The Future of Virtual Machine Performance
Speaker: Matthew Arnold , IBM T.J. Watson Research CenterContact:
Date: February 15 2006
Time: 11:00AM to 12:00PM
Location: Star Conference Room 32-D463
Host: Martin Rinard, MIT-CSAIL
Mary McDavitt, 617-253-9620, email@example.com
Users of virtual machines care most about two aspects of performance: startup and throughput. In this talk, I will give a brief overview of the techniques commercial VMs use to improve these aspects of performance, and discuss the challenges that still remain. I will then present two new, nontraditional approaches for making progress in these areas.
1) Improving startup performance using a cross-run profile repository (OOPSLA'05). Despite the important role that profiling plays in achieving high performance, current virtual machines discard a program's profile data at the end of execution. Our work presents a fully automated architecture for exploiting cross-run profile data in virtual machines. This work addresses a number of challenges that previously limited the practicality of such an approach.
2) Throughput performance: "Online Performance Auditing" (PLDI'06). This work describes an online framework for evaluating the effectiveness of optimizations, enabling an online system to automatically identify and correct performance anomalies that occur at runtime. This work encourages a shift in the way optimizations are developed and tuned for online systems, and may allow much of the work in offline empirical optimization search to be applied automatically at runtime.
All of this work is implemented and evaluated using IBM's product J9 Java Virtual Machine.
Matthew Arnold received his Ph.D. from Rutgers University in 2002, and is now a Research Staff Member at the IBM T.J. Watson Research Center in Hawthorne, NY. For his thesis work he developed low-overhead profiling techniques and showed how they can be used to drive feedback-directed optimization in a virtual machine; this work is currently used in IBM's product JVM. He has worked with the Jikes Research Virtual Machine and IBM's production JVM, and continues to use both for his research. His current interests include virtual machine performance, low overhead profiling, and dynamic analysis of software.
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