Visible to Intel only — GUID: GUID-3235AE70-ED6C-43A2-8E68-7FC5F7F15663
Visible to Intel only — GUID: GUID-3235AE70-ED6C-43A2-8E68-7FC5F7F15663
Parallelize Data - OpenMP Counted Loops
When tasks are loop iterations, and the iterations are over a range of values that are known before the loop starts, the loop is easily expressed in OpenMP.
Consider the following annotated serial C/C++ loop:
ANNOTATE_SITE_BEGIN(sitename); for (int i = lo; i < hi; ++i) { ANNOTATE_ITERATION_TASK(taskname); statement; } ANNOTATE_SITE_END();
OpenMP makes it easy to introduce parallelism into loops. With C or C++ programs, add the omp parallel for pragma immediately before the C/C++ for statement:
... #pragma omp parallel for for (int i = lo; i < hi; ++i) { statement; }
Consider the following annotated Fortran serial loop:
call annotate_site_begin("sitename") do i = 1, N call annotate_iteration_task("taskname") statement end do call annotate_site_end
With Fortran programs, add the !$omp parallel do directive immediately before the Fortran do statement:
... !$omp parallel do do i = 1, N statement end do !$omp end parallel do
The OpenMP compiler support encapsulates the parallel construct. The rules for capturing the locals can be defaulted or specified as part of the pragma or directive. The loop control variable defaults to being private so each iteration sees its allotted value.