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Parallel materialisation of datalog programs in centralised, main-memory RDF systems

Abstract:

We present a novel approach to parallel materialisation (i.e., fixpoint computation) of datalog programs in centralised, main-memory, multi-core RDF systems. Our approach comprises an algorithm that evenly distributes the workload to cores, and an RDF indexing data structure that supports efficient, ‘mostly’ lock-free parallel updates. Our empirical evaluation shows that our approach parallelises computation very well: with 16 physical cores, materialisation can be up to 13.9 times faster than with just one core.

Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Institution:
University of Oxford
Research group:
Information Systems Group
Oxford college:
Somerville College
Department:
MPLS, Department of Computer Science
More by this author
Institution:
University of Oxford
Research group:
Information Systems Group
Department:
MPLS, Department of Computer Science
More by this author
Institution:
University of Oxford
Research group:
Information Systems Group
Department:
MPLS, Department of Computer Science
More by this author
Institution:
University of Oxford
Research group:
Information Systems Group
Department:
MPLS,Department of Computer Science
More by this author
Institution:
University of Oxford
Research group:
Information Systems Group
Oxford college:
St Cross College
Department:
MPLS, Department of Computer Science
Publisher:
Association for the Advancement of Artificial intelligence Publisher's website
Volume:
1
Host title:
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence and the Twenty-Sixth Innovative Applications of Artificial Intelligence Conference
Publication date:
2014
ISSN:
2159-5399
URN:
uuid:5800d74f-b9f6-4b12-9908-a45be70b29d2
Local pid:
ora:9552
ISBN:
978-1-57735-661-5

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