Dynamic prediction of collection yield for managed runtimes

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Dynamic prediction of collection yield for managed runtimes
The growth in complexity of modern systems makes it increasingly difficult to extract high-performance. The software stacks for such systems typically consist of multiple layers and include managed runtime environments (MREs). In this paper, we investigate techniques to improve cooperation between these layers and the hardware to increase the efficacy of automatic memory management in MREs. General-purpose MREs commonly implement parallel and/or concurrent garbage collection and employ compaction to eliminate heap fragmentation. Moreover, most systems trigger collection based on the amount of heap a program uses. Our analysis shows that in many cases this strategy leads to ineffective collections that are unable to reclaim sufficient space to justify the incurred cost. To avoid such collections, we exploit the observation that dead objects tend to cluster together and form large, never-referenced, regions in the address space that correlate well with virtual pages that have not recent...
Michal Wegiel, Chandra Krintz
Added 22 Nov 2009
Updated 22 Nov 2009
Type Conference
Year 2009
Authors Michal Wegiel, Chandra Krintz
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