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On-the-fly Data Race Detection with the Enhanced OpenMP Series-Parallel Graph

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OpenMP: Portable Multi-Level Parallelism on Modern Systems (IWOMP 2020)

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Abstract

This paper proposes OMP-RACER, a dynamic apparent data race detector for OpenMP programs. Apparent data races are those races that manifest in a program considering the logical series-parallel relations of the execution. By identifying apparent races, OMP-RACER can detect races that occur not only in the observed schedule but also in other schedules for a given input. Our key contribution is a data structure to capture series-parallel relations between various fragments of an OpenMP program with both structured and unstructured parallelism directives, which we call the Enhanced OpenMP Series-Parallel Graph (EOSPG). OMP-RACER maintains information about previous accesses with each memory access and uses the EOSPG to check if they can logically execute in parallel. OMP-RACER detects more races with similar overheads when compared to existing state-of-the-art race detectors for OpenMP programs.

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Acknowledgments

We thank the reviewers for their feedback. This paper is based on work supported in part by NSF CAREER Award CCF–1453086, NSF Award CCF-1908798, and NSF Award CCF-1917897.

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Authors and Affiliations

  1. Rutgers University, New Brunswick, NJ, 08901, USA

    Nader Boushehrinejadmoradi, Adarsh Yoga & Santosh Nagarakatte

Authors
  1. Nader Boushehrinejadmoradi
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  2. Adarsh Yoga
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  3. Santosh Nagarakatte
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Corresponding author

Correspondence to Nader Boushehrinejadmoradi .

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Editors and Affiliations

  1. Texas Advanced Computing Center (TACC), Austin, TX, USA

    Kent Milfeld

  2. Lawrence Livermore National Laboratory, Livermore, CA, USA

    Bronis R. de Supinski

  3. Texas Advanced Computing Center (TACC), Austin, TX, USA

    Lars Koesterke

  4. RWTH Aachen University, Aachen, Germany

    Jannis Klinkenberg

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Boushehrinejadmoradi, N., Yoga, A., Nagarakatte, S. (2020). On-the-fly Data Race Detection with the Enhanced OpenMP Series-Parallel Graph. In: Milfeld, K., de Supinski, B., Koesterke, L., Klinkenberg, J. (eds) OpenMP: Portable Multi-Level Parallelism on Modern Systems. IWOMP 2020. Lecture Notes in Computer Science(), vol 12295. Springer, Cham. https://doi.org/10.1007/978-3-030-58144-2_10

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  • DOI: https://doi.org/10.1007/978-3-030-58144-2_10

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  • Online ISBN: 978-3-030-58144-2

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