A generational on-the-fly garbage collector for Java

  • Authors:
  • Tamar Domani;Elliot K. Kolodner;Erez Petrank

  • Affiliations:
  • IBM Haifa Research Lab.;IBM Haifa Research Lab.;Computer Science Dept., Technion - Israel Institute of Technology

  • Venue:
  • PLDI '00 Proceedings of the ACM SIGPLAN 2000 conference on Programming language design and implementation
  • Year:
  • 2000

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Abstract

An on-the-fly garbage collector does not stop the program threads to perform the collection. Instead, the collector executes in a separate thread (or process) in parallel to the program. On-the-fly collectors are useful for multi-threaded applications running on multiprocessor servers, where it is important to fully utilize all processors and provide even response time, especially for systems for which stopping the threads is a costly operation. In this work, we report on the incorporation of generations into an on-the-fly garbage collector. The incorporation is non-trivial since an on-the-fly collector avoids explicit synchronization with the program threads. To the best of our knowledge, such an incorporation has not been tried before. We have implemented the collector for a prototype Java Virtual Machine on AIX, and measured its performance on a 4-way multiprocessor.As for other generational collectors, an on-the-fly generationalcollector has the potential for reducing the overall running time and working set of an application by concentrating collection efforts on the young objects. However, in contrast to other generational collectors,on-the-fly collectors do not move the objects; thus, there is no segregation between the old and the young objects. Furthermore, on-the-fly collectors do not stop the threads, so there is no extra benefit for the short pauses obtained by generational collection. Nevertheless, comparing our on-the-fly collector with and without generations, it turns out that the generational collector performs better for most applications. The best reduction in overall running time for the benchmarks we measured was 25%. However, there were some benchmarks for which it had no effect and one for which the overall running time increased by 4%.