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Homework02/README.md

@@ -129,10 +129,16 @@ int paraSumRed() {
 
 考虑一下前面提到的规约操作的两件事情，为了简化理解，我重新设置了 OpenMP 并行线程数 `OMP_NUM_THREADS` 为 2 (之前为4)，并对规约后的过程进行输出，可以发现都是 0,1,3,3,7 的组合，可见规约后的计算过程如下，
 
-![image-20201030214216195](/Users/fc10382/Library/Application Support/typora-user-images/image-20201030214216195.png)
+![规约后的双线程计算流程](https://pic.rmb.bdstatic.com/bjh/10de0e567bb7b86b94ece09dffa461fd.png)
 
 确实是规约操作的思想，采用reduction之后，每个线程根据 `reduction(+: sum)` 的声明算出自己的 `sum`，然后再将每个线程的`sum` 加起来。
 
 ## 总结
 
 规约操作通过将原始任务划分为多个子任务，并将子任务的结果合并以实现多线程下的并行计算，减少计算时间，避免并发一致性的问题。
+
+## 附录
+
+代码：
+
+- [for.cpp](./for.cpp)
\ No newline at end of file

Homework02/for.cpp

+#include <iostream>
+#include <omp.h> // OpenMP编程需要包含的头文件
+
+int paraSum() {
+    int sum = 0;
+    #pragma omp parallel for
+    for (int i = 0; i < 5; ++i) {
+        sum = sum + i;
+    }
+    return sum;
+}
+
+int paraSumRed() {
+    int sum = 0;
+//    std::cout << "Before: " << sum << std::endl;
+    #pragma omp parallel for reduction(+:sum)
+    for (int i = 0; i < 5; ++i) {
+        sum = sum + i;
+//        std::cout << sum << std::endl;
+    }
+//    std::cout << "After: " << sum << std::endl;
+    return sum;
+}
+
+int paraSumRedIO() {
+    int sum = 0;
+    std::cout << "Before: " << sum << std::endl;
+    #pragma omp parallel for reduction(+:sum)
+    for (int i = 0; i < 5; ++i) {
+        sum = sum + i;
+        std::cout << sum << std::endl;
+    }
+    std::cout << "After: " << sum << std::endl;
+    return sum;
+}
+
+int main() {
+//    int clicks = 1000000;
+//    int count = 0;
+//    for (int z = 0; z < clicks; z++) {
+//        //int sum = paraSum();
+//        int sum = paraSumRed();
+//        if (sum == 10)
+//            count++;
+//    }
+//    std::cout<<(double)count/clicks<<std::endl;
+    paraSumRedIO();
+    return 0;
+}