OpenMP

Purpose

Guide agents through OpenMP shared-memory parallelism: #pragma omp parallel for with scheduling clauses, reductions, data-sharing attributes, SIMD hints, task parallelism, OpenMP 5.x GPU target offloading, common pitfalls (false sharing, data races), environment tuning, and profiling with Score-P or TAU.

When to Use

• Parallelizing C/C++/Fortran loops on multicore CPUs
• Implementing reductions (sum, max, custom)
• Task parallelism for irregular workloads
• Offloading compute to GPU with OpenMP target directives
• Diagnosing scaling failures (false sharing, load imbalance)
• Tuning thread count and spin behavior

Workflow

1. Basic parallel for