CODEWITHSUNDEEP
cmultithreadingfor-loopparallel-processingopenmp
Jack
Jack

Reputation: 3

OpenMP parallelization not efficient

I'm trying to parallelize this code using OpenMP.

for(t_step=0;t_step<Ntot;t_step++) {
        // current row
        if(cur_row + 1 < Npt_x)     cur_row++; 
        else                        cur_row = 0;
        // get data from file which update only the row "cur_row" of array val
        read_line(f_u, val[cur_row]);
        // computes
        for(i=0;i<Npt_x;i++) {
            for(j=0;j<Npt_y;j++) {
                i_corrected = cur_row - i;
                if(i_corrected < 0)     i_corrected = Npt_x + i_corrected;
                R[i][j] += val[cur_row][0]*val[i_corrected][j]/Ntot;
            }
        }
    }

with
- val and R declared as **double,
- Npt_x and Npt_y are about 500,
- Ntot is about 10^6.

I've done this

for(t_step=0;t_step<Ntot;t_step++) {
        // current row
        if(cur_row + 1 < Npt_x)     cur_row++; 
        else                        cur_row = 0;
        // get data from file which update only the row "cur_row" of array val
        read_line(f_u, val[cur_row]);
        // computes
        #pragma omp parallel for collapse(2), private(i,j,i_corrected)
        for(i=0;i<Npt_x;i++) {
            for(j=0;j<Npt_y;j++) {
                i_corrected = cur_row - i;
                if(i_corrected < 0)     i_corrected = Npt_x + i_corrected;
                R[i][j] += val[cur_row][0]*val[i_corrected][j]/Ntot;
            }
        }
    }

The problem is that it doesn't seem to be efficient. Is there a way to use OpenMP more efficiently in this case ?

Many thks

Upvotes: 0

Views: 188

Answers (1)

Gilles
Gilles

Reputation: 9489

Right now, I would try something like this:

for(t_step=0;t_step<Ntot;t_step++) {
    // current row
    if(cur_row + 1 < Npt_x)
        cur_row++; 
    else
        cur_row = 0;
    // get data from file which update only the row "cur_row" of array val
    read_line(f_u, val[cur_row]);
    // computes
    #pragma omp parallel for private(i,j,i_corrected)
    for(i=0;i<Npt_x;i++) {
        i_corrected = cur_row - i;
        if(i_corrected < 0)
            i_corrected += Npt_x;
        double tmp = val[cur_row][0]/Ntot;
        #if defined(_OPENMP) && _OPENMP > 201306
        #pragma omp simd
        #endif
        for(j=0;j<Npt_y;j++) {
            R[i][j] += tmp*val[i_corrected][j];
        }
    }
}

However, since the code will be memory bound, that's not sure it'll get you much parallel speed-up... Worth a try though.

Upvotes: 1

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