RDFS Reasoning on Massively Parallel Hardware

Norman Heino, Jeff Z Pan

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

30 Citations (Scopus)


Recent developments in hardware have shown an increase in parallelism as opposed to clock rates. In order to fully exploit these new avenues of performance improvement, computationally expensive workloads have to be expressed in a way that allows for fine-grained parallelism. In this paper, we address the problem of describing RDFS entailment in such a way. Different from previous work on parallel RDFS reasoning, we assume a shared memory architecture. We analyze the problem of duplicates that naturally occur in RDFS reasoning and develop strategies towards its mitigation, exploiting all levels of our architecture. We implement and evaluate our approach on two real-world datasets and study its performance characteristics on different levels of parallelization. We conclude that RDFS entailment lends itself well to parallelization but can benefit even more from careful optimizations that take into account intricacies of modern parallel hardware.
Original languageEnglish
Title of host publicationThe Semantic Web – ISWC 2012
Subtitle of host publication11th International Semantic Web Conference, Boston, MA, USA, November 11-15, 2012, Proceedings, Part I
EditorsPhilippe Cudre-Mauroux, Jeff Heflin, Evren Sirin, Tania Tudorache, Jerome Euzenat, Manfred Hauswirth, Josiane Xavier Parreira, Jim Hendler, Guus Schreiber, Abraham Bernstein, Eva Blomqvist
Number of pages16
ISBN (Electronic)978-3-642-35176-1
ISBN (Print)978-3-642-35175-4
Publication statusPublished - 2012


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