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Scalable Monitoring Technique for Detecting Races in Parallel Programs

  • Yong-Kee Jun
  • Charles E. McDowell
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1800)

Abstract

Detecting races is important for debugging shared-memory parallel programs, because the races result in unintended nondeterministic executions of the programs. Previous on-the-fly techniques to detect races have a bottleneck caused by the need to check or serialize all accesses to each shared variable in a program that may have nested parallelism with barrier synchronization. The new scalable monitoring technique in this paper reduces the bottleneck significantly by c necking or serializing at most 2(B + 1) non-nested accesses in an iteration for each shared variable, where B is the number of barrier operations in the iteration. This technique, therefore, makes on-the-fly race detection more scalable.

Keywords

Parallel Program Shared Variable Parallel Loop Nest Level Shared Memory System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Yong-Kee Jun
    • 1
    • 3
  • Charles E. McDowell
    • 2
  1. 1.Dept. of Computer ScienceGyeongsang National UniversityChinjuSouth Korea
  2. 2.Computer Science DepartmentUniversity of CaliforniaSanta CruzUSA
  3. 3.Institute of Computer Research and Development, and Information and Communication Research CenterGyeongsang National UniversityGyeongsang

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