C++多线程在Linux上的同步与异步混合使用

在Linux上，C++多线程的同步与异步混合使用可以通过多种方式实现。以下是一些常见的方法和技术：

1. 使用互斥锁（Mutex）

互斥锁是最基本的同步机制，用于保护共享资源。

#include <iostream>
#include <thread>
#include <mutex>

std::mutex mtx;
int shared_data = 0;

void thread_func() {
    std::unique_lock<std::mutex> lock(mtx);
    shared_data++;
    lock.unlock();
}

int main() {
    std::thread t1(thread_func);
    std::thread t2(thread_func);

    t1.join();
    t2.join();

    std::cout << "Shared data: " << shared_data << std::endl;
    return 0;
}

2. 使用条件变量（Condition Variable）

条件变量用于线程间的同步，允许线程等待某个条件成立。

#include <iostream>
#include <thread>
#include <mutex>
#include <condition_variable>

std::mutex mtx;
std::condition_variable cv;
int shared_data = 0;
bool ready = false;

void producer() {
    std::unique_lock<std::mutex> lock(mtx);
    shared_data = 42;
    ready = true;
    cv.notify_one();
}

void consumer() {
    std::unique_lock<std::mutex> lock(mtx);
    while (!ready) {
        cv.wait(lock);
    }
    std::cout << "Shared data: " << shared_data << std::endl;
}

int main() {
    std::thread t1(producer);
    std::thread t2(consumer);

    t1.join();
    t2.join();

    return 0;
}

3. 使用异步编程库（如Boost.Asio）

Boost.Asio是一个强大的异步I/O库，可以用于实现高效的异步操作。

#include <iostream>
#include <boost/asio.hpp>
#include <thread>

boost::asio::io_context io_context;

void async_operation(int id) {
    std::cout << "Thread " << id << " starting asynchronous operation." << std::endl;
    std::this_thread::sleep_for(std::chrono::seconds(1));
    std::cout << "Thread " << id << " completing asynchronous operation." << std::endl;
}

int main() {
    std::thread t1([&io_context]() { io_context.run(); });
    std::thread t2([&io_context]() { io_context.run(); });

    boost::asio::post(io_context, [id = 1]() { async_operation(id); });
    boost::asio::post(io_context, [id = 2]() { async_operation(id); });

    t1.join();
    t2.join();

    return 0;
}

4. 使用线程池（Thread Pool）

线程池可以有效地管理线程，避免频繁创建和销毁线程的开销。

#include <iostream>
#include <thread>
#include <vector>
#include <queue>
#include <functional>
#include <mutex>
#include <condition_variable>

class ThreadPool {
public:
    ThreadPool(size_t num_threads) : stop(false) {
        for (size_t i = 0; i < num_threads; ++i) {
            workers.emplace_back([this] {
                for (;;) {
                    std::function<void()> task;
                    {
                        std::unique_lock<std::mutex> lock(this->queue_mutex);
                        this->condition.wait(lock, [this] { return this->stop || !this->tasks.empty(); });
                        if (this->stop && this->tasks.empty()) {
                            return;
                        }
                        task = std::move(this->tasks.front());
                        this->tasks.pop();
                    }
                    task();
                }
            });
        }
    }

    ~ThreadPool() {
        {
            std::unique_lock<std::mutex> lock(queue_mutex);
            stop = true;
        }
        condition.notify_all();
        for (std::thread& worker : workers) {
            worker.join();
        }
    }

    template <class F, class... Args>
    void enqueue(F&& f, Args&&... args) {
        {
            std::unique_lock<std::mutex> lock(queue_mutex);
            tasks.emplace([f, args...] { f(args...); });
        }
        condition.notify_one();
    }

private:
    std::vector<std::thread> workers;
    std::queue<std::function<void()>> tasks;
    std::mutex queue_mutex;
    std::condition_variable condition;
    bool stop;
};

void thread_func(int id) {
    std::cout << "Thread " << id << " starting." << std::endl;
    std::this_thread::sleep_for(std::chrono::seconds(1));
    std::cout << "Thread " << id << " finishing." << std::endl;
}

int main() {
    ThreadPool pool(2);

    for (int i = 0; i < 4; ++i) {
        pool.enqueue(thread_func, i);
    }

    return 0;
}

总结

C++多线程的同步与异步混合使用可以通过互斥锁、条件变量、异步编程库（如Boost.Asio）和线程池等机制实现。选择合适的同步机制取决于具体的应用场景和需求。