OpenMP学习摘录

摘录归纳内容来自helloacm网站

1. Hello World 模式

#include <stdio.h>
 
int main() {
  #pragma omp parallel
  {
    printf("https://helloacm.com\n");     
  }
  printf("program is ending...");
  return 0;
}

注1：编译指令 gcc -O2 -o xxx.exe xxx.c -fopenmp

注2：花括号内的代码运行次数与CPU核心数相同。

2. 指定并行线程个数

#include <stdio.h>
int main() {
  #pragma omp parallel num_threads(3)
  {
    printf("https://helloacm.com\n");
  }
  return 0;
}

注1：花括号内的代码运行次数 = 3

3. 并行线程数可动态设定

#include <stdio.h>
int main() {
  int x = 1;
  int y = x + 2;
  #pragma omp parallel num_threads(y * 3)
  {
    printf("https://helloacm.com\n");
  }
  return 0;
}

4. 获得并行线程总数/当前线程ID

#include <stdio.h>
#include <omp.h>
 
int main() {
  #pragma omp parallel num_threads(3)
  {
    int id = omp_get_thread_num();
    int data = id;
    int total = omp_get_num_threads();
    printf("Greetings from process %d out of %d with Data %d\n", id, total, data);
  }
  printf("parallel for ends.\n");
  return 0;
}

注1：这里需要导入头文件omp.h

注2：omp花括号内的变量为局部线程变量，多线程有多个拷贝。

#include <stdio.h>
#include <omp.h>
 
int main() {
  int data;
  #pragma omp parallel num_threads(3)
  {
    int id = omp_get_thread_num();
    data = id; // threads may interleaving the modification
    int total = omp_get_num_threads();
    printf("Greetings from process %d out of %d with Data %d\n", id, total, data);
  }
  printf("parallel for ends.\n");
  return 0;
}

注1：上面这段代码存在问题，多个线程在修改同一个全局变量data！！

#include <stdio.h>
#include <omp.h>
int main() {
  int data, id, total;
  // each thread has its own copy of data, id and total.
  #pragma omp parallel private(data, id, total) num_threads(6) 
  {
    printf("local data=%d\n", data);
    id = omp_get_thread_num();
    total = omp_get_num_threads();
    data = id;      
    printf("Greetings from process %d out of %d with Data %d\n", id, total, data);
  }
  printf("data=%d, id=%d, total=%d\n", data, id, total);
  printf("parallel for ends.\n");
  return 0;
}

注1：输出全是0，因为没有代码修改过这些全局变量。

注2：实际上这段代码与之前第一段代码毫无区别，线程私有变量虽与全局变量同名，但即便是在进入omp线程时，同名私有变量也没有拷贝共有变量的数值。

 5. 临界区

#include <stdio.h>
#include <omp.h>
 
int main() {
  int data;
  #pragma omp parallel num_threads(3)
  {
    int id = omp_get_thread_num();    
    int total = omp_get_num_threads();
    #pragma omp critical 
    { // make sure only 1 thread exectutes the critical section at a time.
        data = id; // threads may interleaving the modification
        printf("Greetings from process %d out of %d with Data %d\n", id, total, data);
    }
  }
  printf("parallel for ends.\n");
  return 0;
}

注1：并行编程常会遇到资源竞争和协调的问题，于是就有各种策略来保证程序运行的可控性。

注2：在并行线程中对部分代码加锁（超市里n个人同时购物，但只有一个收银员，一次只能服务一人）

6. 进阶学习网站

• 　https://computing.llnl.gov/tutorials/openMP/

标签：num,int,学习,omp,printf,OpenMP,data,id,摘录
来源： https://www.cnblogs.com/zbnbu/p/10987938.html