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.
|Publication status||Published - 19 Feb 2017|
|Event||International Conferences on Pervasive Patterns and Applications - Athens, Greece|
Duration: 19 Feb 2017 → 23 Feb 2017
Conference number: 9
|Conference||International Conferences on Pervasive Patterns and Applications|
|Period||19/02/17 → 23/02/17|
- pattern matching algorithm
- trie compression
- data compression
- graphics processing units
Bellekens, X., Seeam, A., Tachtatzis, C., & Atkinson, R. (2017). Trie compression for GPU accelerated multi-pattern matching. Paper presented at International Conferences on Pervasive Patterns and Applications, Athens, Greece.