earticle

영어

It is difficult and troublesome to detect data races occurred in an execution of parallel programs. On-the-fly race detection techniques use monitoring to threads and events, which access to shared variables. Any of them using Lamport's happened-before relation needs a thread labeling scheme for generating unique identifiers which maintain logical concurrency information of the parallel threads. Previous labeling schemes for on-the-fly race detection in parallel programs with nested parallelism depend on the nesting depth on every fork and join operation. This paper presents e-NR (Extended Nest Region) labeling in which every thread generates and maintains its label in a constant amount of time and space. Experimental results using OpenMP programs show that presented labeling detects data races more efficiently, because it requires reduced time overhead about 10% and it 3.2 times smaller than previous labeling scheme in average space for race detection.