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A Parallel Computing Architecture for High-Performance OWL Reasoning


A Parallel Computing Architecture for High-Performance OWL Reasoning

Quan, Zixi and Haarslev, Volker (2018) A Parallel Computing Architecture for High-Performance OWL Reasoning. Parallel Computing . ISSN 01678191 (In Press)

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Official URL: http://dx.doi.org/10.1016/j.parco.2018.05.001


The Web Ontology Language (OWL) is a widely used knowledge representation language for describing knowledge in application domains by using classes, properties, and individuals. Ontology classification is an important and widely used service that computes a taxonomy of all classes occurring in an ontology. It can require significant amounts of runtime, but most OWL reasoners do not support any kind of parallel processing. We present a novel thread-level parallel architecture for ontology classification, which is ideally suited for shared-memory SMP servers, but does not rely on locking techniques and thus avoids possible race conditions. We evaluated our prototype implementation with a set of real-world ontologies. Our experiments demonstrate a very good scalability resulting in a speedup that is linear to the number of available cores.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Article
Authors:Quan, Zixi and Haarslev, Volker
Journal or Publication:Parallel Computing
Date:16 May 2018
Digital Object Identifier (DOI):10.1016/j.parco.2018.05.001
Keywords:Ontology classification; parallel computing
ID Code:983894
Deposited On:28 May 2018 14:33
Last Modified:16 May 2020 00:00


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