Towards providing low-overhead data race detection for large OpenMP applications

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Publication Type pre-print
School or College College of Engineering
Department Computing, School of
Creator Gopalakrishnan, Ganesh
Other Author Protze, Joachim; Atzeni, Simone; Ahn, Dong H.; Schulz, Martin; Müller, Matthias S.; Laguna, Ignacio; Rakamarić, Zvonimir; Lee, Greg L.
Title Towards providing low-overhead data race detection for large OpenMP applications
Date 2014-01-01
Description Neither static nor dynamic data race detection methods, by themselves, have proven to be sufficient for large HPC applications, as they often result in high runtime overheads and/or low race-checking accuracy. While combined static and dynamic approaches can fare better, creating such combinations, in practice, requires attention to many details. Specifically, existing state of the art dynamic race detectors are aimed at low level threading models, and cannot handle high level models such as OpenMP. Further, they do not provide mechanisms by which static analysis methods can target selected regions of code with sufficient precision. In this paper, we present our solutions to both challenges. Specifically, we identify patterns within OpenMP run times that tend to mislead existing dynamic race checkers and provide mechanisms that help establish an explicit happens before relation to prevent such misleading checks. We also implement a fine-grained blacklist mechanism to allow a runtime analyzer to exclude regions of code at line number granularity. We support race checking by adapting Thread Sanitizer, a mature data-race checker developed at Google that is now an integral part of Clang and GCC; and we have implemented our techniques within the state-of-the-art Intel OpenMP Runtime. Our results demonstrate that these techniques can significantly improve run time analysis accuracy and overhead in the context of data race checking of Open MP applications.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
First Page 40
Last Page 47
Language eng
Bibliographic Citation Protze, J., Atzeni, S., Ahn, D. H., Schulz, M., Gopalakrishnan, G., Müller, M. S., Laguna, I., Rakamarić, Z., & Lee, G. L. (2014). Towards providing low-overhead data race detection for large OpenMP applications. The International Conference for High Performance Computing, Networking, Storage and Analysis, 40-7.
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Format Medium application/pdf
Format Extent 410,084 bytes
Identifier uspace,19411
ARK ark:/87278/s61s00pq
Setname ir_uspace
Date Created 2015-05-04
Date Modified 2021-05-06
ID 713036
Reference URL https://collections.lib.utah.edu/ark:/87278/s61s00pq
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