Openmp: невозможно правильно рассчитать статус задания внутри параллели для цикла

Question

Openmp: невозможно правильно рассчитать статус задания внутри параллели для цикла

Я пытаюсь реализовать функции отчетности о состоянии задачи внутри параллельного цикла for. Это распараллеливание цикла for выполняется с использованием "OPENMP".

Я хочу, чтобы отчеты о состоянии выполнялись следующим образом:

Work done 70%; estimated time left 3:30:05 hour.

Конечно, я могу рассчитать "расчетное оставшееся время", рассчитав разницу между "временем начала" и "текущим временем". Но, похоже, я не могу точно рассчитать "проделанную работу" внутри цикла for, даже используя "статическое" объявление.

Некоторое руководство будет оценено.

Вывод моего кода:

Values of cores : 8
Outer loop =================================
Thread 0  iCount0   
 % of work done 10
Outer loop ================================= 
Thread 0  iCount1
Outer loop ================================= 
Thread 2  iCount2
Outer loop ================================= 
Thread 7  iCount3
 % of work done 40
Outer loop =================================
Thread 5  iCount4
 % of work done 50
Outer loop =================================
Thread 3  iCount5
 % of work done 60
Outer loop =================================
Thread 4  iCount6 
 % of work done 70
Outer loop =================================
Thread 1  iCount7
 % of work done 20
 % of work done 80
Outer loop ================================= 
Thread 6  iCount8 
 % of work done 90
Outer loop ================================= 
Thread 1  iCount9  
 % of work done 100
 % of work done 30

Как видно из последних двух строк, я не могу правильно рассчитать статус работы.

Вот мой код:

ПРИМЕЧАНИЕ: я намеренно использовал "std::endl", а не "\ n", так как очистка выходного буфера как-то портит мой расчет% работы. Я уверен, что подобный сценарий возникнет, если я выполню реальный расчет внутри параллели для

#include "stdafx.h"
#include <iostream>     // std::cout, std::endl
#include <iomanip>      // std::setfill, std::setw
#include <math.h>       /* pow */
#include <omp.h>

int main(int argc, char** argv)
  {
    // Get the number of processors in this system
    int iCPU = omp_get_num_procs();

    // Now set the number of threads
    omp_set_num_threads(iCPU);
    std::cout << "Values of cores : " << iCPU <<" \n";

    int x = 0; 
    int iTotalOuter = 10;
    static int iCount = 0;

    #pragma omp parallel for private(x) 
    for(int y = 0; y < iTotalOuter; y++) 
    { 
        std::cout << "Outer loop =================================\n" ;     
        std::cout <<"\nThread "<<omp_get_thread_num()<<"  iCount" << iCount<<std::endl;

        for(x = 0; x< 5; x++) 
        { 
            //std::cout << "Inner loop \n" ;        
        } 
        iCount = iCount + 1;        
        std::cout <<"\n % of work done " << (double)100*((double)iCount/(double)iTotalOuter)<<std::endl;
    }

  std::cin.ignore(); //Wait for user to hit enter
  return 0;
  }

ОБНОВЛЕНИЕ: Основываясь на ответе "Ави Гинзбурга", я пытаюсь сделать так:

#include "stdafx.h"
#include <iostream>     // std::cout, std::endl
#include <iomanip>      // std::setfill, std::setw
#include <math.h>       /* pow */
#include <omp.h>
void ReportJobStatus(int , int );

int main(int argc, char** argv)
  {   
    // Get the number of processors in this system
    int iCPU = omp_get_num_procs();

    // Now set the number of threads
    omp_set_num_threads(iCPU);
    std::cout << "Values of cores : " << iCPU <<" \n";

    int x = 0; 
    int iTotalOuter = 100;
    static int iCount = 0;

    #pragma omp parallel for private(x) 
    for(int y = 0; y < iTotalOuter; y++) 
    { 
        std::cout << "Outer loop =================================\n" ;     

        for(x = 0; x< 5; x++) 
        { 
            //std::cout << "Inner loop \n" ;        
        } 
        #pragma omp atomic
        iCount++;   

        std::cout<< " omp_get_thread_num(): " << omp_get_thread_num() <<"\n";
        if (omp_get_thread_num() == 0){
            ReportJobStatus(iCount, iTotalOuter);
        }

    }

  std::cin.ignore(); //Wait for user to hit enter
  return 0;
  }

Проблема (обновленная): проблема в том, что один и тот же поток используется для одновременного выполнения. Таким образом, отчет о проделанной работе становится серьезно ограниченным. Как можно назначать задания различным ядрам на основе данных.

Вот текущий вывод моего кода:

Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 1
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 2
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 3
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 4
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 5
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 6
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 7
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 8
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 9
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 10
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 11
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 12
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 13
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 14
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 15
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 16
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 17
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 18
Outer loop =================================
 omp_get_thread_num(): 0
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 1

 % of work done 19
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 54
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 55
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 56
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 57
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 58
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 59
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 60
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 61
Outer loop =================================
 omp_get_thread_num(): 0

 % of work done 62
Outer loop =================================
 omp_get_thread_num(): 6
Outer loop =================================
 omp_get_thread_num(): 6
Outer loop =================================
 omp_get_thread_num(): 6
Outer loop =================================
 omp_get_thread_num(): 6
Outer loop =================================
 omp_get_thread_num(): 6
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 3
Outer loop =================================
 omp_get_thread_num(): 1
Outer loop =================================
 omp_get_thread_num(): 5
Outer loop =================================
 omp_get_thread_num(): 5
Outer loop =================================
 omp_get_thread_num(): 5
Outer loop =================================
 omp_get_thread_num(): 5
Outer loop =================================
 omp_get_thread_num(): 5
Outer loop =================================
 omp_get_thread_num(): 5
Outer loop =================================
 omp_get_thread_num(): 5
Outer loop =================================
 omp_get_thread_num(): 5
Outer loop =================================
Outer loop =================================
 omp_get_thread_num(): 4
Outer loop =================================
 omp_get_thread_num(): 4
Outer loop =================================
 omp_get_thread_num(): 4
Outer loop =================================
 omp_get_thread_num(): 4
Outer loop =================================
 omp_get_thread_num(): 4
Outer loop =================================
 omp_get_thread_num(): 4
Outer loop =================================
 omp_get_thread_num(): 4
Outer loop =================================
 omp_get_thread_num(): 4
Outer loop =================================
 omp_get_thread_num(): 4
Outer loop =================================
 omp_get_thread_num(): 4
 omp_get_thread_num(): 7
Outer loop =================================
 omp_get_thread_num(): 7
Outer loop =================================
 omp_get_thread_num(): 7
Outer loop =================================
 omp_get_thread_num(): 7
Outer loop =================================
 omp_get_thread_num(): 7
Outer loop =================================
 omp_get_thread_num(): 7
Outer loop =================================
 omp_get_thread_num(): 2
Outer loop =================================
 omp_get_thread_num(): 2
Outer loop =================================
 omp_get_thread_num(): 2
Outer loop =================================
 omp_get_thread_num(): 2
Outer loop =================================
 omp_get_thread_num(): 2
Outer loop =================================
 omp_get_thread_num(): 2
Outer loop =================================
 omp_get_thread_num(): 2

1

c++ openmp parallel-for

Источник

user1138921 02 фев '15 в 10:38

1 ответ

Другие вопросы по тегам c++ openmp parallel-for

user2899559 02 фев '15 в 10:50 2015-02-02 10:50 · Answer 1 · 2015-02-02 10:50

Использовать critical или же atomic в цикле:

#pragma omp critical
    {
        (++prog);
    }

или лучше:

#pragma omp atomic
(++prog);

и думать только о том, чтобы позволить главному потоку распечатать прогресс.

if(omp_get_thread_num() == 0)
{
  cout << "Progress: " << float(prog)/totalNumber;
}

4

Источник

user2899559 02 фев '15 в 10:50