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ProRace: Practical data race detection for production use

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

21 Scopus citations

Abstract

This paper presents PRORACE, a dynamic data race detector practical for production runs. It is lightweight, but still offers high race detection capability. To track memory accesses, PRORACE leverages instruction sampling using the performance monitoring unit (PMU) in commodity processors. Our PMU driver enables PRORACE to sample more memory accesses at a lower cost compared to the state-of-the-art Linux driver. Moreover, PRORACE uses PMU-provided execution contexts including register states and program path, and reconstructs unsampled memory accesses offline. This technique allows PRORACE to overcome inherent limitations of sampling and improve the detection coverage by performing data race detection on the trace with not only sampled but also reconstructed memory accesses. Experiments using racy production software including apache and mysql shows that, with a reasonable offline cost, PRORACE incurs only 2.6% overhead at runtime with 27.5% detection probability with a sampling period of 10,000.

Original languageEnglish
Title of host publicationASPLOS 2017 - 22nd International Conference on Architectural Support for Programming Languages and Operating Systems
PublisherAssociation for Computing Machinery
Pages149-162
Number of pages14
ISBN (Electronic)9781450344654
DOIs
StatePublished - Apr 4 2017
Event22nd International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2017 - Xi'an, China
Duration: Apr 8 2017Apr 12 2017

Publication series

NameInternational Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS
VolumePart F127193

Conference

Conference22nd International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2017
Country/TerritoryChina
CityXi'an
Period04/8/1704/12/17

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