c - 为什么两个相似的CPU执行相同程序的时间不同？

Question

我试图弄清楚为什么程序(下面的代码)在 Intel(R) Core(TM) i5-3210M CPU @ 2.50GHz 上使用两个而不是四个，但在 Intel(R) Core(TM) 上运行得更快i7-4510U CPU @ 2.00GHz 四线程版本比同一程序的两线程版本运行速度更快。

# include <stdlib.h>
# include <stdio.h>
# include <math.h>
# include <time.h>
# include <omp.h>

int main ( void );
void timestamp ( void );

int main ( void )
{
    double a[500][500];
    double angle;
    double b[500][500];
    double c[500][500];
    int i;
    int j;
    int k;
    int n = 500;
    double pi = M_PI;
    double s;
    int thread_num;
    double wtime;

    timestamp ( );

    printf ( "\n" );
    printf ( "MXM_OPENMP:\n" );
    printf ( "  C/OpenMP version\n" );
    printf ( "  Compute matrix product C = A * B.\n" );

    omp_set_dynamic(0);
    omp_set_num_threads(2);  /* Change param to modify number of threads */

    thread_num = omp_get_max_threads ( );

    printf ( "\n" );
    printf ( "  The number of processors available = %d\n", omp_get_num_procs ( ) );
    printf ( "  The number of threads available    = %d\n", thread_num );

    printf ( "  The matrix order N                 = %d\n", n );

    /*Loop 1: Evaluate A.*/

    s = 1.0 / sqrt ( ( double ) ( n ) );

    wtime = omp_get_wtime ( );

    # pragma omp parallel shared ( a, b, c, n, pi, s ) private ( angle, i, j, k )
        {
        # pragma omp for
            for ( i = 0; i < n; i++ )
            {
                for ( j = 0; j < n; j++ )
                {
                    angle = 2.0 * pi * i * j / ( double ) n;
                    a[i][j] = s * ( sin ( angle ) + cos ( angle ) );
                }
         }

/* Loop 2: Copy A into B.*/

       # pragma omp for
           for ( i = 0; i < n; i++ )
           {
               for ( j = 0; j < n; j++ )
                   {
                   b[i][j] = a[i][j];
                   }
           }

/* Loop 3: Compute C = A * B.*/

        # pragma omp for
            for ( i = 0; i < n; i++ )
            {
                for ( j = 0; j < n; j++ )
                {
                    c[i][j] = 0.0;
                    for ( k = 0; k < n; k++ )
                    {
                        c[i][j] = c[i][j] + a[i][k] * b[k][j];
                    }
                }
            }
        printf ( "  The number of threads used    = %d\n", omp_get_num_threads() );
    }
    wtime = omp_get_wtime ( ) - wtime;
    printf ( "  Elapsed seconds = %g\n", wtime );
    printf ( "  C(100,100)  = %g\n", c[99][99] );
    /*Terminate.*/
    printf ( "\n" );
    printf ( "MXM_OPENMP:\n" );
    printf ( "  Normal end of execution.\n" );

    printf ( "\n" );
    timestamp ( );
    return 0;
}
void timestamp ( void )
{
# define TIME_SIZE 40
    static char time_buffer[TIME_SIZE];
    const struct tm *tm;
    time_t now;

    now = time ( NULL );
    tm = localtime ( &now );

    strftime ( time_buffer, TIME_SIZE, "%d %B %Y %I:%M:%S %p", tm );

    printf ( "%s\n", time_buffer );

    return;
# undef TIME_SIZE
}

Answer 1

即使您拥有完全相同的机器，所有相同的功能，执行时间也可能不同。为什么？因为，当机器 1 中可能运行 200 个服务，而机器 2 中运行 225 个服务时，机器 2 中的程序将在处理器/资源上获得更少的时间，这可能会导致额外的时间。

这完全取决于正在运行的服务(后台和前台)。