Dynamic Data Race Detection for OpenMP Programs

Two concurrent accesses to a shared variable that are unordered by synchronization are said to be a data race if at least one access is a write. Data races cause shared memory parallel programs to behave unpredictably. This paper describes ROMP - a tool for detecting data races in executions of scalable parallel applications that employ OpenMP for node-level parallelism. The complexity of OpenMP, which includes primitives for managing data environments, SPMD and SIMD parallelism, work sharing, tasking, mutual exclusion, and ordering, presents a formidable challenge for data race detection. ROMP is a hybrid data race detector that tracks accesses, access orderings and mutual exclusion. Unlike other OpenMP race detectors, ROMP detects races with respect to concurrency rather than implementation threads. Experiments show that ROMP yields precise race reports for a broader set of OpenMP constructs than prior state-of-the-art race detectors.