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A comprehensive toolchain for workload characterization across JVM languages

Sarimbekov, Aibek, Sewe, Andreas, Kell, Stephen, Zheng, Yudi, Binder, Walter, Bulej, Lubom\'r, Ansaloni, Danilo (2013) A comprehensive toolchain for workload characterization across JVM languages. In: Proceedings of the 11th ACM SIGPLAN-SIGSOFT Workshop on Program Analysis for Software Tools and Engineering. . pp. 9-16. ACM, USA, New York ISBN 978-1-4503-2128-0. (doi:10.1145/2462029.2462033) (KAR id:69711)

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The Java Virtual Machine (JVM) today hosts implementations of numerous languages. To achieve high performance, JVM implementations rely on heuristics in choosing compiler optimizations and adapting garbage collection behavior. Historically, these heuristics have been tuned to suit the dynamics of Java programs only. This leads to unnecessarily poor performance in case of non-Java languages, which often exhibit systematic differences in workload behavior. Dynamic metrics characterizing the workload help to identify and quantify useful optimizations, but so far, no cohesive suite of metrics has adequately covered properties that vary systematically between Java and non-Java workloads. We present a suite of such metrics, justifying our choice with reference to a range of guest languages. These metrics are implemented on a common portable infrastructure which ensures ease of deployment and customization.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1145/2462029.2462033
Uncontrolled keywords: Workload characterization, dynamic program analysis, bytecode instrumentation, dynamic metrics
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Stephen Kell
Date Deposited: 25 Jan 2019 14:21 UTC
Last Modified: 16 Nov 2021 10:25 UTC
Resource URI: (The current URI for this page, for reference purposes)
Kell, Stephen:
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