Deferred methods: accelerating dynamic program analysis on multicores

  • Authors:

  • Danilo Ansaloni;Walter Binder;Abbas Heydarnoori;Lydia Y. Chen

  • Affiliations:

  • University of Lugano, Lugano, Switzerland;University of Lugano, Lugano, Switzerland;University of Lugano, Lugano, Switzerland;IBM Research, Zürich Laboratory, Rüschlikon, Switzerland

  • Venue:
  • Proceedings of the Tenth International Symposium on Code Generation and Optimization
  • Year:
  • 2012

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Abstract

Parallelization is attractive for speeding up dynamic program analysis on multicores. However, inter-thread communication overhead may outweigh any benefit from parallel execution. We propose deferred methods, a high-level Java framework to accelerate dynamic analysis on multicores. To minimize inter-thread communication overhead, invocations to analysis methods are automatically aggregated in thread-local buffers that are processed when full. In contrast to other approaches, our framework supports custom buffer processing strategies, eases pre-processing of buffers to reduce contention on shared data structures, and offers a synchronization mechanism to wait for the completion of previously invoked deferred methods. We also present a novel adaptive buffer processing strategy that parallelizes the analysis only when the observed workload leaves some CPU cores under-utilized. Using a profiler as case study, we show that deferred methods with the adaptive buffer processing strategy yield an average speedup of factor 4.09 on a quad-core machine. The speedup stems both from parallelization and from reduced contention.