C++ 我可以报告openmp任务的进度吗？

想象一个典型的OMP任务：

• 对[0.0,1.0]范围内的大向量进行求和

using namespace std;

int main() {
    vector<double> v;

    // generate some data
    generate_n(back_inserter(v), 1ul << 18, 
       bind(uniform_real_distribution<double>(0,1.0), default_random_engine { random_device {}() }));

    long double sum = 0;

    {
#pragma omp parallel for reduction(+:sum)
        for(size_t i = 0; i < v.size(); i++)
        {
            sum += v[i];
        }
    }
    std::cout << "Done: sum = " << sum << "\n";
}

#include <omp.h>
#include <vector>
#include <random>
#include <algorithm>
#include <iterator>
#include <functional>
#include <iostream>
#include <iomanip>

using namespace std;

int main() {
    vector<double> v;
    // generate some data
    generate_n(back_inserter(v), 1ul << 18, bind(uniform_real_distribution<double>(0,1.0), default_random_engine { random_device {}() }));

    auto step_size   = 100ul;
    auto total_steps = v.size() / step_size + 1;

    size_t steps_completed = 0;
    long double sum = 0;

#pragma omp parallel 
    {
        size_t local_count = 0;


#pragma omp for reduction(+:sum)
        for(size_t i = 0; i < v.size(); i++)
        {
            sum += v[i];

            if (local_count++ % step_size == step_size-1)
            {
#pragma omp atomic
                ++steps_completed;

                if (steps_completed % 100 == 1)
                {
#pragma omp critical
                    std::cout << "Progress: " << steps_completed << " of " << total_steps << " (" << std::fixed << std::setprecision(1) << (100.0*steps_completed/total_steps) << "%)\n";
                }
            }
        }
    }
    std::cout << "Done: sum = " << sum << "\n";
}

使用名称空间std；
int main（）{
向量v；
//生成一些数据
生成插入器（v），1ul只需让团队中的每个线程跟踪本地进度并原子地更新全局计数器。您仍然可以让另一个线程观察它，或者，如下面的示例所示，您可以在OMP关键部分内执行终端输出

这里的关键是调整步长，使其不会导致频繁的更新，因为关键区域的锁定（原子负载/存储的锁定程度较低）会降低性能


using namespace std;

int main() {
    vector<double> v;

    // generate some data
    generate_n(back_inserter(v), 1ul << 18, 
       bind(uniform_real_distribution<double>(0,1.0), default_random_engine { random_device {}() }));

    long double sum = 0;

    {
#pragma omp parallel for reduction(+:sum)
        for(size_t i = 0; i < v.size(); i++)
        {
            sum += v[i];
        }
    }
    std::cout << "Done: sum = " << sum << "\n";
}

#include <omp.h>
#include <vector>
#include <random>
#include <algorithm>
#include <iterator>
#include <functional>
#include <iostream>
#include <iomanip>

using namespace std;

int main() {
    vector<double> v;
    // generate some data
    generate_n(back_inserter(v), 1ul << 18, bind(uniform_real_distribution<double>(0,1.0), default_random_engine { random_device {}() }));

    auto step_size   = 100ul;
    auto total_steps = v.size() / step_size + 1;

    size_t steps_completed = 0;
    long double sum = 0;

#pragma omp parallel 
    {
        size_t local_count = 0;


#pragma omp for reduction(+:sum)
        for(size_t i = 0; i < v.size(); i++)
        {
            sum += v[i];

            if (local_count++ % step_size == step_size-1)
            {
#pragma omp atomic
                ++steps_completed;

                if (steps_completed % 100 == 1)
                {
#pragma omp critical
                    std::cout << "Progress: " << steps_completed << " of " << total_steps << " (" << std::fixed << std::setprecision(1) << (100.0*steps_completed/total_steps) << "%)\n";
                }
            }
        }
    }
    std::cout << "Done: sum = " << sum << "\n";
}

我下面的代码与前面的代码类似，但存在一些差异，这使我能够处理要报告的跳过点，因为完全相等，包括按模除法。此外，全局计数器收集所有线程的实际循环执行，但可能不精确-这对于这个特定问题是可以接受的。我只使用用于报告的主线程

const size_t size = ...
const size_t step_size = size / 100;
const size_t nThreads = ...
const size_t local_count_max = step_size / nThreads;
size_t count = 0;
#pragma omp parallel num_threads(nThreads)
{
  size_t reported_count = 0;
  size_t local_count = 0;
  #pragma omp for
  for (size_t i = 0; i < size; ++i)
  {
    <... do some useful work ...>
    // -------------------------- update local and global progress counters
    if (local_count >= local_count_max)
    {
      #pragma omp atomic
      count += local_count_max;
      local_count = 0;
    }
    else
    {
      ++local_count;
    }
    // ------------------------------ report progress (in master thread only)
    #pragma omp master
    if (count - reported_count >= step_size)
    {
      <... report the progress ...>
      reported_count = count;
    }
  }
}

const size\u t size=。。。
常数大小t步长大小=大小/100；
常量大小\u t n读取=。。。
const size\u t local\u count\u max=步长/n次读取；
大小\u t计数=0；
#pragma omp并行num_线程（n线程）
{
报告的大小\u计数=0；
大小\u t本地\u计数=0；
#pragma omp for
对于（大小i=0；i=本地计数最大值）
{
#布拉格omp原子
计数+=本地计数\u最大值；
本地_计数=0；
}
其他的
{
++本地(u)计数;；
}
//------------------------------------报告进度（仅在主线程中）
#pragma-omp-master
如果（计数-报告的计数>=步长大小）
{
报告的计数=计数；
}
}
}
在没有本机原子支持的处理器上（即使有本机原子支持），使用
#pragma omp-atomic
，正如这里的其他答案所建议的，可能会降低程序的速度

进度指示器的概念是让用户知道什么时候事情会完成。如果你在目标上加上/减去总运行时间的一小部分，用户就不会太烦恼。也就是说，用户希望事情更快完成，而不是以更准确地知道事情何时完成为代价

出于这个原因，我通常只跟踪单个线程的进度，并使用它来估计总进度。这对于每个线程都有类似工作负载的情况很好。因为您使用的是
#pragma omp parallel For
，您可能在处理一系列类似的元素，而没有相互依赖性，所以我的假设是p可能对您的用例有效

我将此逻辑包装在一个类
ProgressBar
，我通常将其与它的助手类
Timer
一起包含在头文件中。该类使用ANSI控制信号来保持外观良好

输出如下所示：

[======                                            ] (12% - 22.0s - 4 threads)

通过声明
-DNOPROGRESS
编译标志，让编译器消除progressbar的所有开销也很容易

代码和示例用法如下所示：

#include <iostream>
#include <chrono>
#include <thread>
#include <iomanip>
#include <stdexcept>

#ifdef _OPENMP
  ///Multi-threading - yay!
  #include <omp.h>
#else
  ///Macros used to disguise the fact that we do not have multithreading enabled.
  #define omp_get_thread_num()  0
  #define omp_get_num_threads() 1
#endif


///@brief Used to time how intervals in code.
///
///Such as how long it takes a given function to run, or how long I/O has taken.
class Timer{
 private:
  typedef std::chrono::high_resolution_clock clock;
  typedef std::chrono::duration<double, std::ratio<1> > second;

  std::chrono::time_point<clock> start_time; ///< Last time the timer was started
  double accumulated_time;                   ///< Accumulated running time since creation
  bool running;                              ///< True when the timer is running

 public:
  Timer(){
    accumulated_time = 0;
    running          = false;
  }

  ///Start the timer. Throws an exception if timer was already running.
  void start(){
    if(running)
      throw std::runtime_error("Timer was already started!");
    running=true;
    start_time = clock::now();
  }

  ///Stop the timer. Throws an exception if timer was already stopped.
  ///Calling this adds to the timer's accumulated time.
  ///@return The accumulated time in seconds.
  double stop(){
    if(!running)
      throw std::runtime_error("Timer was already stopped!");

    accumulated_time += lap();
    running           = false;

    return accumulated_time;
  }

  ///Returns the timer's accumulated time. Throws an exception if the timer is
  ///running.
  double accumulated(){
    if(running)
      throw std::runtime_error("Timer is still running!");
    return accumulated_time;
  }

  ///Returns the time between when the timer was started and the current
  ///moment. Throws an exception if the timer is not running.
  double lap(){
    if(!running)
      throw std::runtime_error("Timer was not started!");
    return std::chrono::duration_cast<second> (clock::now() - start_time).count();
  }

  ///Stops the timer and resets its accumulated time. No exceptions are thrown
  ///ever.
  void reset(){
    accumulated_time = 0;
    running          = false;
  }
};


///@brief Manages a console-based progress bar to keep the user entertained.
///
///Defining the global `NOPROGRESS` will
///disable all progress operations, potentially speeding up a program. The look
///of the progress bar is shown in ProgressBar.hpp.
class ProgressBar{
 private:
  uint32_t total_work;    ///< Total work to be accomplished
  uint32_t next_update;   ///< Next point to update the visible progress bar
  uint32_t call_diff;     ///< Interval between updates in work units
  uint32_t work_done;
  uint16_t old_percent;   ///< Old percentage value (aka: should we update the progress bar) TODO: Maybe that we do not need this
  Timer    timer;         ///< Used for generating ETA

  ///Clear current line on console so a new progress bar can be written
  void clearConsoleLine() const {
    std::cerr<<"\r\033[2K"<<std::flush;
  }

 public:
  ///@brief Start/reset the progress bar.
  ///@param total_work  The amount of work to be completed, usually specified in cells.
  void start(uint32_t total_work){
    timer = Timer();
    timer.start();
    this->total_work = total_work;
    next_update      = 0;
    call_diff        = total_work/200;
    old_percent      = 0;
    work_done        = 0;
    clearConsoleLine();
  }

  ///@brief Update the visible progress bar, but only if enough work has been done.
  ///
  ///Define the global `NOPROGRESS` flag to prevent this from having an
  ///effect. Doing so may speed up the program's execution.
  void update(uint32_t work_done0){
    //Provide simple way of optimizing out progress updates
    #ifdef NOPROGRESS
      return;
    #endif

    //Quick return if this isn't the main thread
    if(omp_get_thread_num()!=0)
      return;

    //Update the amount of work done
    work_done = work_done0;

    //Quick return if insufficient progress has occurred
    if(work_done<next_update)
      return;

    //Update the next time at which we'll do the expensive update stuff
    next_update += call_diff;

    //Use a uint16_t because using a uint8_t will cause the result to print as a
    //character instead of a number
    uint16_t percent = (uint8_t)(work_done*omp_get_num_threads()*100/total_work);

    //Handle overflows
    if(percent>100)
      percent=100;

    //In the case that there has been no update (which should never be the case,
    //actually), skip the expensive screen print
    if(percent==old_percent)
      return;

    //Update old_percent accordingly
    old_percent=percent;

    //Print an update string which looks like this:
    //  [================================================  ] (96% - 1.0s - 4 threads)
    std::cerr<<"\r\033[2K["
             <<std::string(percent/2, '=')<<std::string(50-percent/2, ' ')
             <<"] ("
             <<percent<<"% - "
             <<std::fixed<<std::setprecision(1)<<timer.lap()/percent*(100-percent)
             <<"s - "
             <<omp_get_num_threads()<< " threads)"<<std::flush;
  }

  ///Increment by one the work done and update the progress bar
  ProgressBar& operator++(){
    //Quick return if this isn't the main thread
    if(omp_get_thread_num()!=0)
      return *this;

    work_done++;
    update(work_done);
    return *this;
  }

  ///Stop the progress bar. Throws an exception if it wasn't started.
  ///@return The number of seconds the progress bar was running.
  double stop(){
    clearConsoleLine();

    timer.stop();
    return timer.accumulated();
  }

  ///@return Return the time the progress bar ran for.
  double time_it_took(){
    return timer.accumulated();
  }

  uint32_t cellsProcessed() const {
    return work_done;
  }
};

int main(){
  ProgressBar pg;
  pg.start(100);
  //You should use 'default(none)' by default: be specific about what you're
  //sharing
  #pragma omp parallel for default(none) schedule(static) shared(pg)
  for(int i=0;i<100;i++){
    pg.update(i);
    std::this_thread::sleep_for(std::chrono::seconds(1));
  }
}

#包括
#包括
#包括
#包括
#包括
#ifdef\u OPENMP
///多线程-耶！
#包括
#否则
///宏用来掩盖我们没有启用多线程的事实。
#定义omp\u get\u thread\u num（）0
#定义omp_get_num_线程（）1
#恩迪夫
///@用于在代码中计算时间间隔的简要说明。
///
///例如，给定函数运行所需的时间，或I/O所需的时间。
班级计时器{
私人：
typedef std:：chrono:：高分辨率时钟；
typedef std:：chrono:：持续时间秒；
std:：chrono:：time\u point start\u time；//<上次启动计时器的时间
双累计_时间；//<自创建以来的累计运行时间
bool running；//<计时器运行时为True
公众：
计时器（）{
累计_时间=0；
运行=错误；
}
///启动计时器。如果计时器已在运行，则引发异常。
void start（）{
如果（正在运行）
抛出std:：runtime_错误（“计时器已启动！”）；
运行=真；
开始时间=时钟：：现在（）；
}
///停止计时器。如果计时器已停止，则引发异常。
///调用此选项会增加计时器的累计时间。
///@返回以秒为单位的累计时间。
双止点（）{
如果（！正在运行）
抛出std:：runtime_错误（“计时器已停止！”）；
累计_时间+=圈（）；
运行=错误；
返回累计时间；
}
///返回计时器的累计时间。如果计时器为空，则引发异常
///跑步。
双倍累积（）{
如果（正在运行）
抛出std:：runtime_错误（“计时器仍在运行！”）；
返回累计时间；
}
///返回计时器启动与当前时间之间的时间
///如果计时器未运行，则引发异常。
双圈（）{
如果（！正在运行）
抛出std:：runtime_错误（“计时器未启动！”）；
返回std:：chrono:：duration_cast（clock:：now（）-start_time）.count（）；
}
///停止计时器并重置其累计时间。不会引发异常
///永远。
无效重置（）{
累计_时间=0；
运行=错误；
}
};
///@brief管理一个基于控制台的进度条，以保持用户的娱乐。
///
///定义全球“无进展”将
///禁用所有进度操作，可能会加快程序的速度
///进度条的路径显示在ProgressBar.hpp中。
类进度条{
私人：
uint32总工作量；//<待完成的总工作量
uint32\u t next\u update；//<更新可见进度条的下一点
uint32\u t调用\u diff；//<工作单元中更新之间的间隔
uint32未完成的工作；
uint16旧百分比；旧百分比值（又名：