About: NFA Reduction for Regular Expressions Matching Using FPGA     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • Many algorithms have been proposed to accelerate regular expression matching via mapping of a nondeterministic finite automaton into a circuit implemented in an FPGA. These algorithms exploit unique features of the FPGA to achieve high throughput. On the other hand the FPGA poses a limit on the number of regular expressions by its limited resources. In this paper, we investigate applicability of NFA reduction techniques - a formal aparatus to reduce the number of states and transitions in NFA prior to its mapping into FPGA. The paper presents several NFA reduction techniques, each with a different reduction power and time complexity. The evaluation utilizes regular expressions from Snort and L7 decoder. The best NFA reduction algorithms achieve more than 66% reduction in the number of states for a Snort ftp module. Such a reduction translates directly into 66% LUT and FF saving in the FPGA.
  • Many algorithms have been proposed to accelerate regular expression matching via mapping of a nondeterministic finite automaton into a circuit implemented in an FPGA. These algorithms exploit unique features of the FPGA to achieve high throughput. On the other hand the FPGA poses a limit on the number of regular expressions by its limited resources. In this paper, we investigate applicability of NFA reduction techniques - a formal aparatus to reduce the number of states and transitions in NFA prior to its mapping into FPGA. The paper presents several NFA reduction techniques, each with a different reduction power and time complexity. The evaluation utilizes regular expressions from Snort and L7 decoder. The best NFA reduction algorithms achieve more than 66% reduction in the number of states for a Snort ftp module. Such a reduction translates directly into 66% LUT and FF saving in the FPGA. (en)
Title
  • NFA Reduction for Regular Expressions Matching Using FPGA
  • NFA Reduction for Regular Expressions Matching Using FPGA (en)
skos:prefLabel
  • NFA Reduction for Regular Expressions Matching Using FPGA
  • NFA Reduction for Regular Expressions Matching Using FPGA (en)
skos:notation
  • RIV/00216305:26230/13:PU107071!RIV14-MSM-26230___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(ED1.1.00/02.0070), S, Z(MSM0021630528)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 91786
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26230/13:PU107071
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • FPGA, NFA, Reduction, Regular expressions matching (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [16775E5DBF8D]
http://linked.open...v/mistoKonaniAkce
  • Kyoto
http://linked.open...i/riv/mistoVydani
  • Kyoto
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 2013 International Conference on Field Programmable Technology
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Kořenek, Jan
  • Žádník, Martin
  • Košař, Vlastimil
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • IEEE Computer Society
https://schema.org/isbn
  • 978-1-4799-2199-7
http://localhost/t...ganizacniJednotka
  • 26230
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 77 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software