Task-aware garbage collection in a multi-tasking virtual machine

  • Authors:

  • Sunil Soman;Laurent Daynès;Chandra Krintz

  • Affiliations:

  • University of California, Santa Barbara, Santa Barbara, CA;Sun Microsystems Inc., Montbonnot St-Martin, France;University of California, Santa Barbara, Santa Barbara, CA

  • Venue:
  • Proceedings of the 5th international symposium on Memory management
  • Year:
  • 2006

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Abstract

A multi-tasking virtual machine (MVM) executes multiple programs in isolation, within a single operating system process. The goal of a MVM is to improve startup time, overall system throughput, and performance, by effective reuse and sharing of system resources across programs (tasks). However, multitasking also mandates a memory management system capable of offering a guarantee of isolation with respect to garbage collection costs, accounting of memory usage, and timely reclamation of heap resources upon task termination.To this end, we investigate and evaluate, novel task-aware extensions to a state-of-the-art MVM garbage collector (GC). Our task-aware GC exploits the generational garbage collection hypothesis, in the context of multiple tasks, to provide performance isolation by maintaining task-private young generations. Task aware GC facilitates concurrent per-task allocation and promotion, and minimizes synchronization and scanning overhead. In addition, we efficiently track per-task heap usage to enable GC-free reclamation upon task termination. Moreover, we couple these techniques with a light-weight synchronization mechanism that enables per-task minor collection, concurrently with allocation by other tasks.We empirically evaluate the efficiency, scalability, and through-put that our task-aware GC system enables.