ncnn刚发布不久，博主在ios下尝试编译。

遇上了openmp的编译问题。

寻找各种解决方案无果，亲自操刀。

采用std::thread 替换 openmp。

ncnn项目地址:

后来询问ncnn的作者才知道在ios下的编译方法。

至此，当时的临时方案 采用std::thread 替换 openmp。

想想也许在一些特定情况下还是比较适用的，当前方便两者之间进行切换验证。

抽空写了一个示例项目。

项目地址:

贴上完整代码:

#include 
     
      #include 
      
          #include 
       
        #if defined(_OPENMP)// compile with: /openmp  #include 
        
         auto const epoch = omp_get_wtime();double now() {    return omp_get_wtime() - epoch;};#else #include 
         
          auto const epoch = std::chrono::steady_clock::now();double now() {    return std::chrono::duration_cast
          
           (std::chrono::steady_clock::now() - epoch).count() / 1000.0;};#endiftemplate
           
            double bench(const FN &fn) { auto took = -now(); return (fn(), took + now());}#include 
            
             #if defined(_OPENMP)# include 
             
              #else #include 
              
               #include 
               
                #endif#ifdef _OPENMPstatic int processorCount = static_cast
                
                 (omp_get_num_procs());#elsestatic int processorCount = static_cast
                 
                  (std::thread::hardware_concurrency());#endifstatic void ParallelFor(int inclusiveFrom, int exclusiveTo, std::function
                  
                    func){#if defined(_OPENMP)#pragma omp parallel for num_threads(processorCount) for (int i = inclusiveFrom; i < exclusiveTo; ++i) { func(i); } return;#else if (inclusiveFrom >= exclusiveTo) return; static size_t thread_cnt = 0; if (thread_cnt == 0) { thread_cnt = std::thread::hardware_concurrency(); } size_t entry_per_thread = (exclusiveTo - inclusiveFrom) / thread_cnt; if (entry_per_thread < 1) { for (int i = inclusiveFrom; i < exclusiveTo; ++i) { func(i); } return; } std::vector
                   
                     threads; int start_idx, end_idx; for (start_idx = inclusiveFrom; start_idx < exclusiveTo; start_idx += entry_per_thread) { end_idx = start_idx + entry_per_thread; if (end_idx > exclusiveTo) end_idx = exclusiveTo; threads.emplace_back([&](size_t from, size_t to) { for (size_t entry_idx = from; entry_idx < to; ++entry_idx) func(entry_idx); }, start_idx, end_idx); } for (auto& t : threads) { t.join(); }#endif}void test_scale(int i, double* a, double* b) { a[i] = 4 * b[i];}int main(){ int N = 10000; double* a2 = (double*)calloc(N, sizeof(double)); double* a1 = (double*)calloc(N, sizeof(double)); double* b = (double*)calloc(N, sizeof(double)); if (a1 == NULL || a2 == NULL || b == NULL) { if (a1) { free(a1); }if (a2) { free(a2); }if (b) { free(b); } return -1; } for (int i = 0; i < N; i++) { a1[i] = i; a2[i] = i; b[i] = i; } double beforeTime = bench([&] { for (int i = 0; i < N; i++) { test_scale(i, a1, b); } }); std::cout << " \nbefore: " << int(beforeTime * 1000) << "ms" << std::endl; double afterTime = bench([&] { ParallelFor(0, N, [a2, b](size_t i) { test_scale(i, a2, b); }); }); std::cout << " \nafter: " << int(afterTime * 1000) << "ms" << std::endl; for (int i = 0; i < N; i++) { if (a1[i] != a2[i]) { printf("error %f : %f \t", a1[i], a2[i]); getchar(); } } free(a1); free(a2); free(b); getchar(); return 0;}
                   
                  
                 
                
               
              
             
            
           
          
         
        
       
      
     

要使用OPENMP,加个编译选项/openmp  或者定义一下 _OPENMP 即可。

建议c++11编译。

示例代码比较简单。

ncnn代码修改例子如下:

#pragma omp parallel for        for (int q=0; q

　改为

ParallelFor(0, channels, [&](int  q) {                {                    const Mat m = src.channel(q);                    Mat borderm = dst.channel(q);                    copy_make_border_image(m, borderm, top, left, type, v);                }});

 

本来计划抽点时间把ncnn整体都改一下，发个修改版本出来。

想想还是把做法贴出来，给有需求的人吧。

自己动手丰衣足食。

若有其他相关问题或者需求也可以邮件联系俺探讨。

邮箱地址是: 

gaozhihan@vip.qq.com