因爲工程需要處理大量的圖片,這段時間看了一下C++多線程的相關內容,並參照網上寫的多線程類,運用到自己的工程中。
一 多線程
https://blog.csdn.net/invincibleFF/article/details/80048868 這篇文章介紹的很詳細。關於多線程是什麼。在計算時間相對較長,計算量相對較大的並行計算時,使用多線程可以極大的提高運算速度。
二 多線程的使用
我在網上找的一個多線程類ThreadPool.h,代碼如下(如果該代碼原作者看到,請留言,由於時間很長,是在找不到原作者了。):
#ifndef THREAD_POOL_H
#define THREAD_POOL_H
#include <vector>
#include <queue>
#include <memory>
#include <thread>
#include <mutex>
#include <condition_variable>
#include <future>
#include <functional>
#include <stdexcept>
class ThreadPool {
public:
ThreadPool(size_t);
template<class F, class... Args>
auto enqueue(F&& f, Args&&... args)
->std::future<typename std::result_of<F(Args...)>::type>;
~ThreadPool();
private:
// need to keep track of threads so we can join them
std::vector< std::thread > workers;
// the task queue
std::queue< std::function<void()> > tasks;
// synchronization
std::mutex queue_mutex;
std::condition_variable condition;
bool stop;
};
// the constructor just launches some amount of workers
inline ThreadPool::ThreadPool(size_t threads)
: stop(false)
{
for (size_t i = 0; i < 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();
}
}
);
}
// add new work item to the pool
template<class F, class... Args>
auto ThreadPool::enqueue(F&& f, Args&&... args)
-> std::future<typename std::result_of<F(Args...)>::type>
{
using return_type = typename std::result_of<F(Args...)>::type;
auto task = std::make_shared< std::packaged_task<return_type()> >(
std::bind(std::forward<F>(f), std::forward<Args>(args)...)
);
std::future<return_type> res = task->get_future();
{
std::unique_lock<std::mutex> lock(queue_mutex);
// don't allow enqueueing after stopping the pool
if (stop)
throw std::runtime_error("enqueue on stopped ThreadPool");
tasks.emplace([task](){ (*task)(); });
}
condition.notify_one();
return res;
}
// the destructor joins all threads
inline ThreadPool::~ThreadPool()
{
{
std::unique_lock<std::mutex> lock(queue_mutex);
stop = true;
}
condition.notify_all();
for (std::thread &worker : workers)
worker.join();
}
#endif
直接添加這個類。
應用:
double terr(int i)
{
double area_i = i* i * 3.14;
area_i = area_i*area_i;
return area_i;
}
void main()
{
std::mutex mutex_tmp;
float startTime0, endTime0;
//定義線程數
int tread_num = 10;
ThreadPool pool(tread_num);
///任務隊列 放任務函數
std::vector< std::future<double> > results;
for (int i = 0; i != 1000000; i++)
{
results.emplace_back(pool.enqueue(bind(terr, i)));
}
//計時
startTime0 = omp_get_wtime();
vector<std::future<double>>::iterator result;
for (result = results.begin(); result != results.end(); result++)
{
mutex_tmp.lock();
result->get();
mutex_tmp.unlock();
}
endTime0 = omp_get_wtime();
cout << tread_num << "個線程處理時間爲 : " << endTime0 - startTime0 << endl;
system("pause");
return;
}
results.emplace_back(pool.enqueue(bind(terr, i)));將任務函數放到隊列中。並使用result->get();得到最後的計算結果。
以上是C++實現多線程計算的一種方式。還有使用openmp的方式:https://blog.csdn.net/zcgyq/article/details/83088324可以參考這篇博文,關於openmp的用法更爲簡單。
下面介紹QT多線程用法。