NDLI: SmartStealing: Analysis and Optimization of Work Stealing in Parallel Garbage Collection for Java VM

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SmartStealing: Analysis and Optimization of Work Stealing in Parallel Garbage Collection for Java VM

SmartStealing: Analysis and Optimization of Work Stealing in Parallel Garbage Collection for Java VM

Content Provider	ACM Digital Library
Author	Srisa-an, Witawas Jiang, Hong Seth, Sharad Yang, Yaodong Li, Du Qian, Junjie
Abstract	Parallel garbage collection has been used to speedup the collection process on multicore architectures. Similar to other parallel techniques, balancing the workload among threads is critical to ensuring good overall collection performance. To this end, work stealing is employed by the current state-of-the-art Java Virtual Machine, OpenJDK, to keep GC threads from idling during a collection process. However, we found that the current algorithm is not efficient. Its usage can often cause GC performance to be worse than when work stealing is not used. In this paper, we identify three factors that affect work stealing efficiency: determining tasks that can benefit from stealing, frequency with which to attempt stealing, and performance impacts of failed stealing attempts. Based on this analysis, we propose SmartStealing, a new algorithm that can automatically decide whether to attempt stealing at a particular point during execution. If stealing is attempted, it can efficiently identify a task to steal from. We then compare the collection performances when (i) the default work stealing algorithm is used, (ii) work stealing is not used at all, and (iii) the SmartStealing approach is used. Without modifying the remaining garbage collection system, the evaluation result shows that SmartStealing can reduce the parallel GC execution time for 19 of the 21 benchmarks. The average reduction is 50.4% and the highest reduction is 78.7%. We also investigate the performances of SmartStealing on NUMA and UMA architectures.
Starting Page	170
Ending Page	181
Page Count	12
File Format	PDF
ISBN	9781450337120
DOI	10.1145/2807426.2807441
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-09-08
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Work stealing Parallel garbage collection
Content Type	Text
Resource Type	Article

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