Trie compression for GPU accelerated multi-pattern matching

Xavier Bellekens, Amar Seeam, Christos Tachtatzis, Robert Atkinson

Research output: Contribution to conferencePaperpeer-review

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Graphics Processing Units allow for running massively parallel applications offloading the CPU from computationally intensive resources, however GPUs have a limited amount of memory. In this paper a trie compression algorithm for massively parallel pattern matching is presented demonstrating 85% less space requirements than the original highly efficient parallel failure-less aho-corasick, whilst demonstrating over 22 Gbps throughput. The algorithm presented takes advantage of compressed row storage matrices as well as shared and texture memory on the GPU.
Original languageEnglish
Publication statusPublished - 19 Feb 2017
EventInternational Conferences on Pervasive Patterns and Applications - Athens, Greece
Duration: 19 Feb 201723 Feb 2017
Conference number: 9


ConferenceInternational Conferences on Pervasive Patterns and Applications
Abbreviated titlePATTERNS
Internet address


  • pattern matching algorithm
  • trie compression
  • searching
  • data compression
  • GPU
  • graphics processing units


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