Consider the following OpenMP for loop: #pragma omp parallel for schedule(dynamic) for (int i = 0; i < n; ++i)
My problem is related to the one discussed here: Is there a way that OpenMP can operate on Qt spanwed threads?
#pragma omp parallel for reduction(+ : numOfVecs) for(itc=clus.begin() ; itc!=clus.end() ; itc++) { numOfVecs += (*itc)->getNumOfVecs();
I\'m trying to adapt a normal code to a parallel one. When I make a for loop parallel, which has some variables declared inside of it, are those variables private or shared?
I\'m using a version of openMP which does not support reduce() for complex argument. I need a fast dot-product function like
Could someone please provide some suggestions on how I can decrease the following for loop\'s runtime through multithreading? Suppose I also have two vectors called \'a\' and \'b\'.
I\'m trying to learn how to use OpenMP by parallelizing a monte carlo code that calculates the value of PI with a given number of iterations. The meat of the code is this:
First of all, OpenMP obviously only runs in one of the motherboards in the cluster, in this case each motherboard has two quad-core Xeons E5405 at 2GHz and its running Scientific Linux 5.3 (released i
SOLVED: see EDIT 2 below I am trying to parallelise an algorithm which does some operation on a matrix (lets call it blurring for simplicity sake). Once this operation has been done, it finds the big
If I have a program that uses OpenMP, is there a way I can see the transformed code generated by the compiler, that is the code the compiler actually compiles. Actually I\'m interested in seeing what
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