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Wednesday, October 23 • 4:25pm - 4:50pm
Improving J9 Java Virtual Machine with LTTng for Efficient & Effective Tracing, Yang Wang, University of New Brunswick

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The ability to observe the internal operation of the J9 virtual machine is essential for effective performance tuning. To this end, tracing is an important method, which is the action of recording events from a running system with minimum performance overhead for online or off-line analysis. In this paper, we propose the integration of LTTng, an effective opensource tracing toolset, with J9 to improve its tracing functions. With this integration, the tracing component is not only decoupled from the virtual machine but also performed efficiently at both user and kernel levels to achieve a high-throughput result. To validate the integration and its impact performance, some empirical study results based on the SpecJBB2005 and SQLBenchmark are also presented.


Yang Wang

PDF, IBM CAS Atlantic
Yang Wang is currently at IBM Center for Advanced Studies (CAS), Atlantic, University of New Brunswick, Fredericton, Canada. Before joining CAS Atlantic in 2012, he was a research fellow at the National University of Singapore from November 2010 to 2012. In 2009, he was awarded by... Read More →

Wednesday October 23, 2013 4:25pm - 4:50pm BST
Harris Suite

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