5b1be75929
ThreadPoolExecutor is the only implementation. Remove the Executor base class so that add() and getThreadCount() are direct calls instead of virtual dispatches.
277 lines
8.3 KiB
C++
277 lines
8.3 KiB
C++
//===- llvm/Support/Parallel.cpp - Parallel algorithms --------------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#include "llvm/Support/Parallel.h"
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#include "llvm/ADT/ScopeExit.h"
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#include "llvm/Config/llvm-config.h"
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#include "llvm/Support/ExponentialBackoff.h"
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#include "llvm/Support/Jobserver.h"
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#include "llvm/Support/ManagedStatic.h"
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#include "llvm/Support/Threading.h"
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#include <atomic>
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#include <future>
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#include <memory>
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#include <mutex>
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#include <thread>
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#include <vector>
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using namespace llvm;
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using namespace llvm::parallel;
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llvm::ThreadPoolStrategy parallel::strategy;
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#if LLVM_ENABLE_THREADS
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#ifdef _WIN32
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static thread_local unsigned threadIndex = UINT_MAX;
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unsigned parallel::getThreadIndex() { GET_THREAD_INDEX_IMPL; }
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#else
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thread_local unsigned parallel::threadIndex = UINT_MAX;
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#endif
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namespace {
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/// Runs closures on a thread pool in filo order.
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class ThreadPoolExecutor {
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public:
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explicit ThreadPoolExecutor(ThreadPoolStrategy S) {
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if (S.UseJobserver)
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TheJobserver = JobserverClient::getInstance();
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ThreadCount = S.compute_thread_count();
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// Spawn all but one of the threads in another thread as spawning threads
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// can take a while.
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Threads.reserve(ThreadCount);
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Threads.resize(1);
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std::lock_guard<std::mutex> Lock(Mutex);
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// Use operator[] before creating the thread to avoid data race in .size()
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// in 'safe libc++' mode.
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auto &Thread0 = Threads[0];
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Thread0 = std::thread([this, S] {
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for (unsigned I = 1; I < ThreadCount; ++I) {
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Threads.emplace_back([this, S, I] { work(S, I); });
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if (Stop)
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break;
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}
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ThreadsCreated.set_value();
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work(S, 0);
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});
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}
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// To make sure the thread pool executor can only be created with a parallel
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// strategy.
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ThreadPoolExecutor() = delete;
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void stop() {
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{
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std::lock_guard<std::mutex> Lock(Mutex);
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if (Stop)
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return;
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Stop = true;
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}
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Cond.notify_all();
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ThreadsCreated.get_future().wait();
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std::thread::id CurrentThreadId = std::this_thread::get_id();
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for (std::thread &T : Threads)
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if (T.get_id() == CurrentThreadId)
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T.detach();
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else
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T.join();
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}
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~ThreadPoolExecutor() { stop(); }
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struct Creator {
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static void *call() { return new ThreadPoolExecutor(strategy); }
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};
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struct Deleter {
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static void call(void *Ptr) { ((ThreadPoolExecutor *)Ptr)->stop(); }
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};
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void add(std::function<void()> F) {
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{
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std::lock_guard<std::mutex> Lock(Mutex);
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WorkStack.push_back(std::move(F));
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}
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Cond.notify_one();
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}
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size_t getThreadCount() const { return ThreadCount; }
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private:
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void work(ThreadPoolStrategy S, unsigned ThreadID) {
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threadIndex = ThreadID;
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S.apply_thread_strategy(ThreadID);
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// Note on jobserver deadlock avoidance:
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// GNU Make grants each invoked process one implicit job slot. Our
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// JobserverClient models this by returning an implicit JobSlot on the
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// first successful tryAcquire() in a process. This guarantees forward
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// progress without requiring a dedicated "always-on" thread here.
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while (true) {
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if (TheJobserver) {
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// Jobserver-mode scheduling:
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// - Acquire one job slot (with exponential backoff to avoid busy-wait).
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// - While holding the slot, drain and run tasks from the local queue.
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// - Release the slot when the queue is empty or when shutting down.
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// Rationale: Holding a slot amortizes acquire/release overhead over
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// multiple tasks and avoids requeue/yield churn, while still enforcing
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// the jobserver’s global concurrency limit. With K available slots,
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// up to K workers run tasks in parallel; within each worker tasks run
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// sequentially until the local queue is empty.
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ExponentialBackoff Backoff(std::chrono::hours(24));
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JobSlot Slot;
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do {
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if (Stop)
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return;
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Slot = TheJobserver->tryAcquire();
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if (Slot.isValid())
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break;
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} while (Backoff.waitForNextAttempt());
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llvm::scope_exit SlotReleaser(
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[&] { TheJobserver->release(std::move(Slot)); });
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while (true) {
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std::function<void()> Task;
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{
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std::unique_lock<std::mutex> Lock(Mutex);
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Cond.wait(Lock, [&] { return Stop || !WorkStack.empty(); });
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if (Stop && WorkStack.empty())
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return;
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if (WorkStack.empty())
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break;
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Task = std::move(WorkStack.back());
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WorkStack.pop_back();
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}
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Task();
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}
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} else {
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std::unique_lock<std::mutex> Lock(Mutex);
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Cond.wait(Lock, [&] { return Stop || !WorkStack.empty(); });
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if (Stop)
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break;
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auto Task = std::move(WorkStack.back());
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WorkStack.pop_back();
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Lock.unlock();
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Task();
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}
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}
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}
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std::atomic<bool> Stop{false};
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std::vector<std::function<void()>> WorkStack;
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std::mutex Mutex;
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std::condition_variable Cond;
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std::promise<void> ThreadsCreated;
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std::vector<std::thread> Threads;
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unsigned ThreadCount;
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JobserverClient *TheJobserver = nullptr;
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};
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} // namespace
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static ThreadPoolExecutor *getDefaultExecutor() {
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#ifdef _WIN32
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// The ManagedStatic enables the ThreadPoolExecutor to be stopped via
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// llvm_shutdown() on Windows. This is important to avoid various race
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// conditions at process exit that can cause crashes or deadlocks.
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static ManagedStatic<ThreadPoolExecutor, ThreadPoolExecutor::Creator,
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ThreadPoolExecutor::Deleter>
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ManagedExec;
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static std::unique_ptr<ThreadPoolExecutor> Exec(&(*ManagedExec));
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return Exec.get();
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#else
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// ManagedStatic is not desired on other platforms. When `Exec` is destroyed
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// by llvm_shutdown(), worker threads will clean up and invoke TLS
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// destructors. This can lead to race conditions if other threads attempt to
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// access TLS objects that have already been destroyed.
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static ThreadPoolExecutor Exec(strategy);
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return &Exec;
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#endif
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}
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size_t parallel::getThreadCount() {
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return getDefaultExecutor()->getThreadCount();
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}
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#endif
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// Latch::sync() called by the dtor may cause one thread to block. If is a dead
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// lock if all threads in the default executor are blocked. To prevent the dead
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// lock, only allow the root TaskGroup to run tasks parallelly. In the scenario
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// of nested parallel_for_each(), only the outermost one runs parallelly.
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TaskGroup::TaskGroup()
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: Parallel(
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#if LLVM_ENABLE_THREADS
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strategy.ThreadsRequested != 1 && threadIndex == UINT_MAX
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#else
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false
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#endif
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) {
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}
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TaskGroup::~TaskGroup() {
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// We must ensure that all the workloads have finished before decrementing the
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// instances count.
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L.sync();
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}
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void TaskGroup::spawn(std::function<void()> F) {
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#if LLVM_ENABLE_THREADS
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if (Parallel) {
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L.inc();
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getDefaultExecutor()->add([&, F = std::move(F)] {
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F();
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L.dec();
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});
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return;
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}
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#endif
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F();
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}
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void llvm::parallelFor(size_t Begin, size_t End,
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function_ref<void(size_t)> Fn) {
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#if LLVM_ENABLE_THREADS
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if (strategy.ThreadsRequested != 1) {
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size_t NumItems = End - Begin;
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if (NumItems == 0)
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return;
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// Distribute work via an atomic counter shared by NumWorkers threads,
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// keeping the task count (and thus Linux futex calls) at O(ThreadCount)
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// For lld, per-file work is somewhat uneven, so a multipler > 1 is safer.
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// While 2 vs 4 vs 8 makes no measurable difference, 4 is used as a
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// reasonable default.
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size_t NumWorkers = std::min<size_t>(NumItems, getThreadCount());
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size_t ChunkSize = std::max(size_t(1), NumItems / (NumWorkers * 4));
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std::atomic<size_t> Idx{Begin};
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auto Worker = [&] {
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while (true) {
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size_t I = Idx.fetch_add(ChunkSize, std::memory_order_relaxed);
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if (I >= End)
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break;
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size_t IEnd = std::min(I + ChunkSize, End);
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for (; I < IEnd; ++I)
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Fn(I);
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}
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};
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TaskGroup TG;
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for (size_t I = 0; I != NumWorkers; ++I)
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TG.spawn(Worker);
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return;
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}
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#endif
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for (; Begin != End; ++Begin)
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Fn(Begin);
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}
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