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HomeBackend DevelopmentC++How do C++ functions improve performance in concurrent programming?

How do C++ functions improve performance in concurrent programming?

Apr 27, 2024 pm 09:03 PM
c++Concurrent programmingconcurrent access

Methods to improve concurrent programming performance in C include: Parallel execution: Use std::thread to create threads that execute tasks in parallel. Lock operation: Use std::mutex to protect shared data from concurrent access. Condition variables: Use std::condition_variable and std::mutex to achieve synchronization between threads. Atomic operations: Use the std::atomic type to provide thread-safe counters or other variables.

C++ 函数在并发编程中如何提升性能?

How C functions improve performance in concurrent programming

Introduction
In concurrent programming , threads can perform tasks simultaneously, thereby improving overall performance. C provides a variety of functions that can help developers optimize the performance of concurrent code.

Parallel execution

#include <thread>

void task() {
  // 并行执行的任务
}

int main() {
  std::thread t(task);
  t.join();
  return 0;
}

Lock operation

#include <mutex>

std::mutex m;
void task() {
  std::lock_guard<std::mutex> lock(m);
  // 受保护的任务
}

int main() {
  std::thread t(task);
  t.join();
  return 0;
}

Condition variable

#include <condition_variable>

std::condition_variable cv;
std::mutex m;
void producer() {
  std::unique_lock<std::mutex> lock(m);
  // 生产数据
  cv.notify_one();
}

void consumer() {
  std::unique_lock<std::mutex> lock(m);
  cv.wait(lock);
  // 消费数据
}

int main() {
  std::thread t1(producer);
  std::thread t2(consumer);
  t1.join();
  t2.join();
  return 0;
}

Atomic operations

#include <atomic>

std::atomic<int> counter(0);
void task() {
  counter++;
}

int main() {
  std::thread t1(task);
  std::thread t2(task);
  t1.join();
  t2.join();
  std::cout << "Counter: " << counter << std::endl;
  return 0;
}

Practical case
Consider an image processing application that requires the conversion of a large number of images. Using concurrency techniques can significantly increase processing speed. Developers can use std::thread to convert multiple images simultaneously on multiple threads, thereby reducing the total execution time.

Conclusion
The functions provided by C can help developers write efficient concurrent code. Understanding the correct usage of these functions is critical to optimizing the performance of concurrent applications.

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