GPGPU DFA membership tests

Beorn Facchini, Yousun Ko, Min Young Jung, Bernd Burgstaller

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

Abstract

Pattern matching is often implemented on the CPU to-day using deterministic finite automata (DFAs). We present methods to efficiently parallelize the DFA membership test on general-purpose graphics processing units (GPGPUs). Our partitioning scheme builds on the work of Holub and Stekr [1]. Our implementations utilize the OpenCL programming model, in which we propose a series of algorithms and related memory size constraints. Experimental results are presented on the effectiveness of these algorithms, yielding GPU speedups between 19x and 39x over the Grep utility in matching PROSITE motifs [2].

Original languageEnglish
Title of host publicationProceedings of the IASTED International Conference on Parallel and Distributed Computing and Systems, PDCS 2011
Pages73-82
Number of pages10
DOIs
Publication statusPublished - 2011 Dec 1
EventIASTED International Conference on Parallel and Distributed Computing and Systems, PDCS 2011 - Dallas, TX, United States
Duration: 2011 Dec 142011 Dec 16

Publication series

NameProceedings of the IASTED International Conference on Parallel and Distributed Computing and Systems
ISSN (Print)1027-2658

Other

OtherIASTED International Conference on Parallel and Distributed Computing and Systems, PDCS 2011
CountryUnited States
CityDallas, TX
Period11/12/1411/12/16

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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  • Cite this

    Facchini, B., Ko, Y., Jung, M. Y., & Burgstaller, B. (2011). GPGPU DFA membership tests. In Proceedings of the IASTED International Conference on Parallel and Distributed Computing and Systems, PDCS 2011 (pp. 73-82). (Proceedings of the IASTED International Conference on Parallel and Distributed Computing and Systems). https://doi.org/10.2316/P.2011.757-014