Fast parallel algorithms for the longest common subsequence problem using an optical bus

Abstract

A parallel algorithm for the longest common subsequence problem on LARPBS is presented. For two sequences of lengths m and n, the algorithm uses p processors and costs O(mn/p) computation time where 1 ≤ p ≤ max{m, n}. Time-area cost of the algorithm is O(mn/p) and memory space required is O((m+n)/p) which all reach optimal. We also show this algorithm is scalable when the number of processors p satisfies 1 ≤ p ≤ max{m, n}. To the best of our knowledge this is the fastest and cost-optimal parallel algorithm for LCS problem on array architectures. © Springer-Verlag Berlin Heidelberg 2005.