C++ Concurrent Programming: How to use parallel libraries (like OpenMP)?

Concurrent programming improves program performance by using multiple processors. OpenMP is a parallel programming library that provides instructions to support the creation and management of concurrent tasks, including creating parallel regions, parallel for loops, critical sections and barriers.

C Concurrent Programming: Mastering Parallel Libraries (such as OpenMP)

Concurrent Programming Basics

Concurrent programming involves creating and managing multiple executions at the same time task program. By leveraging multiple processors or processor cores, concurrent programming can significantly improve application performance.

Introduction to OpenMP

OpenMP is a widely used open source parallel programming library that provides support for parallelizing C, C, and Fortran programs. OpenMP provides many functions and directives for creating and managing concurrent tasks.

OpenMP basic instructions

The following are some basic instructions of OpenMP:

• #pragma omp parallel: Create a parallel region in which the code Will be executed in parallel by multiple threads.
• #pragma omp for: Creates a parallel for loop where loop iterations will be processed in parallel by multiple threads.
• #pragma omp critical: Create a critical section to ensure that only one thread can execute the code block in it at a time.
• #pragma omp barrier: Sets a barrier to ensure that all threads have reached this point before continuing execution.

Practical Case

Consider the following C program that uses OpenMP to perform parallel summation:

#include <iostream>
#include <omp.h>

int main() {
  int n = 10000000;
  int sum = 0;

  // 创建一个并行区域
  #pragma omp parallel
  {
    // 每条线程计算其部分和
    #pragma omp for reduction(+:sum)
    for (int i = 0; i < n; i++) {
      sum += i;
    }
  }

  std::cout << "总和为：" << sum << std::endl;

  return 0;
}

Conclusion

OpenMP provides a set of powerful Tools for creating and managing parallel programs. By following these basic instructions, you can take advantage of multiple processors or processors to improve application performance.

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