High-performance computing applied to semantic databases

Authors:
Eric L. Goodman;Edward Jimenez;David Mizell;Sinan al-Saffar;Bob Adolf;David Haglin
Affiliations:
Sandia National Laboratories, Albuquerque, NM;Sandia National Laboratories, Albuquerque, NM;Cray, Inc., Seattle, WA;Pacific Northwest National Laboratory, Richland, WA;Pacific Northwest National Laboratory, Richland, WA;Pacific Northwest National Laboratory, Richland, WA
Venue:
ESWC'11 Proceedings of the 8th extended semantic web conference on The semanic web: research and applications - Volume Part II
Year:
2011

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Abstract

To-date, the application of high-performance computing resources to Semantic Web data has largely focused on commodity hardware and distributed memory platforms. In this paper we make the case that more specialized hardware can offer superior scaling and close to an order of magnitude improvement in performance. In particular we examine the Cray XMT. Its key characteristics, a large, global sharedmemory, and processors with a memory-latency tolerant design, offer an environment conducive to programming for the Semantic Web and have engendered results that far surpass current state of the art. We examine three fundamental pieces requisite for a fully functioning semantic database: dictionary encoding, RDFS inference, and query processing. We show scaling up to 512 processors (the largest configuration we had available), and the ability to process 20 billion triples completely in-memory.