Massively Parallel Reasoning under the Well-Founded Semantics Using X10

Ilias Tachmazidis, Long Cheng, Spyros Kotoulas, Grigoris Antoniou, Tomas E. Ward

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Academia and industry are investigating novel approaches for processing vast amounts of data coming from enterprises, the Web, social media and sensor readings in an area that has come to be known as Big Data. Logic programming has traditionally focused on complex knowledge structures/programs. The question arises whether and how it can be applied in the context of Big Data. In this paper, we study how the well-founded semantics can be computed over huge amounts of data using mass parallelization. Specifically, we propose and evaluate a parallel approach based on the X10 programming language. Our experiments demonstrate that our approach has the ability to process up to 1 billion facts within minutes.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE 26th International Conference on Tools with Artificial Intelligence, ICTAI 2014
PublisherIEEE Computer Society
Pages162-169
Number of pages8
Volume2014-December
ISBN (Electronic)9781479965724
DOIs
Publication statusPublished - 12 Dec 2014
Event26th IEEE International Conference on Tools with Artificial Intelligence - Limassol, Cyprus
Duration: 10 Nov 201412 Nov 2014
Conference number: 26

Conference

Conference26th IEEE International Conference on Tools with Artificial Intelligence
Abbreviated titleICTAI 2014
CountryCyprus
CityLimassol
Period10/11/1412/11/14

Fingerprint Dive into the research topics of 'Massively Parallel Reasoning under the Well-Founded Semantics Using X10'. Together they form a unique fingerprint.

  • Cite this

    Tachmazidis, I., Cheng, L., Kotoulas, S., Antoniou, G., & Ward, T. E. (2014). Massively Parallel Reasoning under the Well-Founded Semantics Using X10. In Proceedings - 2014 IEEE 26th International Conference on Tools with Artificial Intelligence, ICTAI 2014 (Vol. 2014-December, pp. 162-169). [6984469] IEEE Computer Society. https://doi.org/10.1109/ICTAI.2014.33