It's a follow-up question to this one
Now I have the code:
#include <iostream>
#include <cmath>
#include <omp.h>
#define max(a, b) (a)>(b)?(a):(b)
const int m = 2001;
const int n = 2000;
const int p = 4;
double v[m + 2][m + 2];
double x[m + 2];
double y[m + 2];
double _new[m + 2][m + 2];
double maxdiffA[p + 1];
int icol, jrow;
int main() {
omp_set_num_threads(p);
double h = 1.0 / (n + 1);
double start = omp_get_wtime();
#pragma omp parallel for private(icol) shared(x, y, v, _new)
for (icol = 0; icol <= n + 1; ++icol) {
x[icol] = y[icol] = icol * h;
_new[icol][0] = v[icol][0] = 6 - 2 * x[icol];
_new[n + 1][icol] = v[n + 1][icol] = 4 - 2 * y[icol];
_new[icol][n + 1] = v[icol][n + 1] = 3 - x[icol];
_new[0][icol] = v[0][icol] = 6 - 3 * y[icol];
}
const double eps = 0.01;
#pragma omp parallel private(icol, jrow) shared(_new, v, maxdiffA)
{
while (true) { //for [iters=1 to maxiters by 2]
#pragma omp single
for (int i = 0; i < p; i++) maxdiffA[i] = 0;
#pragma omp for
for (icol = 1; icol <= n; icol++)
for (jrow = 1; jrow <= n; jrow++)
_new[icol][jrow] =
(v[icol - 1][jrow] + v[icol + 1][jrow] + v[icol][jrow - 1] + v[icol][jrow + 1]) / 4;
#pragma omp for
for (icol = 1; icol <= n; icol++)
for (jrow = 1; jrow <= n; jrow++)
v[icol][jrow] = (_new[icol - 1][jrow] + _new[icol + 1][jrow] + _new[icol][jrow - 1] +
_new[icol][jrow + 1]) / 4;
#pragma omp for
for (icol = 1; icol <= n; icol++)
for (jrow = 1; jrow <= n; jrow++)
maxdiffA[omp_get_thread_num()] = max(maxdiffA[omp_get_thread_num()],
fabs(_new[icol][jrow] - v[icol][jrow]));
#pragma omp barrier
double maxdiff = 0.0;
for (int k = 0; k < p; ++k) {
maxdiff = max(maxdiff, maxdiffA[k]);
}
if (maxdiff < eps)
break;
#pragma omp barrier
//#pragma omp single
//std::cout << maxdiff << std::endl;
}
}
double end = omp_get_wtime();
printf("start = %.16lf
end = %.16lf
diff = %.16lf
", start, end, end - start);
return 0;
}
But why it works 2-3 times slower (32sec vs 18sec) than serial analog:
#include <iostream>
#include <cmath>
#include <omp.h>
#define max(a,b) (a)>(b)?(a):(b)
const int m = 2001;
const int n = 2000;
double v[m + 2][m + 2];
double x[m + 2];
double y[m + 2];
double _new[m + 2][m + 2];
int main() {
double h = 1.0 / (n + 1);
double start = omp_get_wtime();
for (int i = 0; i <= n + 1; ++i) {
x[i] = y[i] = i * h;
_new[i][0]=v[i][0] = 6 - 2 * x[i];
_new[n + 1][i]=v[n + 1][i] = 4 - 2 * y[i];
_new[i][n + 1]=v[i][n + 1] = 3 - x[i];
_new[0][i]=v[0][i] = 6 - 3 * y[i];
}
const double eps=0.01;
while(true){ //for [iters=1 to maxiters by 2]
double maxdiff=0.0;
for (int i=1;i<=n;i++)
for (int j=1;j<=n;j++)
_new[i][j]=(v[i-1][j]+v[i+1][j]+v[i][j-1]+v[i][j+1])/4;
for (int i=1;i<=n;i++)
for (int j=1;j<=n;j++)
v[i][j]=(_new[i-1][j]+_new[i+1][j]+_new[i][j-1]+_new[i][j+1])/4;
for (int i=1;i<=n;i++)
for (int j=1;j<=n;j++)
maxdiff=max(maxdiff, fabs(_new[i][j]-v[i][j]));
if(maxdiff<eps) break;
std::cout << maxdiff<<std::endl;
}
double end = omp_get_wtime();
printf("start = %.16lf
end = %.16lf
diff = %.16lf
", start, end, end - start);
return 0;
}
Also interesting that it works SAME TIME as version (I can post it here if you say so) which looks like so
while(true){ //106 iteratins here!!!
#pragma omp paralell for
for(...)
#pragma omp paralell for
for(...)
#pragma omp paralell for
for(...)
}
But I thought that what making omp code slow is spawning threads inside while loop 106 times... But no! Then probably threads simultaneously write to the same array cells.. But where does it happen? I don't see it could you show me please?
Maybe it's because too much barriers? But Lecturer told me to implement the code like so and "analyse it" Maybe the answer is "Jacobi algorithm isn't meant to run well in parallel"? Or it's just my lame coding?
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