Parallel materialisation of datalog programs in centralised, main-memory RDF systems - Motik, B; Nenov, Y; Piro, R; Horrocks, I; Olteanu, D (Association for the Advancement of Artificial intelligence, 2014)
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.