CODEWITHSUNDEEP
copenmp
Sergio
Sergio

Reputation: 275

Why would executing a function in parallel significantly slowdown the program?

I am trying to parallelize a code using OpenMP, the serial time for my current input size is around 9 seconds, I have a code of the following form:

int main()
{
    /* do some stuff*/ 
    myfunction();
}

void myfunction()
{
    for (int i=0; i<n; i++)
    {
        //it has some parameters but that is beyond the point I guess
        int rand = custom_random_generator();
        compute(rand);
    }
}

so here the random generator can be executed in parallel since there are no dependencies, and the same goes for the compute function so I was attempting to parallel this piece but all my attempts resulted in a failure, the first thought was to put these functions as task so they get executed in parallel but resulted in a slower result, here is what I did

void myfunction()
{
    for (int i=0; i<n; i++)
    {
        #pragma omp task 
        {
            //it has some parameters but that is beyond the point I guess
            int rand=custom_random_generator();
            compute(rand);
        }
    }
}

Result: 23 seconds, more than double the serial time

Putting task on compute() only resulted in the same

Even worse attempt:

void myfunction()
{
    #pragma omp parallel for
    for (int i=0; i<n; i++)
    {
        //it has some parameters but that is beyond the point I guess
        int rand=custom_random_generator();
        compute(rand);
    }
}

Result: 45 seconds

Theoretically speaking, why could this happen? I know that for anyone to tell my exact problem they would need a minimum reproducible example but my goal from the question is to understand the different theories that could explain my problem and apply them myself, why would parallelizing an "embarrassingly parallel" piece of code result in way worse performance?

Upvotes: 2

Views: 98

Answers (1)

anastaciu
anastaciu

Reputation: 23832

One theory could be the overhead that is associated with creating and maintaining multiple threads.

The advantges of parallel programming can only be seen when each iteration has to perform more complicated processor intensive tasks.

A simple for loop with some simple routine inside would not take advantage of it.

Upvotes: 1

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