Trie Compression for GPU Accelerated Multi-Pattern Matching

Xavier Bellekens, Amar Seeam, Christos Tachtatzis, Robert Atkinson
Division of Computing and Mathematics, Abertay University, Dundee, Scotland
arXiv:1702.03657 [cs.DS], (13 Feb 2017)


   title={Trie Compression for GPU Accelerated Multi-Pattern Matching},

   author={Bellekens, Xavier and Seeam, Amar and Tachtatzis, Christos and Atkinson, Robert},






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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.
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