Abstract
Since data races result in unintended nondeterministic executions of the programs, detecting the races is important for debugging shared memory programs with nested parallelism. Particularly, the first races to occur in an execution of a program must be detected, because they can potentially affect other races that occur later. Previous on-the-fly techniques are inefficient or can not guarantee to verify the existence of the first tangle of data races to occur. This paper presents an efficient two-pass on-the-fly technique in such a kind of programs. This technique is still efficient with regard to the execution time and memory space by keeping a constant number of accesses involved in the first races for each shared variable during the execution. We empirically compare our technique with previous techniques using a set of synthetic programs with OpenMP directives.
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2011-0026340).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chandra, R., Menon, R., Dagum, L., Kohr, D., Maydan, D., McDonald, D.: Parallel programming in openmp
Dagum, L., Menon, R.: Openmp: An industry-standard api for shared-memory programming. In: IEEE Computational Science, pp. 46–55. IEEE (January/March 1998)
Dinning, A., Schonberg, E.: An empirical comparison of monitoring algorithms for access anomaly detection. SIGPLAN Not. 25, 1–10 (1990)
Ha, K., Jun, Y.J., Yoo, K.: Efficient on-the-fly detection of first races in nested parallel programs. In: Proc. of Workshop on State-of-the-Art in Scientific Computing, PARA 2004. LNCS, pp. 75–84 (2004)
Helmbold, D.P., McDowell, C.E.: A taxonomy of race conditions. J. Parallel Distrib. Comput. 33, 159–164 (1996)
Jun, Y.K., Koh, K.: On-the-fly detection of access anomalies in nested parallel loops. SIGPLAN Not. 28, 107–117 (1993)
Jun, Y.K., McDowell, C.E.: On-the-fly detection of the first races in programs with nested parallelism. In: 2nd Conf. on Parallel and Distributed Processing Technique and Application, CSREA, pp. 1549–1560 (1996)
Kim, J.S., Jun, Y.K.: Scalable on-the-fly detection of the first races in parallel programs. In: Proceedings of the 12th International Conference on Supercomputing, ICS 1998, pp. 345–352. ACM, New York (1998)
Lamport, L.: Ti clocks, and the ordering of events in a distributed system. Commun. ACM 21, 558–565 (1978)
Mellor-Crummey, J.: On-the-fly detection of data races for programs with nested fork-join parallelism. In: Proceedings of the 1991 ACM/IEEE Conference on Supercomputing, Supercomputing 1991, pp. 24–33. ACM, New York (1991)
Netzer, R.H.B., Miller, B.P.: What are race conditions?: Some issues and formalizations. ACM Lett. Program. Lang. Syst. 1, 74–88 (1992)
Netzer, R.H.B., Miller, B.P.: Openmp architecture review board (2008)
Park, H.D., Jun, Y.K.: Two-pass on-the-fly detection of the first races in shared-memory parallel. In: Proceedings of the SIGMETRICS Symposium on Parallel and Distributed Tools, SPDT 1998, p. 158. ACM, New York (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kang, MH., Jun, YK. (2011). Efficient Verification of First Tangled Races to Occur in Programs with Nested Parallelism. In: Kim, Th., et al. Software Engineering, Business Continuity, and Education. ASEA 2011. Communications in Computer and Information Science, vol 257. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27207-3_49
Download citation
DOI: https://doi.org/10.1007/978-3-642-27207-3_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27206-6
Online ISBN: 978-3-642-27207-3
eBook Packages: Computer ScienceComputer Science (R0)