I use OpenMP to parallelize my code. I try to parallelize a loop for with two iterator. I would like to know if my implementation is the best way to parallelize this sequential code:
#include <iostream>
#include <vector>
#include <omp.h>
using namespace std;
int main(int argc, char *argv[])
{
vector<float> v = {1, 2, 3, 4};
vector<float> d = {0, 0, 0, 0};
vector<float>::iterator iterV, iterD;
for(iterV = v.begin(), iterD = d.begin(); iterV < v.end(); ++iterV, ++iterD)
{
*iterD = *iterV;
}
for(iterD = d.begin(); iterD < d.end(); ++iterD)
cout << *iterD << endl;
return 0;
}
My parallel version of this code :
#include <iostream>
#include <vector>
#include <omp.h>
using namespace std;
int main(int argc, char *argv[])
{
vector<float> v = {1, 2, 3, 4};
vector<float> d = {0, 0, 0, 0};
vector<float>::iterator iterV, iterD;
iterV = v.begin();
iterD = d.begin();
#pragma omp parallel for
for(int i = 0; i < v.size(); ++i)
{
*(iterD + i) = *(iterV + i) ;
}
for(iterD = d.begin(); iterD < d.end(); ++iterD)
cout << *iterD << endl;
return 0;
}`
Your example is very simple which hardly need any performance optimization. You just copy the memory (which could be optimized using std::copy
instead).
The code you have written is correct and there is hardly any other way to write it to gain performance. But however, to maintain cleaner code, I try to maintain loop iterators private to each thread. This makes code clean (personal preference).
vector<float> v = {1, 2, 3, 4};
vector<float> d = {0, 0, 0, 0};
#pragma omp parallel for
for(auto it_v = v.begin(),it_d = d.begin(); it_v!=v.end();++it_v,++it_d)
{
*it_d = *it_v;
}
EDIT
OpenMP 3.1 doesn't allow multiple loop initialization in this case. It doesn't adhere to their specification. So one way to do is as follows:
#pragma omp parallel
{
auto it_v = v.begin(),it_d = d.begin();
#pragma openmp for
for(; it_v!=v.end();++it_v)
{
*it_d = *it_v;
}
}
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