Publication | Closed Access
PACER
253
Citations
41
References
2010
Year
Unknown Venue
Cluster ComputingEngineeringData RacesData ScienceData-level ParallelismProgram AnalysisSerious Concurrency BugsConcurrent ProgrammingParallel Performance EvaluationComputer EngineeringComputer ArchitectureSequential Consistency ViolationsParallel ProgrammingComputer ScienceConcurrent Data StructureParallel ComputingData ManagementBig Data
Data races indicate serious concurrency bugs such as order, atomicity, and sequential consistency violations. Races are difficult to find and fix, often manifesting only after deployment. The frequency and unpredictability of these bugs will only increase as software adds parallelism to exploit multicore hardware. Unfortunately, sound and precise race detectors slow programs by factors of eight or more and do not scale to large numbers of threads.
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