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.
Supported in part by the National Natural Science Foundation under grant No. 60473012, Science Foundation of Educational Commission Jiangsu Province.
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Xu, X., Chen, L., Pan, Y., He, P. (2005). Fast Parallel Algorithms for the Longest Common Subsequence Problem Using an Optical Bus. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2005. ICCSA 2005. Lecture Notes in Computer Science, vol 3482. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424857_37
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DOI: https://doi.org/10.1007/11424857_37
Publisher Name: Springer, Berlin, Heidelberg
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