions of Clang. If there's a LTO-specific bug in a final build, it is very hard to iterate with that kind of timings. In addition, there are hundreds of builds every day on the build system, and we want to keep all the cores in the build system busy. This is why both build and link times are important to us.

In D71775#1793768, @mehdi_amini wrote:

Also: using heavyweight_hardware_concurrency() in the linker but having multiple linker jobs schedules by the build system was another reason (I think LLVM CMake default to 2 parallel link jobs when using ThinLTO for instance).

Understood. If one sets the CPU affinity when starting the application, ie. start /affinity XXX lld-link.exe ..., then this patch disables dispatching on other "processor groups", even if they are available. However, there doesn't seem to be a way to restrain the application to one "processor group".

Remains to see if we want to keep the current behavior, where only one socket is use, and have an option to enable the other CPU sockets. Or if we want that multi-socket behavior by default, as in this patch.

[rnk]

+@gbiv @inglorion, other ThinLTO users.

To solve this situation, we capture (and retain) the initial intention until the point of usage, through a new ThreadPoolStrategy class. The number of threads to use is deferred as late as possible, until the moment where the std::threads are created (ThreadPool in the case of ThinLTO).

That seems reasonable to me.

llvm/include/llvm/ADT/SmallBitVector.h

487 ↗

(On Diff #234910)

I guess we don't need these changes, since it looks like you use BitVector only below.

500 ↗

(On Diff #234910)

You return A - B but then compare for equality to -1 and 1. I guess it works because you are doing it bit by bit, but it's exciting.

llvm/include/llvm/Support/Threading.h

152

Let's name the fields in a way that indicates that these numbers are the requested number of threads, not the final number. So, ThreadsRequested or something like that.

157

This could be UseHyperThreads. The first time I read it, I guessed that it indicated if the system has hyperthreads.

llvm/lib/Support/Host.cpp

1277

Another -1 case.

1334

Note: the -1 case.

llvm/lib/Support/Threading.cpp

84–85

We already have a public API, getHostNumPhysicalCores. Can this use that?

87

I see these computeHostNum* methods return int, and some versions seem to return -1 to indicate errors. I think you'll want to use int here and check if MaxThreadCount <= 0. Otherwise below we may do a signed/unsigned comparison mismatch, and return ~0U for MaxThreadCount.

llvm/lib/Support/Unix/Threading.inc

273

I'm not sure it makes sense to say "physical threads". I think "physical cores" was meant to distinguish between hardware threads and cores. Describing hardware execution resources as physical or non-physical isn't very precise or meaningful in the first place, but I don't think it should apply to hyper threads.

llvm/lib/Support/Windows/Threading.inc

160

This is cached, so maybe getProcessorGroups to indicate that it is not intended to be expensive.

212

Seems like static can be used here.

llvm/unittests/Support/ThreadPool.cpp

31

"Temporary" >_>

180

I guess this is why you added comparison operators. In any case, let's remove the commented out code in the final version.

[aganea]

Updated as suggested by @rnk.
I've also removed ThreadPoolStrategy::PinThreads because it wasn't conclusive. In the best case, pinning threads to a core / hyperthread, was similar in performance to that of using a full CPU socket affinity; in the worst case, it was degrading performance. The NT scheduler seems to be doing a pretty good job here, so we'll stick with it :-)

[aganea]

llvm/lib/Support/Unix/Threading.inc

273

computeHostNumHardwareThreads() ?

[aganea]

Ping! Any further comments?

[rnk]

lgtm

llvm/lib/Support/Unix/Threading.inc

273

lgtm

[rriddle]

(Appeasing herald for MLIR changes).

[thakis]

https://bugs.chromium.org/p/chromium/issues/detail?id=1051578#c12 :

"""
FYI for those building on AMD Bulldozer family of processors and its various iterations after this commit:

https://reviews.llvm.org/D71775

Building with ThinLTO on Bulldozer and similar appears to now be capped to how Windows reports cores versus logical processors, thus now halving the number of LTO threads available when building. Manually setting /opt:lldltojobs= for LLD does not override it, as that only sets an upper limit.

Found out as I locally build on a 32-core Opteron system. Windows treats it as 16 cores and 32 logical processors, but it is not a SMT setup like Intel HyperTreading. In particular:

"A module consists of a coupling of two "conventional" x86 out of order processing cores. The processing core shares the early pipeline stages (e.g. L1i, fetch, decode), the FPUs, and the L2 cache with the rest of the module."

https://en.wikipedia.org/wiki/Bulldozer_(microarchitecture)

Naturally, build times have increased dramatically. YMMV.
"""

Sounds like this patch might have some drawbacks.

[aganea]

@thakis I think this is a side-effect of implementing computeHostNumPhysicalCores() for Windows, which previously returned -1, which in turn made llvm::heavyweight_hardware_concurrency() previously behave like llvm::hardware_concurrency() (on Windows only).
At first sight, Linux seems to report the same thing as Windows (2 cores per "module"). If I read this correctly, the behavior on Linux for a AMD Opteron is/was the same as it is currently on Windows after this patch, that is, only one core out of two would be used for llvm::heavyweight_hardware_concurrency().

I think there is a wider problem outside the scope of this patch, which is, some users want to use 100% of the cores/hyper-threads when using ThinLTO. Currently there's no way. An algorithm using llvm::heavyweight_hardware_concurrency() explicitly states "I only want one core out of two". It'd be nice if we had a cmd-line flag to override this, to say "I want to use all hyper-threads/cores/modules". /opt:lldltojobs=all? The impact is small on a modern Intel Skylake CPU, but it might be better depending on the CPU (AMD Bulldozer).

CORRECTION: The impact is small(-er) with SMT enabled because only half of that link-time truly multi-threaded (in this example). The other half is essentially the falloff and the regular .EXE section merging & debug info merging (of which currently none is multi-threaded for the COFF driver).
Graph of the CPU usage when linking clang.exe (here with rpmalloc):

[RobRich999]

I too can see how SMT might not afford much performance difference for LTO codegen.

CMT appears to be more significant. I do not have exact numbers right now as my build box is busy, but the change added like an hour to locally building the Chromium browser with ThinLTO optimizations enabled. Win10 running on a 32-core Opteron Piledriver (bdver2) system.

Definitely agree something like "/opt:lldltojobs=all" in a separate patch would be a good solution if possible for this particular (corner) case.

[mehdi_amini]

There is something puzzling to me in this patch in the way the ThreadPool was modified: the client of the thread pool cannot request a number of threads anymore, but only a *maximum* number of threads. I don't really understand why? Using the OS reported concurrency was always a "default", isn't this change orthogonal / unrelated to the stated goal of this patch?

[aganea]

llvm/lib/Support/Threading.cpp

94

@mehdi_amini You mean this? Testing was showing degraded performance if ThreadsRequested > MaxThreadCount, so I thought it'd maybe better to prevent that situation. More soft threads than hardware threads means you'd pay for context switching, for the cache eviction and for extra memory pressure (even more if the allocator has per-thread pools).
Do you see a cases where not having this test would be valuable? Providing --threads=50, and creating 50-threads ThreadPool when your CPU only supports 12 hardware threads? The only case I can think of is usage of async operations in threads, but then your ThreadPool sounds more like a queue, and maybe it's not the right hammer for the nail? Should we support that case and explicitly tag the ThreadPool constructor in client code with something like ThreadPool(50, AcknowledgeDegradedPerformance)?

[mehdi_amini]

llvm/lib/Support/Threading.cpp

94

Testing was showing degraded performance

I don't understand why this is relevant to anything else than the default? This is a library and if the caller override the default then IMO this layer should just let it be!

The current issue with bulldozer is a perfect example of this: the user is *requesting* more threads: why wouldn't you honor this request? If they want to shoot themselves in the foot, I'd let them (in most cases the user would know something you don't, like here).

I don't think we need the extra AcknowledgeDegradedPerformance flag, if the client override the default they can be assumed to know what they're doing (or they shouldn't use such an API in the first place), this seems more in line with the rest of the system (and C++ API in general I believe).

[john.brawn]

With this patch the Threading.PhysicalConcurrency unit test fails when run with an affinity less than the number of physical cpus. I've raised https://bugs.llvm.org/show_bug.cgi?id=45556.

[sammccall]

clang-tools-extra/clangd/index/Background.cpp

154

Hmm, I finally stumbled across this today when editing the rebuild policy.
I do wish this hadn't been changed without understanding what this code is doing or getting review from an owner.

After this change, modifying the background-index rebuild frequency (which was initially tuned to be roughly "after each thread built one file") has the side-effect of changing the number of threads used for background indexing!

Less seriously, the use of zero to mean "all the threads" is problematic here because in the other thread roots in this project we use zero to mean "no threads, work synchronously".

I'll look into reverting the clangd parts of this patch.

[aganea]

clang-tools-extra/clangd/index/Background.cpp

154

Sorry about that Sam. Do you think 'one' could be used in clangd instead? That is the common value used across other parts of LLVM to signify 'no threads', and also when LLVM_ENABLE_THREADS is off. 'zero' means to use the default settings for the thread strategy. That is, llvm::hardware_concurrency(0) means to use all hardware threads; or llvm::heavyweight_hardware_concurrency(0) means to use all hardware cores, but only one std::thread per core.

[sammccall]

I've sent https://reviews.llvm.org/D82352 to clean up some of the logic in clangd.

clang-tools-extra/clangd/index/Background.cpp

154

No worries, it happens and nothing came of it except a little head-scratching. Sorry for being grumpy, I shouldn't send email late at night...

Do you think 'one' could be used in clangd instead? That is the common value used across other parts of LLVM to signify 'no threads', and also when LLVM_ENABLE_THREADS is off

One can't be used here, it means "spawn one background thread". (Clangd has several distinct components that spawn threads).

FWIW, clangd can't be built without LLVM_ENABLE_THREADS - it needs concurrency to be useful, and we designed around threads. Most of the threading can be turned off *at runtime* for certain tests (that's what a threadpool size of zero means) but not the background index - we just disable it instead.

clang-tools-extra/clang-doc/tool/ClangDocMain.cpp

Exec->get()->getToolResults()->forEachResult(
       });
 
   // First reducing phase (reduce all decls into one info per decl).
   llvm::outs() << "Reducing " << USRToBitcode.size() << " infos...\n";
   std::atomic<bool> Error;
   Error = false;
   llvm::sys::Mutex IndexMutex;
   // ExecutorConcurrency is a flag exposed by AllTUsExecution.h
-  llvm::ThreadPool Pool(ExecutorConcurrency == 0 ? llvm::hardware_concurrency()
-                                                 : ExecutorConcurrency);
+  llvm::ThreadPool Pool(llvm::hardware_concurrency(ExecutorConcurrency));
   for (auto &Group : USRToBitcode) {
     Pool.async([&]() {
       std::vector<std::unique_ptr<doc::Info>> Infos;
 
       for (auto &Bitcode : Group.getValue()) {
         llvm::BitstreamCursor Stream(Bitcode);
         doc::ClangDocBitcodeReader Reader(Stream);
         auto ReadInfos = Reader.readBitcode();

clang-tools-extra/clangd/TUScheduler.cpp

case TUAction::Idle:
     break;
   }
   return OS.str();
 }
 
 } // namespace
 
 unsigned getDefaultAsyncThreadsCount() {
-  unsigned HardwareConcurrency = llvm::heavyweight_hardware_concurrency();
-  // heavyweight_hardware_concurrency may fall back to hardware_concurrency.
-  // C++ standard says that hardware_concurrency() may return 0; fallback to 1
-  // worker thread in that case.
-  if (HardwareConcurrency == 0)
-    return 1;
-  return HardwareConcurrency;
+  return llvm::heavyweight_hardware_concurrency().compute_thread_count();
 }
 
 FileStatus TUStatus::render(PathRef File) const {
   FileStatus FStatus;
   FStatus.uri = URIForFile::canonicalize(File, /*TUPath=*/File);
   FStatus.state = renderTUAction(Action);
   return FStatus;
 }

clang-tools-extra/clangd/index/Background.h

 public:
   /// If BuildIndexPeriodMs is greater than 0, the symbol index will only be
   /// rebuilt periodically (one per \p BuildIndexPeriodMs); otherwise, index is
   /// rebuilt for each indexed file.
   BackgroundIndex(
       Context BackgroundContext, const FileSystemProvider &,
       const GlobalCompilationDatabase &CDB,
       BackgroundIndexStorage::Factory IndexStorageFactory,
-      size_t ThreadPoolSize = llvm::heavyweight_hardware_concurrency(),
+      size_t ThreadPoolSize = 0, // 0 = use all hardware threads
       std::function<void(BackgroundQueue::Stats)> OnProgress = nullptr);
   ~BackgroundIndex(); // Blocks while the current task finishes.
 
   // Enqueue translation units for indexing.
   // The indexing happens in a background thread, so the symbols will be
   // available sometime later.
   void enqueue(const std::vector<std::string> &ChangedFiles) {
     Queue.push(changedFilesTask(ChangedFiles));

clang-tools-extra/clangd/index/Background.cpp

: SwapIndex(std::make_unique<MemIndex>()), FSProvider(FSProvider), CDB(CDB),
       BackgroundContext(std::move(BackgroundContext)),
       Rebuilder(this, &IndexedSymbols, ThreadPoolSize),
       IndexStorageFactory(std::move(IndexStorageFactory)),
       Queue(std::move(OnProgress)),
       CommandsChanged(
           CDB.watch([&](const std::vector<std::string> &ChangedFiles) {
             enqueue(ChangedFiles);
           })) {
-  assert(ThreadPoolSize > 0 && "Thread pool size can't be zero.");
+  assert(Rebuilder.TUsBeforeFirstBuild > 0 &&
+         "Thread pool size can't be zero.");
   assert(this->IndexStorageFactory && "Storage factory can not be null!");
-  for (unsigned I = 0; I < ThreadPoolSize; ++I) {
+  for (unsigned I = 0; I < Rebuilder.TUsBeforeFirstBuild; ++I) {
     ThreadPool.runAsync("background-worker-" + llvm::Twine(I + 1), [this] {
       WithContext Ctx(this->BackgroundContext.clone());
       Queue.work([&] { Rebuilder.idle(); });
     });
   }
 }
 
 BackgroundIndex::~BackgroundIndex() {

clang-tools-extra/clangd/index/BackgroundRebuild.h

 // etc. Without external locking, the rebuilt index may include more updates
 // than intended, which is fine.
 //
 // This class is exposed in the header so it can be tested.
 class BackgroundIndexRebuilder {
 public:
   BackgroundIndexRebuilder(SwapIndex *Target, FileSymbols *Source,
                            unsigned Threads)
-      : TUsBeforeFirstBuild(Threads), Target(Target), Source(Source) {}
+      : TUsBeforeFirstBuild(llvm::heavyweight_hardware_concurrency(Threads)
+                                .compute_thread_count()),
+        Target(Target), Source(Source) {}
 
   // Called to indicate a TU has been indexed.
   // May rebuild, if enough TUs have been indexed.
   void indexedTU();
   // Called to indicate that all worker threads are idle.
   // May reindex, if the index is not up to date.
   void idle();
   // Called to indicate we're going to load a batch of shards from disk.

clang/lib/Tooling/AllTUsExecution.cpp

llvm::Error AllTUsToolExecutor::execute(
   auto Count = [&]() {
     std::unique_lock<std::mutex> LockGuard(TUMutex);
     return ++Counter;
   };
 
   auto &Action = Actions.front();
 
   {
-    llvm::ThreadPool Pool(ThreadCount == 0 ? llvm::hardware_concurrency()
-                                           : ThreadCount);
+    llvm::ThreadPool Pool(llvm::hardware_concurrency(ThreadCount));
     for (std::string File : Files) {
       Pool.async(
           [&](std::string Path) {
             Log("[" + std::to_string(Count()) + "/" + TotalNumStr +
                 "] Processing file " + Path);
             // Each thread gets an indepent copy of a VFS to allow different
             // concurrent working directories.
             IntrusiveRefCntPtr<llvm::vfs::FileSystem> FS =

clang/lib/Tooling/DependencyScanning/DependencyScanningFilesystem.cpp

 
 DependencyScanningFilesystemSharedCache::
     DependencyScanningFilesystemSharedCache() {
   // This heuristic was chosen using a empirical testing on a
   // reasonably high core machine (iMacPro 18 cores / 36 threads). The cache
   // sharding gives a performance edge by reducing the lock contention.
   // FIXME: A better heuristic might also consider the OS to account for
   // the different cost of lock contention on different OSes.
-  NumShards = std::max(2u, llvm::hardware_concurrency() / 4);
+  NumShards =
+      std::max(2u, llvm::hardware_concurrency().compute_thread_count() / 4);
   CacheShards = std::make_unique<CacheShard[]>(NumShards);
 }
 
 /// Returns a cache entry for the corresponding key.
 ///
 /// A new cache entry is created if the key is not in the cache. This is a
 /// thread safe call.
 DependencyScanningFilesystemSharedCache::SharedFileSystemEntry &

clang/tools/clang-scan-deps/ClangScanDeps.cpp

AdjustingCompilations->appendArgumentsAdjuster(
       tooling::getClangStripSerializeDiagnosticAdjuster());
 
   SharedStream Errs(llvm::errs());
   // Print out the dependency results to STDOUT by default.
   SharedStream DependencyOS(llvm::outs());
 
   DependencyScanningService Service(ScanMode, Format, ReuseFileManager,
                                     SkipExcludedPPRanges);
-#if LLVM_ENABLE_THREADS
-  unsigned NumWorkers =
-      NumThreads == 0 ? llvm::hardware_concurrency() : NumThreads;
-#else
-  unsigned NumWorkers = 1;
-#endif
-  llvm::ThreadPool Pool(NumWorkers);
+  llvm::ThreadPool Pool(llvm::hardware_concurrency(NumThreads));
   std::vector<std::unique_ptr<DependencyScanningTool>> WorkerTools;
-  for (unsigned I = 0; I < NumWorkers; ++I)
+  for (unsigned I = 0; I < Pool.getThreadCount(); ++I)
     WorkerTools.push_back(std::make_unique<DependencyScanningTool>(Service));
 
   std::vector<SingleCommandCompilationDatabase> Inputs;
   for (tooling::CompileCommand Cmd :
        AdjustingCompilations->getAllCompileCommands())
     Inputs.emplace_back(Cmd);
 
   std::atomic<bool> HadErrors(false);
   FullDeps FD;
   std::mutex Lock;
   size_t Index = 0;
 
   if (Verbose) {
     llvm::outs() << "Running clang-scan-deps on " << Inputs.size()
-                 << " files using " << NumWorkers << " workers\n";
+                 << " files using " << Pool.getThreadCount() << " workers\n";
   }
-  for (unsigned I = 0; I < NumWorkers; ++I) {
+  for (unsigned I = 0; I < Pool.getThreadCount(); ++I) {
     Pool.async([I, &Lock, &Index, &Inputs, &HadErrors, &FD, &WorkerTools,
                 &DependencyOS, &Errs]() {
       llvm::StringSet<> AlreadySeenModules;
       while (true) {
         const SingleCommandCompilationDatabase *Input;
         std::string Filename;
         std::string CWD;
         size_t LocalIndex;

lld/ELF/SyntheticSections.cpp

createSymbols(ArrayRef<std::vector<GdbIndexSection::NameAttrEntry>> nameAttrs,
   }
 
   // The number of symbols we will handle in this function is of the order
   // of millions for very large executables, so we use multi-threading to
   // speed it up.
   size_t numShards = 32;
   size_t concurrency = 1;
   if (threadsEnabled)
-    concurrency =
-        std::min<size_t>(PowerOf2Floor(hardware_concurrency()), numShards);
+    concurrency = std::min<size_t>(
+        hardware_concurrency().compute_thread_count(), numShards);
 
   // A sharded map to uniquify symbols by name.
   std::vector<DenseMap<CachedHashStringRef, size_t>> map(numShards);
   size_t shift = 32 - countTrailingZeros(numShards);
 
   // Instantiate GdbSymbols while uniqufying them by name.
   std::vector<std::vector<GdbSymbol>> symbols(numShards);
   parallelForEachN(0, concurrency, [&](size_t threadId) {
void MergeNoTailSection::finalizeContents() {
   // Initializes string table builders.
   for (size_t i = 0; i < numShards; ++i)
     shards.emplace_back(StringTableBuilder::RAW, alignment);
 
   // Concurrency level. Must be a power of 2 to avoid expensive modulo
   // operations in the following tight loop.
   size_t concurrency = 1;
   if (threadsEnabled)
-    concurrency =
-        std::min<size_t>(PowerOf2Floor(hardware_concurrency()), numShards);
+    concurrency = std::min<size_t>(
+        hardware_concurrency().compute_thread_count(), numShards);
 
   // Add section pieces to the builders.
   parallelForEachN(0, concurrency, [&](size_t threadId) {
     for (MergeInputSection *sec : sections) {
       for (size_t i = 0, e = sec->pieces.size(); i != e; ++i) {
         if (!sec->pieces[i].live)
           continue;
         size_t shardId = getShardId(sec->pieces[i].hash);

llvm/include/llvm/LTO/LTO.h

 /// The details of this type definition aren't important; clients can only
 /// create a ThinBackend using one of the create*ThinBackend() functions below.
 using ThinBackend = std::function<std::unique_ptr<ThinBackendProc>(
     const Config &C, ModuleSummaryIndex &CombinedIndex,
     StringMap<GVSummaryMapTy> &ModuleToDefinedGVSummaries,
     AddStreamFn AddStream, NativeObjectCache Cache)>;
 
 /// This ThinBackend runs the individual backend jobs in-process.
-ThinBackend createInProcessThinBackend(unsigned ParallelismLevel);
+/// The default value means to use one job per hardware core (not hyper-thread).
+ThinBackend createInProcessThinBackend(unsigned ParallelismLevel = 0);
 
 /// This ThinBackend writes individual module indexes to files, instead of
 /// running the individual backend jobs. This backend is for distributed builds
 /// where separate processes will invoke the real backends.
 ///
 /// To find the path to write the index to, the backend checks if the path has a
 /// prefix of OldPrefix; if so, it replaces that prefix with NewPrefix. It then
 /// appends ".thinlto.bc" and writes the index to that path. If

llvm/include/llvm/Support/ThreadPool.h

 //===-- llvm/Support/ThreadPool.h - A ThreadPool implementation -*- 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
 //
 //===----------------------------------------------------------------------===//
 //
 // This file defines a crude C++11 based thread pool.
 //
 //===----------------------------------------------------------------------===//
 
 #ifndef LLVM_SUPPORT_THREAD_POOL_H
 #define LLVM_SUPPORT_THREAD_POOL_H
 
+#include "llvm/ADT/BitVector.h"
 #include "llvm/Config/llvm-config.h"
+#include "llvm/Support/Threading.h"
 #include "llvm/Support/thread.h"
 
 #include <future>
 
 #include <atomic>
 #include <condition_variable>
 #include <functional>
 #include <memory>
 #include <mutex>
 #include <queue>
 #include <utility>
 
 namespace llvm {
 
 /// A ThreadPool for asynchronous parallel execution on a defined number of
 /// threads.
 ///
 /// The pool keeps a vector of threads alive, waiting on a condition variable
 /// for some work to become available.
 class ThreadPool {
 public:
   using TaskTy = std::function<void()>;
   using PackagedTaskTy = std::packaged_task<void()>;
 
-  /// Construct a pool with the number of threads found by
-  /// hardware_concurrency().
-  ThreadPool();
-
-  /// Construct a pool of \p ThreadCount threads
-  ThreadPool(unsigned ThreadCount);
+  /// Construct a pool using the hardware strategy \p S for mapping hardware
+  /// execution resources (threads, cores, CPUs)
+  /// Defaults to using the maximum execution resources in the system, but
+  /// excluding any resources contained in the affinity mask.
+  ThreadPool(ThreadPoolStrategy S = hardware_concurrency());
 
   /// Blocking destructor: the pool will wait for all the threads to complete.
   ~ThreadPool();
 
   /// Asynchronous submission of a task to the pool. The returned future can be
   /// used to wait for the task to finish and is *non-blocking* on destruction.
   template <typename Function, typename... Args>
   inline std::shared_future<void> async(Function &&F, Args &&... ArgList) {
     auto Task =
         std::bind(std::forward<Function>(F), std::forward<Args>(ArgList)...);
     return asyncImpl(std::move(Task));
   }
 
   /// Asynchronous submission of a task to the pool. The returned future can be
   /// used to wait for the task to finish and is *non-blocking* on destruction.
   template <typename Function>
   inline std::shared_future<void> async(Function &&F) {
     return asyncImpl(std::forward<Function>(F));
   }
 
   /// Blocking wait for all the threads to complete and the queue to be empty.
   /// It is an error to try to add new tasks while blocking on this call.
   void wait();
 
+  unsigned getThreadCount() const { return ThreadCount; }
+
 private:
   /// Asynchronous submission of a task to the pool. The returned future can be
   /// used to wait for the task to finish and is *non-blocking* on destruction.
   std::shared_future<void> asyncImpl(TaskTy F);
 
   /// Threads in flight
   std::vector<llvm::thread> Threads;
 
private:
 
   /// Keep track of the number of thread actually busy
   std::atomic<unsigned> ActiveThreads;
 
 #if LLVM_ENABLE_THREADS // avoids warning for unused variable
   /// Signal for the destruction of the pool, asking thread to exit.
   bool EnableFlag;
 #endif
+
+  unsigned ThreadCount;
 };
 }
 
 #endif // LLVM_SUPPORT_THREAD_POOL_H

llvm/include/llvm/Support/Threading.h

 //===-- llvm/Support/Threading.h - Control multithreading mode --*- 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
 //
 //===----------------------------------------------------------------------===//
 //
 // This file declares helper functions for running LLVM in a multi-threaded
 // environment.
 //
 //===----------------------------------------------------------------------===//
 
 #ifndef LLVM_SUPPORT_THREADING_H
 #define LLVM_SUPPORT_THREADING_H
 
+#include "llvm/ADT/BitVector.h"
 #include "llvm/ADT/FunctionExtras.h"
 #include "llvm/ADT/SmallVector.h"
 #include "llvm/Config/llvm-config.h" // for LLVM_ON_UNIX
 #include "llvm/Support/Compiler.h"
 #include <ciso646> // So we can check the C++ standard lib macros.
 #include <functional>
 
 #if defined(_MSC_VER)
if (old_val == Uninitialized) {
         tmp = flag.status;
         sys::MemoryFence();
       }
     }
     TsanHappensAfter(&flag.status);
 #endif
   }
 
-  /// Get the amount of currency to use for tasks requiring significant
-  /// memory or other resources. Currently based on physical cores, if
-  /// available for the host system, otherwise falls back to
-  /// thread::hardware_concurrency().
-  /// Returns 1 when LLVM is configured with LLVM_ENABLE_THREADS=OFF
-  unsigned heavyweight_hardware_concurrency();
-
-  /// Get the number of threads that the current program can execute
-  /// concurrently. On some systems std::thread::hardware_concurrency() returns
-  /// the total number of cores, without taking affinity into consideration.
-  /// Returns 1 when LLVM is configured with LLVM_ENABLE_THREADS=OFF.
-  /// Fallback to std::thread::hardware_concurrency() if sched_getaffinity is
-  /// not available.
-  unsigned hardware_concurrency();
+  /// This tells how a thread pool will be used
+  class ThreadPoolStrategy {
+  public:
+    // The default value (0) means all available threads should be used,
+    // excluding affinity mask. If set, this value only represents a suggested
+    // high bound, the runtime might choose a lower value (not higher).
+    unsigned ThreadsRequested = 0;
+
+    // If SMT is active, use hyper threads. If false, there will be only one
+    // std::thread per core.
+    bool UseHyperThreads = true;
+
+    /// Retrieves the max available threads for the current strategy. This
+    /// accounts for affinity masks and takes advantage of all CPU sockets.
+    unsigned compute_thread_count() const;
+
+    /// Assign the current thread to an ideal hardware CPU or NUMA node. In a
+    /// multi-socket system, this ensures threads are assigned to all CPU
+    /// sockets. \p ThreadPoolNum represents a number bounded by [0,
+    /// compute_thread_count()).
+    void apply_thread_strategy(unsigned ThreadPoolNum) const;
+  };
+
+  /// Returns a thread strategy for tasks requiring significant memory or other
+  /// resources. To be used for workloads where hardware_concurrency() proves to
+  /// be less efficient. Avoid this strategy if doing lots of I/O. Currently
+  /// based on physical cores, if available for the host system, otherwise falls
+  /// back to hardware_concurrency(). Returns 1 when LLVM is configured with
+  /// LLVM_ENABLE_THREADS = OFF
+  inline ThreadPoolStrategy
+  heavyweight_hardware_concurrency(unsigned ThreadCount = 0) {
+    ThreadPoolStrategy S;
+    S.UseHyperThreads = false;
+    S.ThreadsRequested = ThreadCount;
+    return S;
+  }
+
+  /// Returns a default thread strategy where all available hardware ressources
+  /// are to be used, except for those initially excluded by an affinity mask.
+  /// This function takes affinity into consideration. Returns 1 when LLVM is
+  /// configured with LLVM_ENABLE_THREADS=OFF.
+  inline ThreadPoolStrategy hardware_concurrency(unsigned ThreadCount = 0) {
+    ThreadPoolStrategy S;
+    S.ThreadsRequested = ThreadCount;
+    return S;
+  }
 
   /// Return the current thread id, as used in various OS system calls.
   /// Note that not all platforms guarantee that the value returned will be
   /// unique across the entire system, so portable code should not assume
   /// this.
   uint64_t get_threadid();
 
   /// Get the maximum length of a thread name on this platform.
#endif
   /// Get the name of the current thread.  The level of support for
   /// getting a thread's name varies wildly across operating systems, and it
   /// is not even guaranteed that if you can successfully set a thread's name
   /// that you can later get it back.  This function is intended for diagnostic
   /// purposes, and as with setting a thread's name no indication of whether
   /// the operation succeeded or failed is returned.
   void get_thread_name(SmallVectorImpl<char> &Name);
 
+  /// Returns a mask that represents on which hardware thread, core, CPU, NUMA
+  /// group, the calling thread can be executed. On Windows, threads cannot
+  /// cross CPU boundaries.
+  llvm::BitVector get_thread_affinity_mask();
+
+  /// Returns how many physical CPUs or NUMA groups the system has.
+  unsigned get_cpus();
+
   enum class ThreadPriority {
     Background = 0,
     Default = 1,
   };
   /// If priority is Background tries to lower current threads priority such
   /// that it does not affect foreground tasks significantly. Can be used for
   /// long-running, latency-insensitive tasks to make sure cpu is not hogged by
   /// this task.
   /// If the priority is default tries to restore current threads priority to
   /// default scheduling priority.
   enum class SetThreadPriorityResult { FAILURE, SUCCESS };
   SetThreadPriorityResult set_thread_priority(ThreadPriority Priority);
 }
 
 #endif

llvm/lib/CodeGen/ParallelCG.cpp

if (!BCOSs.empty())
       WriteBitcodeToFile(*M, *BCOSs[0]);
     codegen(M.get(), *OSs[0], TMFactory, FileType);
     return M;
   }
 
   // Create ThreadPool in nested scope so that threads will be joined
   // on destruction.
   {
-    ThreadPool CodegenThreadPool(OSs.size());
+    ThreadPool CodegenThreadPool(hardware_concurrency(OSs.size()));
     int ThreadCount = 0;
 
     SplitModule(
         std::move(M), OSs.size(),
         [&](std::unique_ptr<Module> MPart) {
           // We want to clone the module in a new context to multi-thread the
           // codegen. We do it by serializing partition modules to bitcode
           // (while still on the main thread, in order to avoid data races) and

llvm/lib/DWARFLinker/DWARFLinker.cpp

bool DWARFLinker::link() {
   // in endDebugObject.
   if (Options.Threads == 1) {
     for (unsigned I = 0, E = NumObjects; I != E; ++I) {
       AnalyzeLambda(I);
       CloneLambda(I);
     }
     EmitLambda();
   } else {
-    ThreadPool Pool(2);
+    ThreadPool Pool(hardware_concurrency(2));
     Pool.async(AnalyzeAll);
     Pool.async(CloneAll);
     Pool.wait();
   }
 
   return true;
 }
 
 } // namespace llvm

llvm/lib/DebugInfo/GSYM/DwarfTransformer.cpp

if (NumThreads == 1) {
 
     // We need to call getAbbreviations sequentially first so that getUnitDIE()
     // only works with its local data.
     for (const auto &CU : DICtx.compile_units())
       CU->getAbbreviations();
 
     // Now parse all DIEs in case we have cross compile unit references in a
     // thread pool.
-    ThreadPool pool(NumThreads);
+    ThreadPool pool(hardware_concurrency(NumThreads));
     for (const auto &CU : DICtx.compile_units())
       pool.async([&CU]() { CU->getUnitDIE(false /*CUDieOnly*/); });
     pool.wait();
 
     // Now convert all DWARF to GSYM in a thread pool.
     std::mutex LogMutex;
     for (const auto &CU : DICtx.compile_units()) {
       DWARFDie Die = CU->getUnitDIE(false /*CUDieOnly*/);

llvm/lib/ExecutionEngine/Orc/LLJIT.cpp

else {
     }
     CompileLayer = std::make_unique<IRCompileLayer>(
         *ES, ObjTransformLayer, std::move(*CompileFunction));
     TransformLayer = std::make_unique<IRTransformLayer>(*ES, *CompileLayer);
   }
 
   if (S.NumCompileThreads > 0) {
     TransformLayer->setCloneToNewContextOnEmit(true);
-    CompileThreads = std::make_unique<ThreadPool>(S.NumCompileThreads);
+    CompileThreads =
+        std::make_unique<ThreadPool>(hardware_concurrency(S.NumCompileThreads));
     ES->setDispatchMaterialization(
         [this](JITDylib &JD, std::unique_ptr<MaterializationUnit> MU) {
           // FIXME: Switch to move capture once we have c++14.
           auto SharedMU = std::shared_ptr<MaterializationUnit>(std::move(MU));
           auto Work = [SharedMU, &JD]() { SharedMU->doMaterialize(JD); };
           CompileThreads->async(std::move(Work));
         });
   }

llvm/lib/LTO/LTO.cpp

LTO::RegularLTOState::RegularLTOState(unsigned ParallelCodeGenParallelismLevel,
                                       const Config &Conf)
     : ParallelCodeGenParallelismLevel(ParallelCodeGenParallelismLevel),
       Ctx(Conf), CombinedModule(std::make_unique<Module>("ld-temp.o", Ctx)),
       Mover(std::make_unique<IRMover>(*CombinedModule)) {}
 
 LTO::ThinLTOState::ThinLTOState(ThinBackend Backend)
     : Backend(Backend), CombinedIndex(/*HaveGVs*/ false) {
   if (!Backend)
-    this->Backend =
-        createInProcessThinBackend(llvm::heavyweight_hardware_concurrency());
+    this->Backend = createInProcessThinBackend();
 }
 
 LTO::LTO(Config Conf, ThinBackend Backend,
          unsigned ParallelCodeGenParallelismLevel)
     : Conf(std::move(Conf)),
       RegularLTO(ParallelCodeGenParallelismLevel, this->Conf),
       ThinLTO(std::move(Backend)) {}
 

 
 public:
   InProcessThinBackend(
       const Config &Conf, ModuleSummaryIndex &CombinedIndex,
       unsigned ThinLTOParallelismLevel,
       const StringMap<GVSummaryMapTy> &ModuleToDefinedGVSummaries,
       AddStreamFn AddStream, NativeObjectCache Cache)
       : ThinBackendProc(Conf, CombinedIndex, ModuleToDefinedGVSummaries),
-        BackendThreadPool(ThinLTOParallelismLevel),
+        BackendThreadPool(
+            heavyweight_hardware_concurrency(ThinLTOParallelismLevel)),
         AddStream(std::move(AddStream)), Cache(std::move(Cache)) {
     for (auto &Name : CombinedIndex.cfiFunctionDefs())
       CfiFunctionDefs.insert(
           GlobalValue::getGUID(GlobalValue::dropLLVMManglingEscape(Name)));
     for (auto &Name : CombinedIndex.cfiFunctionDecls())
       CfiFunctionDecls.insert(
           GlobalValue::getGUID(GlobalValue::dropLLVMManglingEscape(Name)));
   }

llvm/lib/LTO/LTOBackend.cpp

void codegen(const Config &Conf, TargetMachine *TM, AddStreamFn AddStream,
 
   if (DwoOut)
     DwoOut->keep();
 }
 
 void splitCodeGen(const Config &C, TargetMachine *TM, AddStreamFn AddStream,
                   unsigned ParallelCodeGenParallelismLevel,
                   std::unique_ptr<Module> Mod) {
-  ThreadPool CodegenThreadPool(ParallelCodeGenParallelismLevel);
+  ThreadPool CodegenThreadPool(
+      heavyweight_hardware_concurrency(ParallelCodeGenParallelismLevel));
   unsigned ThreadCount = 0;
   const Target *T = &TM->getTarget();
 
   SplitModule(
       std::move(Mod), ParallelCodeGenParallelismLevel,
       [&](std::unique_ptr<Module> MPart) {
         // We want to clone the module in a new context to multi-thread the
         // codegen. We do it by serializing partition modules to bitcode

llvm/lib/LTO/ThinLTOCodeGenerator.cpp

 extern cl::opt<std::string> RemarksFilename;
 extern cl::opt<std::string> RemarksPasses;
 extern cl::opt<bool> RemarksWithHotness;
 extern cl::opt<std::string> RemarksFormat;
 }
 
 namespace {
 
-static cl::opt<int>
-    ThreadCount("threads", cl::init(llvm::heavyweight_hardware_concurrency()));
+// Default to using one job per hardware core in the system
+static cl::opt<int> ThreadCount("threads", cl::init(0));
 
 // Simple helper to save temporary files for debug.
 static void saveTempBitcode(const Module &TheModule, StringRef TempDir,
                             unsigned count, StringRef Suffix) {
   if (TempDir.empty())
     return;
   // User asked to save temps, let dump the bitcode file after import.
   std::string SaveTempPath = (TempDir + llvm::Twine(count) + Suffix).str();
auto LSize =
         Modules[LeftIndex]->getSingleBitcodeModule().getBuffer().size();
     auto RSize =
         Modules[RightIndex]->getSingleBitcodeModule().getBuffer().size();
     return LSize > RSize;
   });
 
   // Parallel optimizer + codegen
   {
-    ThreadPool Pool(ThreadCount);
+    ThreadPool Pool(heavyweight_hardware_concurrency(ThreadCount));
     for (auto IndexCount : ModulesOrdering) {
       auto &Mod = Modules[IndexCount];
       Pool.async([&](int count) {
         auto ModuleIdentifier = Mod->getName();
         auto &ExportList = ExportLists[ModuleIdentifier];
 
         auto &DefinedGVSummaries = ModuleToDefinedGVSummaries[ModuleIdentifier];
 

llvm/lib/Support/Host.cpp

 #else
 StringRef sys::getHostCPUName() { return "generic"; }
 #endif
 
 #if defined(__linux__) && defined(__x86_64__)
 // On Linux, the number of physical cores can be computed from /proc/cpuinfo,
 // using the number of unique physical/core id pairs. The following
 // implementation reads the /proc/cpuinfo format on an x86_64 system.
-static int computeHostNumPhysicalCores() {
+int computeHostNumPhysicalCores() {
   // Read /proc/cpuinfo as a stream (until EOF reached). It cannot be
   // mmapped because it appears to have 0 size.
   llvm::ErrorOr<std::unique_ptr<llvm::MemoryBuffer>> Text =
       llvm::MemoryBuffer::getFileAsStream("/proc/cpuinfo");
   if (std::error_code EC = Text.getError()) {
     llvm::errs() << "Can't read "
                  << "/proc/cpuinfo: " << EC.message() << "\n";
     return -1;
   }
   SmallVector<StringRef, 8> strs;
   (*Text)->getBuffer().split(strs, "\n", /*MaxSplit=*/-1,
                              /*KeepEmpty=*/false);
   int CurPhysicalId = -1;
   int CurCoreId = -1;
   SmallSet<std::pair<int, int>, 32> UniqueItems;
   for (auto &Line : strs) {
int computeHostNumPhysicalCores() {
   }
   return UniqueItems.size();
 }
 #elif defined(__APPLE__) && defined(__x86_64__)
 #include <sys/param.h>
 #include <sys/sysctl.h>
 
 // Gets the number of *physical cores* on the machine.
-static int computeHostNumPhysicalCores() {
+int computeHostNumPhysicalCores() {
   uint32_t count;
   size_t len = sizeof(count);
   sysctlbyname("hw.physicalcpu", &count, &len, NULL, 0);
   if (count < 1) {
     int nm[2];
     nm[0] = CTL_HW;
     nm[1] = HW_AVAILCPU;
     sysctl(nm, 2, &count, &len, NULL, 0);
     if (count < 1)
       return -1;
   }
   return count;
 }
+#elif defined(_WIN32)
+// Defined in llvm/lib/Support/Windows/Threading.inc
+int computeHostNumPhysicalCores();
 #else
 // On other systems, return -1 to indicate unknown.
 static int computeHostNumPhysicalCores() { return -1; }
 #endif
 
 int sys::getHostNumPhysicalCores() {
   static int NumCores = computeHostNumPhysicalCores();
   return NumCores;
 }
 
 #if defined(__i386__) || defined(_M_IX86) || \

llvm/lib/Support/Parallel.cpp

public:
 
   static Executor *getDefaultExecutor();
 };
 
 /// An implementation of an Executor that runs closures on a thread pool
 ///   in filo order.
 class ThreadPoolExecutor : public Executor {
 public:
-  explicit ThreadPoolExecutor(unsigned ThreadCount = hardware_concurrency()) {
+  explicit ThreadPoolExecutor(ThreadPoolStrategy S = hardware_concurrency()) {
+    unsigned ThreadCount = S.compute_thread_count();
     // Spawn all but one of the threads in another thread as spawning threads
     // can take a while.
     Threads.reserve(ThreadCount);
     Threads.resize(1);
     std::lock_guard<std::mutex> Lock(Mutex);
-    Threads[0] = std::thread([&, ThreadCount] {
-      for (unsigned i = 1; i < ThreadCount; ++i) {
-        Threads.emplace_back([=] { work(); });
+    Threads[0] = std::thread([this, ThreadCount, S] {
+      for (unsigned I = 1; I < ThreadCount; ++I) {
+        Threads.emplace_back([=] { work(S, I); });
         if (Stop)
           break;
       }
       ThreadsCreated.set_value();
-      work();
+      work(S, 0);
     });
   }
 
   void stop() {
     {
       std::lock_guard<std::mutex> Lock(Mutex);
       if (Stop)
         return;
void add(std::function<void()> F) override {
     {
       std::lock_guard<std::mutex> Lock(Mutex);
       WorkStack.push(F);
     }
     Cond.notify_one();
   }
 
 private:
-  void work() {
+  void work(ThreadPoolStrategy S, unsigned ThreadID) {
+    S.apply_thread_strategy(ThreadID);
     while (true) {
       std::unique_lock<std::mutex> Lock(Mutex);
       Cond.wait(Lock, [&] { return Stop || !WorkStack.empty(); });
       if (Stop)
         break;
       auto Task = WorkStack.top();
       WorkStack.pop();
       Lock.unlock();

llvm/lib/Support/ThreadPool.cpp

 #include "llvm/Config/llvm-config.h"
 #include "llvm/Support/Threading.h"
 #include "llvm/Support/raw_ostream.h"
 
 using namespace llvm;
 
 #if LLVM_ENABLE_THREADS
 
-// Default to hardware_concurrency
-ThreadPool::ThreadPool() : ThreadPool(hardware_concurrency()) {}
-
-ThreadPool::ThreadPool(unsigned ThreadCount)
-    : ActiveThreads(0), EnableFlag(true) {
+ThreadPool::ThreadPool(ThreadPoolStrategy S)
+    : ActiveThreads(0), EnableFlag(true),
+      ThreadCount(S.compute_thread_count()) {
   // Create ThreadCount threads that will loop forever, wait on QueueCondition
   // for tasks to be queued or the Pool to be destroyed.
   Threads.reserve(ThreadCount);
   for (unsigned ThreadID = 0; ThreadID < ThreadCount; ++ThreadID) {
-    Threads.emplace_back([&] {
+    Threads.emplace_back([S, ThreadID, this] {
+      S.apply_thread_strategy(ThreadID);
       while (true) {
         PackagedTaskTy Task;
         {
           std::unique_lock<std::mutex> LockGuard(QueueLock);
           // Wait for tasks to be pushed in the queue
           QueueCondition.wait(LockGuard,
                               [&] { return !EnableFlag || !Tasks.empty(); });
           // Exit condition
ThreadPool::~ThreadPool() {
   }
   QueueCondition.notify_all();
   for (auto &Worker : Threads)
     Worker.join();
 }
 
 #else // LLVM_ENABLE_THREADS Disabled
 
-ThreadPool::ThreadPool() : ThreadPool(0) {}
-
 // No threads are launched, issue a warning if ThreadCount is not 0
-ThreadPool::ThreadPool(unsigned ThreadCount)
-    : ActiveThreads(0) {
-  if (ThreadCount) {
+ThreadPool::ThreadPool(ThreadPoolStrategy S)
+    : ActiveThreads(0), ThreadCount(S.compute_thread_count()) {
+  if (ThreadCount != 1) {
     errs() << "Warning: request a ThreadPool with " << ThreadCount
            << " threads, but LLVM_ENABLE_THREADS has been turned off\n";
   }
 }
 
 void ThreadPool::wait() {
   // Sequential implementation running the tasks
   while (!Tasks.empty()) {
     auto Task = std::move(Tasks.front());
     Tasks.pop();
     Task();
   }
 }
 
 std::shared_future<void> ThreadPool::asyncImpl(TaskTy Task) {
   // Get a Future with launch::deferred execution using std::async
   auto Future = std::async(std::launch::deferred, std::move(Task)).share();
   // Wrap the future so that both ThreadPool::wait() can operate and the
   // returned future can be sync'ed on.
   PackagedTaskTy PackagedTask([Future]() { Future.get(); });
   Tasks.push(std::move(PackagedTask));
   return Future;
 }
 
-ThreadPool::~ThreadPool() {
-  wait();
-}
+ThreadPool::~ThreadPool() { wait(); }
 
 #endif

llvm/lib/Support/Threading.cpp

#if LLVM_ENABLE_THREADS == 0 ||                                                \
     (!defined(_WIN32) && !defined(HAVE_PTHREAD_H))
 // Support for non-Win32, non-pthread implementation.
 void llvm::llvm_execute_on_thread(void (*Fn)(void *), void *UserData,
                                   llvm::Optional<unsigned> StackSizeInBytes) {
   (void)StackSizeInBytes;
   Fn(UserData);
 }
 
-unsigned llvm::heavyweight_hardware_concurrency() { return 1; }
-
-unsigned llvm::hardware_concurrency() { return 1; }
-
 uint64_t llvm::get_threadid() { return 0; }
 
 uint32_t llvm::get_max_thread_name_length() { return 0; }
 
 void llvm::set_thread_name(const Twine &Name) {}
 
 void llvm::get_thread_name(SmallVectorImpl<char> &Name) { Name.clear(); }
 
+llvm::BitVector llvm::get_thread_affinity_mask() { return {}; }
+
+unsigned llvm::ThreadPoolStrategy::compute_thread_count() const {
+  // When threads are disabled, ensure clients will loop at least once.
+  return 1;
+}
+
 #if LLVM_ENABLE_THREADS == 0
 void llvm::llvm_execute_on_thread_async(
     llvm::unique_function<void()> Func,
     llvm::Optional<unsigned> StackSizeInBytes) {
   (void)Func;
   (void)StackSizeInBytes;
   report_fatal_error("Spawning a detached thread doesn't make sense with no "
                      "threading support");
 }
 #else
 // Support for non-Win32, non-pthread implementation.
 void llvm::llvm_execute_on_thread_async(
     llvm::unique_function<void()> Func,
     llvm::Optional<unsigned> StackSizeInBytes) {
   (void)StackSizeInBytes;
   std::thread(std::move(Func)).detach();
 }
 #endif
 
 #else
 
-#include <thread>
-unsigned llvm::heavyweight_hardware_concurrency() {
-  // Since we can't get here unless LLVM_ENABLE_THREADS == 1, it is safe to use
-  // `std::thread` directly instead of `llvm::thread` (and indeed, doing so
-  // allows us to not define `thread` in the llvm namespace, which conflicts
-  // with some platforms such as FreeBSD whose headers also define a struct
-  // called `thread` in the global namespace which can cause ambiguity due to
-  // ADL.
-  int NumPhysical = sys::getHostNumPhysicalCores();
-  if (NumPhysical == -1)
-    return std::thread::hardware_concurrency();
-  return NumPhysical;
-}
-
-unsigned llvm::hardware_concurrency() {
-#if defined(HAVE_SCHED_GETAFFINITY) && defined(HAVE_CPU_COUNT)
-  cpu_set_t Set;
-  if (sched_getaffinity(0, sizeof(Set), &Set))
-    return CPU_COUNT(&Set);
-#endif
-  // Guard against std::thread::hardware_concurrency() returning 0.
-  if (unsigned Val = std::thread::hardware_concurrency())
-    return Val;
-  return 1;
+int computeHostNumHardwareThreads();
+
+unsigned llvm::ThreadPoolStrategy::compute_thread_count() const {
+  int MaxThreadCount = UseHyperThreads ? computeHostNumHardwareThreads()
+                                       : sys::getHostNumPhysicalCores();
+  if (MaxThreadCount <= 0)
+    MaxThreadCount = 1;
+
+  // No need to create more threads than there are hardware threads, it would
+  // uselessly induce more context-switching and cache eviction.
+  if (!ThreadsRequested || ThreadsRequested > (unsigned)MaxThreadCount)
+    return MaxThreadCount;
+  return ThreadsRequested;
 }
 
 namespace {
 struct SyncThreadInfo {
   void (*UserFn)(void *);
   void *UserData;
 };
 

llvm/lib/Support/Unix/Threading.inc

#elif defined(__APPLE__)
   return !setpriority(PRIO_DARWIN_THREAD, 0,
                       Priority == ThreadPriority::Background ? PRIO_DARWIN_BG
                                                              : 0)
              ? SetThreadPriorityResult::SUCCESS
              : SetThreadPriorityResult::FAILURE;
 #endif
   return SetThreadPriorityResult::FAILURE;
 }
+
+#include <thread>
+
+int computeHostNumHardwareThreads() {
+#if defined(HAVE_SCHED_GETAFFINITY) && defined(HAVE_CPU_COUNT)
+  cpu_set_t Set;
+  if (sched_getaffinity(0, sizeof(Set), &Set))
+    return CPU_COUNT(&Set);
+#endif
+  // Guard against std::thread::hardware_concurrency() returning 0.
+  if (unsigned Val = std::thread::hardware_concurrency())
+    return Val;
+  return 1;
+}
+
+void llvm::ThreadPoolStrategy::apply_thread_strategy(
+    unsigned ThreadPoolNum) const {}
+
+llvm::BitVector llvm::get_thread_affinity_mask() {
+  // FIXME: Implement
+  llvm_unreachable("Not implemented!");
+}
+
+unsigned llvm::get_cpus() { return 1; }

llvm/lib/Support/Windows/Threading.inc

 //===----------------------------------------------------------------------===//
 
 #include "llvm/ADT/SmallString.h"
 #include "llvm/ADT/Twine.h"
 
 #include "WindowsSupport.h"
 #include <process.h>
 
+#include <bitset>
+
 // Windows will at times define MemoryFence.
 #ifdef MemoryFence
 #undef MemoryFence
 #endif
 
 static unsigned __stdcall threadFuncSync(void *Arg) {
   SyncThreadInfo *TI = static_cast<SyncThreadInfo *>(Arg);
   TI->UserFn(TI->UserData);
SetThreadPriorityResult llvm::set_thread_priority(ThreadPriority Priority) {
   // processing mode.
   return SetThreadPriority(GetCurrentThread(),
                            Priority == ThreadPriority::Background
                                ? THREAD_MODE_BACKGROUND_BEGIN
                                : THREAD_MODE_BACKGROUND_END)
              ? SetThreadPriorityResult::SUCCESS
              : SetThreadPriorityResult::FAILURE;
 }
+
+struct ProcessorGroup {
+  unsigned ID;
+  unsigned AllThreads;
+  unsigned UsableThreads;
+  unsigned ThreadsPerCore;
+  uint64_t Affinity;
+};
+
+template <typename F>
+static bool IterateProcInfo(LOGICAL_PROCESSOR_RELATIONSHIP Relationship, F Fn) {
+  DWORD Len = 0;
+  BOOL R = ::GetLogicalProcessorInformationEx(Relationship, NULL, &Len);
+  if (R || GetLastError() != ERROR_INSUFFICIENT_BUFFER) {
+    return false;
+  }
+  auto *Info = (SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX *)calloc(1, Len);
+  R = ::GetLogicalProcessorInformationEx(Relationship, Info, &Len);
+  if (R) {
+    auto *End =
+        (SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX *)((uint8_t *)Info + Len);
+    for (auto *Curr = Info; Curr < End;
+         Curr = (SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX *)((uint8_t *)Curr +
+                                                            Curr->Size)) {
+      if (Curr->Relationship != Relationship)
+        continue;
+      Fn(Curr);
+    }
+  }
+  free(Info);
+  return true;
+}
+
+static ArrayRef<ProcessorGroup> getProcessorGroups() {
+  auto computeGroups = []() {
+    SmallVector<ProcessorGroup, 4> Groups;
+
+    auto HandleGroup = [&](SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX *ProcInfo) {
+      GROUP_RELATIONSHIP &El = ProcInfo->Group;
+      for (unsigned J = 0; J < El.ActiveGroupCount; ++J) {
+        ProcessorGroup G;
+        G.ID = Groups.size();
+        G.AllThreads = El.GroupInfo[J].MaximumProcessorCount;
+        G.UsableThreads = El.GroupInfo[J].ActiveProcessorCount;
+        assert(G.UsableThreads <= 64);
+        G.Affinity = El.GroupInfo[J].ActiveProcessorMask;
+        Groups.push_back(G);
+      }
+    };
+
+    if (!IterateProcInfo(RelationGroup, HandleGroup))
+      return std::vector<ProcessorGroup>();
+
+    auto HandleProc = [&](SYSTEM_LOGICAL_PROCESSOR_INFORMATION_EX *ProcInfo) {
+      PROCESSOR_RELATIONSHIP &El = ProcInfo->Processor;
+      assert(El.GroupCount == 1);
+      unsigned NumHyperThreads = 1;
+      // If the flag is set, each core supports more than one hyper-thread.
+      if (El.Flags & LTP_PC_SMT)
+        NumHyperThreads = std::bitset<64>(El.GroupMask[0].Mask).count();
+      unsigned I = El.GroupMask[0].Group;
+      Groups[I].ThreadsPerCore = NumHyperThreads;
+    };
+
+    if (!IterateProcInfo(RelationProcessorCore, HandleProc))
+      return std::vector<ProcessorGroup>();
+
+    // If there's an affinity mask set on one of the CPUs, then assume the user
+    // wants to constrain the current process to only a single CPU.
+    for (auto &G : Groups) {
+      if (G.UsableThreads != G.AllThreads) {
+        ProcessorGroup NewG{G};
+        Groups.clear();
+        Groups.push_back(NewG);
+        break;
+      }
+    }
+
+    return std::vector<ProcessorGroup>(Groups.begin(), Groups.end());
+  };
+  static auto Groups = computeGroups();
+  return ArrayRef<ProcessorGroup>(Groups);
+}
+
+template <typename R, typename UnaryPredicate>
+static unsigned aggregate(R &&Range, UnaryPredicate P) {
+  unsigned I{};
+  for (const auto &It : Range)
+    I += P(It);
+  return I;
+}
+
+// for sys::getHostNumPhysicalCores
+int computeHostNumPhysicalCores() {
+  static unsigned Cores =
+      aggregate(getProcessorGroups(), [](const ProcessorGroup &G) {
+        return G.UsableThreads / G.ThreadsPerCore;
+      });
+  return Cores;
+}
+
+int computeHostNumHardwareThreads() {
+  static unsigned Threads =
+      aggregate(getProcessorGroups(),
+                [](const ProcessorGroup &G) { return G.UsableThreads; });
+  return Threads;
+}
+
+// Assign the current thread to a more appropriate CPU socket or CPU group
+void llvm::ThreadPoolStrategy::apply_thread_strategy(
+    unsigned ThreadPoolNum) const {
+  ArrayRef<ProcessorGroup> Groups = getProcessorGroups();
+
+  assert(ThreadPoolNum < compute_thread_count() &&
+         "The thread index is not within thread strategy's range!");
+
+  // In this mode, the ThreadNumber represents the core number, not the
+  // hyper-thread number. Assumes all NUMA groups have the same amount of
+  // hyper-threads.
+  if (!UseHyperThreads)
+    ThreadPoolNum *= Groups[0].ThreadsPerCore;
+
+  unsigned ThreadRangeStart = 0;
+  for (unsigned I = 0; I < Groups.size(); ++I) {
+    const ProcessorGroup &G = Groups[I];
+    if (ThreadPoolNum >= ThreadRangeStart &&
+        ThreadPoolNum < ThreadRangeStart + G.UsableThreads) {
+
+      GROUP_AFFINITY Affinity{};
+      Affinity.Group = G.ID;
+      Affinity.Mask = G.Affinity;
+      SetThreadGroupAffinity(GetCurrentThread(), &Affinity, nullptr);
+    }
+    ThreadRangeStart += G.UsableThreads;
+  }
+}
+
+llvm::BitVector llvm::get_thread_affinity_mask() {
+  GROUP_AFFINITY Affinity{};
+  GetThreadGroupAffinity(GetCurrentThread(), &Affinity);
+
+  static unsigned All =
+      aggregate(getProcessorGroups(),
+                [](const ProcessorGroup &G) { return G.AllThreads; });
+
+  unsigned StartOffset =
+      aggregate(getProcessorGroups(), [&](const ProcessorGroup &G) {
+        return G.ID < Affinity.Group ? G.AllThreads : 0;
+      });
+
+  llvm::BitVector V;
+  V.resize(All);
+  for (unsigned I = 0; I < sizeof(KAFFINITY) * 8; ++I) {
+    if ((Affinity.Mask >> I) & 1)
+      V.set(StartOffset + I);
+  }
+  return V;
+}
+
+unsigned llvm::get_cpus() { return getProcessorGroups().size(); }

llvm/tools/dsymutil/dsymutil.cpp

if (opt::Arg *Toolchain = Args.getLastArg(OPT_toolchain))
     Options.Toolchain = Toolchain->getValue();
 
   if (Args.hasArg(OPT_assembly))
     Options.LinkOpts.FileType = OutputFileType::Assembly;
 
   if (opt::Arg *NumThreads = Args.getLastArg(OPT_threads))
     Options.LinkOpts.Threads = atoi(NumThreads->getValue());
   else
-    Options.LinkOpts.Threads = thread::hardware_concurrency();
+    Options.LinkOpts.Threads = 0; // Use all available hardware threads
 
   if (Options.DumpDebugMap || Options.LinkOpts.Verbose)
     Options.LinkOpts.Threads = 1;
 
   if (getenv("RC_DEBUG_OPTIONS"))
     Options.PaperTrailWarnings = true;
 
   if (opt::Arg *RemarksPrependPath = Args.getLastArg(OPT_remarks_prepend_path))
for (auto &InputFile : Options.InputFiles) {
     if (DebugMapPtrsOrErr->empty()) {
       WithColor::error() << "no architecture to link\n";
       return 1;
     }
 
     // Shared a single binary holder for all the link steps.
     BinaryHolder BinHolder;
 
-    unsigned ThreadCount =
-        std::min<unsigned>(Options.LinkOpts.Threads, DebugMapPtrsOrErr->size());
-    ThreadPool Threads(ThreadCount);
+    unsigned ThreadCount = Options.LinkOpts.Threads;
+    if (!ThreadCount)
+      ThreadCount = DebugMapPtrsOrErr->size();
+    ThreadPool Threads(hardware_concurrency(ThreadCount));
 
     // If there is more than one link to execute, we need to generate
     // temporary files.
     const bool NeedsTempFiles =
         !Options.DumpDebugMap && (Options.OutputFile != "-") &&
         (DebugMapPtrsOrErr->size() != 1 || Options.LinkOpts.Update);
     const bool Verify = Options.Verify && !Options.LinkOpts.NoOutput;
 

llvm/tools/gold/gold-plugin.cpp

enum OutputType {
     OT_BC_ONLY,
     OT_ASM_ONLY,
     OT_SAVE_TEMPS
   };
   static OutputType TheOutputType = OT_NORMAL;
   static unsigned OptLevel = 2;
   // Default parallelism of 0 used to indicate that user did not specify.
   // Actual parallelism default value depends on implementation.
-  // Currently only affects ThinLTO, where the default is
-  // llvm::heavyweight_hardware_concurrency.
+  // Currently only affects ThinLTO, where the default is the max cores in the
+  // system.
   static unsigned Parallelism = 0;
   // Default regular LTO codegen parallelism (number of partitions).
   static unsigned ParallelCodeGenParallelismLevel = 1;
 #ifdef NDEBUG
   static bool DisableVerify = true;
 #else
   static bool DisableVerify = false;
 #endif

llvm/tools/llvm-cov/CodeCoverage.cpp

int CodeCoverageTool::doShow(int argc, const char **argv,
   bool ShowFilenames =
       (SourceFiles.size() != 1) || ViewOpts.hasOutputDirectory() ||
       (ViewOpts.Format == CoverageViewOptions::OutputFormat::HTML);
 
   auto NumThreads = ViewOpts.NumThreads;
 
   // If NumThreads is not specified, auto-detect a good default.
   if (NumThreads == 0)
-    NumThreads =
-        std::max(1U, std::min(llvm::heavyweight_hardware_concurrency(),
-                              unsigned(SourceFiles.size())));
+    NumThreads = SourceFiles.size();
 
   if (!ViewOpts.hasOutputDirectory() || NumThreads == 1) {
     for (const std::string &SourceFile : SourceFiles)
       writeSourceFileView(SourceFile, Coverage.get(), Printer.get(),
                           ShowFilenames);
   } else {
     // In -output-dir mode, it's safe to use multiple threads to print files.
-    ThreadPool Pool(NumThreads);
+    ThreadPool Pool(heavyweight_hardware_concurrency(NumThreads));
     for (const std::string &SourceFile : SourceFiles)
       Pool.async(&CodeCoverageTool::writeSourceFileView, this, SourceFile,
                  Coverage.get(), Printer.get(), ShowFilenames);
     Pool.wait();
   }
 
   return 0;
 }

llvm/tools/llvm-cov/CoverageExporterJson.cpp

json::Object renderFile(const coverage::CoverageMapping &Coverage,
   return File;
 }
 
 json::Array renderFiles(const coverage::CoverageMapping &Coverage,
                         ArrayRef<std::string> SourceFiles,
                         ArrayRef<FileCoverageSummary> FileReports,
                         const CoverageViewOptions &Options) {
   auto NumThreads = Options.NumThreads;
-  if (NumThreads == 0) {
-    NumThreads = std::max(1U, std::min(llvm::heavyweight_hardware_concurrency(),
-                                       unsigned(SourceFiles.size())));
-  }
-  ThreadPool Pool(NumThreads);
+  if (NumThreads == 0)
+    NumThreads = SourceFiles.size();
+  ThreadPool Pool(heavyweight_hardware_concurrency(NumThreads));
   json::Array FileArray;
   std::mutex FileArrayMutex;
 
   for (unsigned I = 0, E = SourceFiles.size(); I < E; ++I) {
     auto &SourceFile = SourceFiles[I];
     auto &FileReport = FileReports[I];
     Pool.async([&] {
       auto File = renderFile(Coverage, SourceFile, FileReport, Options);

llvm/tools/llvm-cov/CoverageReport.cpp

std::vector<FileCoverageSummary> CoverageReport::prepareFileReports(
     const coverage::CoverageMapping &Coverage, FileCoverageSummary &Totals,
     ArrayRef<std::string> Files, const CoverageViewOptions &Options,
     const CoverageFilter &Filters) {
   unsigned LCP = getRedundantPrefixLen(Files);
   auto NumThreads = Options.NumThreads;
 
   // If NumThreads is not specified, auto-detect a good default.
   if (NumThreads == 0)
-    NumThreads =
-        std::max(1U, std::min(llvm::heavyweight_hardware_concurrency(),
-                              unsigned(Files.size())));
-
-  ThreadPool Pool(NumThreads);
+    NumThreads = Files.size();
+  ThreadPool Pool(heavyweight_hardware_concurrency(NumThreads));
 
   std::vector<FileCoverageSummary> FileReports;
   FileReports.reserve(Files.size());
 
   for (StringRef Filename : Files) {
     FileReports.emplace_back(Filename.drop_front(LCP));
     Pool.async(&CoverageReport::prepareSingleFileReport, Filename,
                &Coverage, Options, LCP, &FileReports.back(), &Filters);

llvm/tools/llvm-lto2/llvm-lto2.cpp

 static cl::opt<bool> SaveTemps("save-temps", cl::desc("Save temporary files"));
 
 static cl::opt<bool>
     ThinLTODistributedIndexes("thinlto-distributed-indexes", cl::init(false),
                               cl::desc("Write out individual index and "
                                        "import files for the "
                                        "distributed backend case"));
 
-static cl::opt<int> Threads("thinlto-threads",
-                            cl::init(llvm::heavyweight_hardware_concurrency()));
+// Default to using all hardware cores in the system.
+static cl::opt<int> Threads("thinlto-threads", cl::init(0));
 
 static cl::list<std::string> SymbolResolutions(
     "r",
     cl::desc("Specify a symbol resolution: filename,symbolname,resolution\n"
              "where \"resolution\" is a sequence (which may be empty) of the\n"
              "following characters:\n"
              " p - prevailing: the linker has chosen this definition of the\n"
              "     symbol\n"

llvm/tools/llvm-profdata/llvm-profdata.cpp

if (OutputFormat != PF_Binary && OutputFormat != PF_Compact_Binary &&
       OutputFormat != PF_Ext_Binary && OutputFormat != PF_Text)
     exitWithError("Unknown format is specified.");
 
   std::mutex ErrorLock;
   SmallSet<instrprof_error, 4> WriterErrorCodes;
 
   // If NumThreads is not specified, auto-detect a good default.
   if (NumThreads == 0)
-    NumThreads =
-        std::min(hardware_concurrency(), unsigned((Inputs.size() + 1) / 2));
+    NumThreads = std::min(hardware_concurrency().compute_thread_count(),
+                          unsigned((Inputs.size() + 1) / 2));
+  // FIXME: There's a bug here, where setting NumThreads = Inputs.size() fails
+  // the merge_empty_profile.test because the InstrProfWriter.ProfileKind isn't
+  // merged, thus the emitted file ends up with a PF_Unknown kind.
 
   // Initialize the writer contexts.
   SmallVector<std::unique_ptr<WriterContext>, 4> Contexts;
   for (unsigned I = 0; I < NumThreads; ++I)
     Contexts.emplace_back(std::make_unique<WriterContext>(
         OutputSparse, ErrorLock, WriterErrorCodes));
 
   if (NumThreads == 1) {
     for (const auto &Input : Inputs)
       loadInput(Input, Remapper, Contexts[0].get());
   } else {
-    ThreadPool Pool(NumThreads);
+    ThreadPool Pool(hardware_concurrency(NumThreads));
 
     // Load the inputs in parallel (N/NumThreads serial steps).
     unsigned Ctx = 0;
     for (const auto &Input : Inputs) {
       Pool.async(loadInput, Input, Remapper, Contexts[Ctx].get());
       Ctx = (Ctx + 1) % NumThreads;
     }
     Pool.wait();

llvm/unittests/Support/Host.cpp

 class HostTest : public testing::Test {
   Triple Host;
 
 protected:
   bool isSupportedArchAndOS() {
     // Initially this is only testing detection of the number of
     // physical cores, which is currently only supported/tested for
     // x86_64 Linux and Darwin.
-    return (Host.getArch() == Triple::x86_64 &&
+    return Host.isOSWindows() ||
+           (Host.getArch() == Triple::x86_64 &&
             (Host.isOSDarwin() || Host.getOS() == Triple::Linux));
   }
 
   HostTest() : Host(Triple::normalize(sys::getProcessTriple())) {}
 };
 
 TEST_F(HostTest, NumPhysicalCores) {
   int Num = sys::getHostNumPhysicalCores();

llvm/unittests/Support/TaskQueueTest.cpp

 using namespace llvm;
 
 class TaskQueueTest : public testing::Test {
 protected:
   TaskQueueTest() {}
 };
 
 TEST_F(TaskQueueTest, OrderedFutures) {
-  ThreadPool TP(1);
+  ThreadPool TP(hardware_concurrency(1));
   TaskQueue TQ(TP);
   std::atomic<int> X{ 0 };
   std::atomic<int> Y{ 0 };
   std::atomic<int> Z{ 0 };
 
   std::mutex M1, M2, M3;
   std::unique_lock<std::mutex> L1(M1);
   std::unique_lock<std::mutex> L2(M2);
TEST_F(TaskQueueTest, OrderedFutures) {
   L3.unlock();
   F3.wait();
   ASSERT_EQ(1, X);
   ASSERT_EQ(1, Y);
   ASSERT_EQ(1, Z);
 }
 
 TEST_F(TaskQueueTest, UnOrderedFutures) {
-  ThreadPool TP(1);
+  ThreadPool TP(hardware_concurrency(1));
   TaskQueue TQ(TP);
   std::atomic<int> X{ 0 };
   std::atomic<int> Y{ 0 };
   std::atomic<int> Z{ 0 };
   std::mutex M;
 
   std::unique_lock<std::mutex> Lock(M);
 
TEST_F(TaskQueueTest, UnOrderedFutures) {
 
   F3.wait();
   ASSERT_EQ(1, X);
   ASSERT_EQ(1, Y);
   ASSERT_EQ(1, Z);
 }
 
 TEST_F(TaskQueueTest, FutureWithReturnValue) {
-  ThreadPool TP(1);
+  ThreadPool TP(hardware_concurrency(1));
   TaskQueue TQ(TP);
   std::future<std::string> F1 = TQ.async([&] { return std::string("Hello"); });
   std::future<int> F2 = TQ.async([&] { return 42; });
 
   ASSERT_EQ(42, F2.get());
   ASSERT_EQ("Hello", F1.get());
 }
 #endif

llvm/unittests/Support/ThreadPool.cpp

 //========- unittests/Support/ThreadPools.cpp - ThreadPools.h tests --========//
 //
 // 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 "llvm/Support/ThreadPool.h"
 
+#include "llvm/ADT/DenseSet.h"
 #include "llvm/ADT/STLExtras.h"
 #include "llvm/ADT/SmallVector.h"
 #include "llvm/ADT/Triple.h"
 #include "llvm/Support/Host.h"
 #include "llvm/Support/TargetSelect.h"
+#include "llvm/Support/Threading.h"
 
 #include "gtest/gtest.h"
 
 using namespace llvm;
 
 // Fixture for the unittests, allowing to *temporarily* disable the unittests
 // on a particular platform
 class ThreadPoolTest : public testing::Test {
   Triple Host;
   SmallVector<Triple::ArchType, 4> UnsupportedArchs;
   SmallVector<Triple::OSType, 4> UnsupportedOSs;
   SmallVector<Triple::EnvironmentType, 1> UnsupportedEnvironments;
 protected:
   // This is intended for platform as a temporary "XFAIL"
   bool isUnsupportedOSOrEnvironment() {
     Triple Host(Triple::normalize(sys::getProcessTriple()));
 
     if (find(UnsupportedEnvironments, Host.getEnvironment()) !=
         UnsupportedEnvironments.end())
       return true;
 
     if (is_contained(UnsupportedOSs, Host.getOS()))
void setMainThreadReady() {
       std::unique_lock<std::mutex> LockGuard(WaitMainThreadMutex);
       MainThreadReady = true;
     }
     WaitMainThread.notify_all();
   }
 
   void SetUp() override { MainThreadReady = false; }
 
+  void TestAllThreads(ThreadPoolStrategy S);
+
   std::condition_variable WaitMainThread;
   std::mutex WaitMainThreadMutex;
   bool MainThreadReady = false;
 };
 
 #define CHECK_UNSUPPORTED() \
   do { \
     if (isUnsupportedOSOrEnvironment()) \
TEST_F(ThreadPoolTest, Async) {
   ASSERT_NE(2, i.load());
   setMainThreadReady();
   Pool.wait();
   ASSERT_EQ(2, i.load());
 }
 
 TEST_F(ThreadPoolTest, GetFuture) {
   CHECK_UNSUPPORTED();
-  ThreadPool Pool{2};
+  ThreadPool Pool(hardware_concurrency(2));
   std::atomic_int i{0};
   Pool.async([this, &i] {
     waitForMainThread();
     ++i;
   });
   // Force the future using get()
   Pool.async([&i] { ++i; }).get();
   ASSERT_NE(2, i.load());
for (size_t i = 0; i < 5; ++i) {
         ++checked_in;
       });
     }
     ASSERT_EQ(0, checked_in);
     setMainThreadReady();
   }
   ASSERT_EQ(5, checked_in);
 }
+
+#if LLVM_ENABLE_THREADS == 1
+
+void ThreadPoolTest::TestAllThreads(ThreadPoolStrategy S) {
+  // FIXME: Skip these tests on non-Windows because multi-socket system were not
+  // tested on Unix yet, and llvm::get_thread_affinity_mask() isn't implemented
+  // for Unix.
+  Triple Host(Triple::normalize(sys::getProcessTriple()));
+  if (!Host.isOSWindows())
+    return;
+
+  llvm::DenseSet<llvm::BitVector> ThreadsUsed;
+  std::mutex Lock;
+  unsigned Threads = 0;
+  {
+    ThreadPool Pool(S);
+    Threads = Pool.getThreadCount();
+    for (size_t I = 0; I < 10000; ++I) {
+      Pool.async([&] {
+        waitForMainThread();
+        std::lock_guard<std::mutex> Guard(Lock);
+        auto Mask = llvm::get_thread_affinity_mask();
+        ThreadsUsed.insert(Mask);
+      });
+    }
+    ASSERT_EQ(true, ThreadsUsed.empty());
+    setMainThreadReady();
+  }
+  ASSERT_EQ(llvm::get_cpus(), ThreadsUsed.size());
+}
+
+TEST_F(ThreadPoolTest, AllThreads_UseAllRessources) {
+  CHECK_UNSUPPORTED();
+  TestAllThreads({});
+}
+
+TEST_F(ThreadPoolTest, AllThreads_OneThreadPerCore) {
+  CHECK_UNSUPPORTED();
+  TestAllThreads(llvm::heavyweight_hardware_concurrency());
+}
+
+#endif

llvm/unittests/Support/Threading.cpp

 using namespace llvm;
 
 namespace {
 
 TEST(Threading, PhysicalConcurrency) {
   auto Num = heavyweight_hardware_concurrency();
   // Since Num is unsigned this will also catch us trying to
   // return -1.
-  ASSERT_LE(Num, thread::hardware_concurrency());
+  ASSERT_LE(Num.compute_thread_count(),
+            hardware_concurrency().compute_thread_count());
 }
 
 #if LLVM_ENABLE_THREADS
 
 class Notification {
 public:
   void notify() {
     {

mlir/lib/Pass/Pass.cpp

 
 // Run the held pipeline asynchronously across the functions within the module.
 void OpToOpPassAdaptorParallel::runOnOperation() {
   AnalysisManager am = getAnalysisManager();
 
   // Create the async executors if they haven't been created, or if the main
   // pipeline has changed.
   if (asyncExecutors.empty() || hasSizeMismatch(asyncExecutors.front(), mgrs))
-    asyncExecutors.assign(llvm::hardware_concurrency(), mgrs);
+    asyncExecutors.assign(llvm::hardware_concurrency().compute_thread_count(),
+                          mgrs);
 
   // Run a prepass over the module to collect the operations to execute over.
   // This ensures that an analysis manager exists for each operation, as well as
   // providing a queue of operations to execute over.
   std::vector<std::pair<Operation *, AnalysisManager>> opAMPairs;
   for (auto &region : getOperation()->getRegions()) {
     for (auto &block : region) {
       for (auto &op : block) {