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A NOTE ON THE IMPLEMENTATION OF REPLICATION-BASED GARBAGE COLLECTION FOR MULTITHREADED APPLICATIONS AND MULTIPROCESSOR ENVIRONMENTS

Authors: ALAIN AZAGURY; ELLIOT K. KOLODNER; EREZ PETRANK;

A NOTE ON THE IMPLEMENTATION OF REPLICATION-BASED GARBAGE COLLECTION FOR MULTITHREADED APPLICATIONS AND MULTIPROCESSOR ENVIRONMENTS

Abstract

Replication-based incremental garbage collection is one of the more appealing concurrent garbage collection algorithms known today. It allows continuous operation of the application (the mutator) with very short pauses for garbage collection. There is a growing need for such garbage collectors suitable for a multithreaded environments such as the Java Virtual Machine. Furthermore, it is desirable to construct collectors that also work on multiprocessor computers. We begin by pointing out an important, yet subtle point, which arises when implementing the replication-based garbage collector for a multithreaded environment. We first show that a simple and natural implementation of the algorithm may lead to an incorrect behavior of multithreaded applications. We then show that another simple and natural implementation eliminates the problem completely. Thus, the contribution of this part is in stressing this warning to future implementors. Next, we address the effects of the memory coherence model on this algorithm. We show that even when the algorithm is properly implemented with respect to our first observation, a problem might still arise when a multiprocessor system is used. Adopting a naive solution to this problem results in very frequent (and expensive) synchronization. We offer a slight modification to the algorithm which eliminates the problem and requires little synchronization.

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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!
2
Average
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