Pretenuring for Java

  • Authors:

  • Stephen M. Blackburn;Sharad Singhai;Matthew Hertz;Kathryn S. McKinely;J. Eliot B. Moss

  • Affiliations:

  • Arthitecture and Language Implementation Laboratory, Department of Computer Science, University of Massachusetts, Amherst, MA;Arthitecture and Language Implementation Laboratory, Department of Computer Science, University of Massachusetts, Amherst, MA;Arthitecture and Language Implementation Laboratory, Department of Computer Science, University of Massachusetts, Amherst, MA;Arthitecture and Language Implementation Laboratory, Department of Computer Science, University of Massachusetts, Amherst, MA;Arthitecture and Language Implementation Laboratory, Department of Computer Science, University of Massachusetts, Amherst, MA

  • Venue:
  • OOPSLA '01 Proceedings of the 16th ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
  • Year:
  • 2001

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Abstract

Pretenuring can reduce copying costs in garbage collectors by allocating long-lived objects into regions that the garbage collector with rarely, if ever, collect. We extend previous work on pretenuring as follows. (1) We produce pretenuring advice that is neutral with respect to the garbage collector algorithm and configuration. We thus can and do combine advice from different applications. We find that predictions using object lifetimes at each allocation site in Java prgroams are accurate, which simplifies the pretenuring implementation. (2) We gather and apply advice to applications and the Jalapeño JVM, a compiler and run-time system for Java written in Java. Our results demonstrate that building combined advice into Jalapeño from different application executions improves performance regardless of the application Jalapeño is compiling and executing. This build-time advice thus gives user applications some benefits of pretenuring without any application profiling. No previous work pretenures in the run-time system. (3) We find that application-only advice also improves performance, but that the combination of build-time and application-specific advice is almost always noticeably better. (4) Our same advice improves the performance of generational and Older First colleciton, illustrating that it is collector neutral.