An Algorithm for Fast Edit Distance Computation on GPUs

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Provided by: University of Illinois at Urbana Champaign
Topic: Storage
Format: PDF
The problem of finding the edit distance between two sequences are important problems with applications in many domains like virus scanners, security kernels, natural language translation and genome sequence alignment. The traditional dynamic-programming based algorithm is hard to parallelize on SIMD processors as the algorithm is memory intensive and has many divergent control paths. In this paper, the authors introduce a new algorithm which modifies the dynamic programming method to reduce its amount of data storage and eliminate control flow divergences.
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