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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

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Research group:
Information Systems Group
Oxford college:
Somerville College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Research group:
Information Systems Group
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Research group:
Information Systems Group
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Research group:
Information Systems Group
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Research group:
Information Systems Group
Oxford college:
St Cross College
Role:
Author
More from this funder
Funding agency for:
Motik, B
Grant:
EP/K00607X/1
More from this funder
Funding agency for:
Nenov, Y
Grant:
EP/J020214/1
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:
2014-01-01
ISSN:
2159-5399
ISBN:
9781577356615
Language:
English
Keywords:
Subjects:
UUID:
uuid:5800d74f-b9f6-4b12-9908-a45be70b29d2
Local pid:
ora:9552
Deposit date:
2014-12-08

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