Assume I have a function f(i)
which depends on an index i
(among other values which cannot be precomputed).
I want to fill an array a
so that a[n] = sum(f(i)) from i=0 to n-1
.
Edit: After a comment by Hristo Iliev I realized what I am doing is a cumulative/prefix sum.
This can be written in code as
float sum = 0;
for(int i=0; i<N; i++) {
sum += f(i);
a[i] = sum;
}
Now I want to use OpenMP to do this in parallel. One way I could do this with OpenMP is to write out the values for f(i)
in parallel and then take care of the dependency in serial. If f(i)
is a slow function then this could work well since the non-paralleled loop is simple.
#pragma omp parallel for
for(int i=0; i<N; i++) {
a[i] = f(i);
}
for(int i=1; i<N; i++) {
a[i] += a[i-1];
}
But it's possible to do this without the non-parallel loop with OpenMP. The solution, however, that I have come up with is complicated and perhaps hackish. So my question is if there is a simpler less convoluted way to do this with OpenMP?
The code below basically runs the first code I listed for each thread. The result is that values of a
in a given thread are correct up to a constant. I save the sum for each thread to an array suma
with nthreads+1
elements. This allows me to communicate between threads and determine the constant offset for each thread. Then I correct the values of a[i]
with the offset.
float *suma;
#pragma omp parallel
{
const int ithread = omp_get_thread_num();
const int nthreads = omp_get_num_threads();
const int start = ithread*N/nthreads;
const int finish = (ithread+1)*N/nthreads;
#pragma omp single
{
suma = new float[nthreads+1];
suma[0] = 0;
}
float sum = 0;
for (int i=start; i<finish; i++) {
sum += f(i);
a[i] = sum;
}
suma[ithread+1] = sum;
#pragma omp barrier
float offset = 0;
for(int i=0; i<(ithread+1); i++) {
offset += suma[i];
}
for(int i=start; i<finish; i++) {
a[i] += offset;
}
}
delete[] suma;
A simple test is just to set f(i) = i
. Then the solution is a[i] = i*(i+1)/2
(and at infinity it's -1/12).