Openmp Basics

OpenMP — a directive-based API for shared-memory parallel programming in C/C++/Fortran, enabling parallelization with minimal code changes.

Basic Usage

#pragma omp parallel for
for (int i = 0; i < N; i++) {
    result[i] = compute(data[i]);
}

One line added → loop runs on all available cores.

Key Directives

• `#pragma omp parallel` — create a team of threads
• `#pragma omp for` — distribute loop iterations among threads
• `#pragma omp critical` — mutual exclusion for a code block
• `#pragma omp atomic` — atomic update of a single variable
• `#pragma omp barrier` — synchronization point
• `#pragma omp task` — create a task for dynamic parallelism

Data Sharing

• `shared(var)` — all threads see the same variable (default for most)
• `private(var)` — each thread gets its own copy
• `reduction(+:sum)` — each thread has private copy, combined at end
• `firstprivate` / `lastprivate` — control initialization and final value

Scheduling

• `schedule(static)` — divide iterations equally upfront
• `schedule(dynamic)` — threads grab chunks from a queue
• `schedule(guided)` — decreasing chunk sizes (good for imbalanced workloads)

OpenMP is the easiest way to parallelize existing serial code — 80% of the benefit with 20% of the effort compared to manual threading.