Question

in my previous question
Shared vectors in OpenMP
it was stated that one can let diferent threads read and write on a shared vector as long as
the different threads access different elements of the vector.
What if different threads have to read all the (so sometimes the same) elements of a vector, like in the following case ?

#include <vector> 

int main(){

vector<double> numbers;
vector<double> results(10);
double x;

//write 25 values in vector numbers
for (int i =0; i<25; i++){
    numbers.push_back(cos(i));  
} 

#pragma omp parallel for default(none) \
shared(numbers, results) \
private(x)
    for (int j = 0;  j < 10;  j++){
        for(int k = 0; k < 25; k++){
            x += 2 * numbers[j] * numbers[k] + 5 * numbers[j * k / 25];
        }
        results[j]  =  x;     
    }

    return 0;

}

Will this parallelization be slow because only one thread at a time can read any element of the vector or is this not the case? Could I resolve the problem with the clause firstprivate(numbers)?

Would it make sense to create an array of vectors so every thread gets his own vector ?

For instance:

vector<double> numbersx[**-number of threads-**];

Answer 1

Reading elements of the same vector from multiple threads is not a problem. There is no synchronization in your code, so they will be accessed concurrently.

With the size of vectors that you are working with, you will not have any cache problems either, although for bigger vectors you may get some slow-downs due to the cache access pattern. In that case, separate copies of the numbers data would improve performance.