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Tree rerooting in distributed garbage collection: implementation and performance evaluation

Tree rerooting in distributed garbage collection: implementation and performance evaluation
Tree rerooting in distributed garbage collection: implementation and performance evaluation
We have recently defined a new algorithm for distributed garbage collection based on reference-counting [Moreau ICFP98,Moreau-Duprat ENS99]. At the heart of the algorithm, we find "tree rerooting", a mechanism able to reduce third-party dependencies by reorganising diffusion trees. In reality, the algorithm describes a spectrum of algorithms according to the policy used to manage messages. In this paper, we present the implementation of the algorithm and evaluate its performance. We have implemented two policies, which are extremes of the spectrum, respectively using and not using tree rerooting. In addition, two different strategies for managing action queues have been implemented. The conclusions of our experimentations are the following. Tree rerooting offers more parallelism during distributed GC activity; we explain this phenomenon by the length reduction of causality chains in the distributed GC. Grouping messages per destination dramatically reduces the number of messages, but requires a more complex implementation as messages have to be sorted per destination. Speed up of 100% has been observed on some benchmarks.
1388-3690
357
Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8

Moreau, Luc (2001) Tree rerooting in distributed garbage collection: implementation and performance evaluation. Higher-Order and Symbolic Computation, 14 (4), 357.

Record type: Article

Abstract

We have recently defined a new algorithm for distributed garbage collection based on reference-counting [Moreau ICFP98,Moreau-Duprat ENS99]. At the heart of the algorithm, we find "tree rerooting", a mechanism able to reduce third-party dependencies by reorganising diffusion trees. In reality, the algorithm describes a spectrum of algorithms according to the policy used to manage messages. In this paper, we present the implementation of the algorithm and evaluate its performance. We have implemented two policies, which are extremes of the spectrum, respectively using and not using tree rerooting. In addition, two different strategies for managing action queues have been implemented. The conclusions of our experimentations are the following. Tree rerooting offers more parallelism during distributed GC activity; we explain this phenomenon by the length reduction of causality chains in the distributed GC. Grouping messages per destination dramatically reduces the number of messages, but requires a more complex implementation as messages have to be sorted per destination. Speed up of 100% has been observed on some benchmarks.

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More information

Published date: December 2001
Additional Information: (Coloured figures can be found in http://www.ecs.soton.ac.uk/~lavm/papers/hosc01-colour.tar.gz)
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 256397
URI: http://eprints.soton.ac.uk/id/eprint/256397
ISSN: 1388-3690
PURE UUID: d758786c-b5c7-4c48-a43e-bd3a2d5ce26b
ORCID for Luc Moreau: ORCID iD orcid.org/0000-0002-3494-120X

Catalogue record

Date deposited: 22 Mar 2002
Last modified: 14 Mar 2024 05:42

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Contributors

Author: Luc Moreau ORCID iD

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