Br So the improve factor is exactly O(N) and that is relevant.
Thread 1 : A,B,X 1 0 2).
Example of Standard Use, the standard use looks like this code: void standard_reduction type my_global_sum free snap deal promo code 0; The parallel part of your Algorithm: k-threads works here #pragma omp parallel for reduction my_global_sum) for(int i 0; i N; i) type formula f(i my_global_sum formula; The serial part.The value they hold before the reduction at the end of the parallel region) are only partial and not very useful.The improve version of standard_reduction is: void improve_reduction type my_global_sum 0; The parallel part of your Algorithm: k-threads works here #pragma omp parallel type my_local_sum 0; #pragma omp for nowait for(int i 0; i N; i) type formula f(i my_local_sum formula; #pragma omp atomic my_global_sum.Example of reduction clause!Program threadpriv integer A, B, I, TID, OMP_GET_thread_NUM real*4 X common /C1/ A!OMP threadprivate C1 X)!
Thread 3 : A,B,X 3.
Thread 2 : A,B,X 2.
This is negligible because, for instance, you can't set the number_threads O(106).
Changing Strategy There is an alternative way to totally remove the overhead due to reduction or atomic clauses.
Fortran example do i 1, n sum sum a(i) enddo C/C Example for(i1; i n; i) sum sum ai; How reduction works: sum is the reduction variable cannot be declared shared threads would overwrite the value of sum cannot be declared private private variables don't.
Here the code: void advanced_reduction type my_global_sum 0; type *vectorization; int threads; #pragma omp parallel #pragma omp master threads omp_get_num_threads vectorization ( type 64 assert(vectorization!
Proposal Improvement, using local variable in each thread resolve all the most internal overhead of the algorithm.Br Note on 'Small' : Everything is relative, so the atomic operation has a 'small' overhead respect to the lock/unlock mechanism that can be used to replace the atomic operation.Here the yada yada code should be executed in each iteration once the accumulated value of sum has passed the value of threshold.print '1st Parallel Region!OMP parallel private(B, TID tID OMP_GET_thread_NUM A TID B TID.1 * TID.0 print 'Thread TID A,B,X A,B,X!OMP END parallel.When the loop is run in parallel, the private values of sum might never reach threshold, even if their sum does.Thread 1 : A,B,X 1.