How do C++ functions support parallel computing?

C function parallel computing is implemented using threads, mutexes and parallel algorithms: Use threads and mutexes to synchronize tasks to avoid data competition. Use parallel algorithms to efficiently perform common tasks such as matrix multiplication. Combining these mechanisms allows you to write scalable and performant C code that meets modern computing needs.

Parallel Computing of C Functions: A Simple Introduction

In the modern computing world, parallel computing has become the solution to meet the ever-increasing computing needs. The essential. Parallel computing significantly improves program performance by distributing tasks to multiple processors. The C standard library provides powerful mechanisms to support function parallelism, allowing developers to easily write scalable, high-performance code.

Threads and mutexes

C uses threads to implement parallel computing. Threads are independent execution units in an application that can run concurrently. Mutexes are used to synchronize threads, ensure controlled access to shared resources, and avoid data races.

Syntax

In C, use the thread class and the launch function to create and launch threads. The syntax is as follows:

#include <thread>

using namespace std;

int main() {
  thread t([]() {
    // 子线程执行的代码
  });

  t.join();  // 等待子线程完成

  return 0;
}

Parallel algorithm

C The standard library provides many parallel algorithms that can perform common tasks in parallel. For example:

#include <algorithm>

vector<int> v;
transform(v.begin(), v.end(), v.begin(), [](int x) { return x * 2; });

Practical case: matrix multiplication

Consider a matrix multiplication problem in which two matrices A and B## The dimensions of # are m x n and n x p. The parallel algorithm for matrix multiplication is as follows:

vector<vector<int>> matrixMultiply(vector<vector<int>>& A, vector<vector<int>>& B) {
  int m = A.size(), n = A[0].size(), p = B[0].size();
  vector<vector<int>> C(m, vector<int>(p));

  // 为每个元素创建并启动线程
  for (int i = 0; i < m; ++i) {
    for (int j = 0; j < p; ++j) {
      thread t([i, j, &A, &B, &C]() {
        int sum = 0;
        for (int k = 0; k < n; ++k) {
          sum += A[i][k] * B[k][j];
        }
        C[i][j] = sum;
      });
      t.join();
    }
  }

  return C;
}

Conclusion

Through threads, mutexes and parallel algorithms, C provides a powerful mechanism to support parallel computing of functions. Developers can use these features to write scalable, high-performance code that efficiently meets modern computing needs.

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