Since OpenMP 4.0, user-defined reduction is supported. So I defined the reduction on std::vector in C++ exactly from here. It works fine with GNU/5.4.0 and GNU/6.4.0, but it
This appears to be a bug in the Intel compiler, I can reliably reproduce it with a C example not involving vectors:
#include
void my_sum_fun(int* outp, int* inp) {
printf("%d @ %p += %d @ %p\n", *outp, outp, *inp, inp);
*outp = *outp + *inp;
}
int my_init(int* orig) {
printf("orig: %d @ %p\n", *orig, orig);
return *orig;
}
#pragma omp declare reduction(my_sum : int : my_sum_fun(&omp_out, &omp_in) initializer(omp_priv = my_init(&omp_orig))
int main()
{
int s = 0;
#pragma omp parallel for reduction(my_sum : s)
for (int i = 0; i < 2; i++)
s+= 1;
printf("sum: %d\n", s);
}
Output:
orig: 0 @ 0x7ffee43ccc80
0 @ 0x7ffee43ccc80 += 1 @ 0x7ffee43cc780
orig: 1 @ 0x7ffee43ccc80
1 @ 0x7ffee43ccc80 += 2 @ 0x2b56d095ca80
sum: 3
It applies the reduction operation to the original variable before initializing the private copy from the original value. This leads to the wrong result.
You can manually add a barrier as a workaround:
#pragma omp parallel reduction(vec_double_plus : w)
{
#pragma omp for
for (int i = 0; i < 4; ++i)
for (int j = 0; j < w.size(); ++j)
w[j] += 1;
#pragma omp barrier
}