Parallel Implementation of Fuzzified Pattern Matching Algorithm on GPU

Abstract

Approximate pattern discovery is one of the fundamental and challenging problems in computer science. Fast and high performance algorithms are highly demanded in many applications in bioinformatics and computational molecular biology, which are the domains that are mostly and directly benefit from any enhancement of pattern matching theoretical knowledge and solutions. This paper proposed an efficient GPU implementation of fuzzified Aho-Corasick algorithm using Levenshtein method and N-gram technique as a solution for approximate pattern matching problem.