Measure Execution Time in C++ Openmp Code

Measure execution time in C++ OpenMP code

You could use the built in omp_get_wtime function in omp library itself. Following is an example code snippet to find out execution time.

#include <stdio.h>
#include <omp.h>

int main(){

    double itime, ftime, exec_time;
    itime = omp_get_wtime();

    // Required code for which execution time needs to be computed
    
    ftime = omp_get_wtime();
    exec_time = ftime - itime;
    printf("\n\nTime taken is %f", exec_time);

}

How to measure execution time of each thread in openmp?

You can just print the per-thread time this way (not tested, not even compiled):

#pragma omp parallel
{
    double wtime = omp_get_wtime();
    #pragma omp for schedule( dynamic, 1 ) nowait
    for ( int i=0; i<n; i++ ) {
        // whatever
    }
    wtime = omp_get_wtime() - wtime;
    printf( "Time taken by thread %d is %f\n", omp_get_thread_num(), wtime );
}

NB the nowaitthan removes the barrier at the end of the for loop, otherwise this wouldn't have any interest.

And of couse, using a proper profiling tool is a way better approach...

C program execution time OpenMP/Sequential

Sure, why not. The last line looks a bit cumbersome. Why not like this:

x = (end_##id.tv_sec - start_##id.tv_sec) + (end_##id.tv_usec - start_##id.tv_usec) * 1.e-6;

Other than that, if wall clock time is all you need, your solution will work just fine.

Measure execution time in C++ OpenMP code

You could use the built in omp_get_wtime function in omp library itself. Following is an example code snippet to find out execution time.

#include <stdio.h>
#include <omp.h>

int main(){

    double itime, ftime, exec_time;
    itime = omp_get_wtime();

    // Required code for which execution time needs to be computed
    
    ftime = omp_get_wtime();
    exec_time = ftime - itime;
    printf("\n\nTime taken is %f", exec_time);

}

Parallel exection using OpenMP takes longer than serial execution c++, am i calculating execution time in the right way?

OpenMP internally implement multithreading for parallel processing and multi threading's performance can be measured with large volume of data. With very small volume of data you cannot measure the performance of multithreaded application. The reasons:-

a) To create a thread O/S need to allocate memory to each thread which take time (even though it is tiny bit.)

b) When you create multi threads it needs context switching which also take time.

c) Need to release memory allocated to threads which also take time.

d) It depends on number of processors and total memory (RAM) in your machine

So when you try with small operation with multi threads it's performance will be as same as a single thread (O/S by default assign one thread to every process which is call main thread). So your outcome is perfect in this case. To measure the performance of multithread architecture use large amount of data with complex operation then only you can see the differences.

OpenMP time and clock() give two different results

The clock function measures cpu time, the time you spend actively on the CPU, the OMP function measures the time as it has passed during execution, two completely different things.

Your process seems to be blocked in waiting somewhere.

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