Shared-Memory Parallelism with OpenMP

Explain race conditions in concurrent programs and the need for synchronization

Explain the fork-join execution model of OpenMP

Parallelize loops using '#pragma omp parallel for' and manage the scope of shared and private variables

Implement aggregation operations efficiently using OpenMP reduction clauses

Use OpenMP synchronization constructs (critical, atomic, barrier) to prevent race conditions

Implement task-based parallelism using OpenMP tasks for irregular workloads

Describe the performance trade-offs of fine-grained versus coarse-grained locking

Diagnose and mitigate false sharing to improve cache performance in OpenMP applications