Abstract
Detecting races is important for debugging shared-memory parallel programs, because the races result in unintended nondeterministic executions of the programs. Previous on-the-fly techniques to detect races have a bottleneck caused by the need to check or serialize all accesses to each shared variable in a program that may have nested parallelism with barrier synchronization. The new scalable monitoring technique in this paper reduces the bottleneck significantly by c necking or serializing at most 2(B + 1) non-nested accesses in an iteration for each shared variable, where B is the number of barrier operations in the iteration. This technique, therefore, makes on-the-fly race detection more scalable.
University Research Program supported by Ministry of Information and communication in South Korea.
In Gyeongsang National University, he is also involved in both In both Institute of Computer Research and Development, and Information and Communication Research Center, as a research professor.
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Jun, YK., McDowell, C.E. (2000). Scalable Monitoring Technique for Detecting Races in Parallel Programs. In: Rolim, J. (eds) Parallel and Distributed Processing. IPDPS 2000. Lecture Notes in Computer Science, vol 1800. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45591-4_44
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DOI: https://doi.org/10.1007/3-540-45591-4_44
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