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The Compressor

concurrent, incremental, and parallel compaction
Authors: Haim Kermany; Erez Petrank;

The Compressor

Abstract

The widely used Mark-and-Sweep garbage collector has a drawback in that it does not move objects during collection. As a result, large long-running realistic applications, such as Web application servers, frequently face the fragmentation problem. To eliminate fragmentation, a heap compaction is run periodically. However, compaction typically imposes very long undesirable pauses in the application. While efficient concurrent collectors are ubiquitous in production runtime systems (such as JVMs), an efficient non-intrusive compactor is still missing.In this paper we present the Compressor, a novel compaction algorithm that is concurrent, parallel, and incremental. The Compressor compacts the entire heap to a single condensed area, while preserving the objects' order, but reduces pause times significantly, thereby allowing acceptable runs on large heaps. Furthermore, the Compressor is the first compactor that requires only a single heap pass. As such, it is the most efficient compactors known today, even when run in a parallel Stop-the-World manner (i.e., when the program threads are halted). Thus, to the best of our knowledge, the Compressor is the most efficient compactor known today. The Compressor was implemented on a Jikes Research RVM and we provide measurements demonstrating its qualities.

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
60
Top 10%
Top 10%
Top 10%
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