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

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,...

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Detalhes bibliográficos
Principais autores: Motik, B, Nenov, Y, Piro, R, Horrocks, I, Olteanu, D
Formato: Conference item
Idioma:English
Publicado em: Association for the Advancement of Artificial intelligence 2014
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Descrição
Resumo: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.