全子串最长公共子序列问题的BSP/CGM算法

C. E. R. Alves, E. Cáceres, S. W. Song
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引用次数: 12

摘要

给定两个长度分别为m和n的字符串X和Y,所有子串最长公共子序列(ALCS)问题求出X和Y的任意子串的公共子序列的长度,顺序算法耗时O(mn),空间O(n)。我们提出了一种基于p < /spl径向/m处理器的粗粒度多计算机(BSP/CGM)模型的ALCS并行算法,该模型每个处理器占用O(mn/p)时间和O(n/spl径向/m)空间,通信轮数为O(log p)。提出的并行算法还解决了众所周知的LCS问题。据我们所知,这是文献中针对ALCS问题的最佳BSP/CGM算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A BSP/CGM algorithm for the all-substrings longest common subsequence problem
Given two strings X and Y of lengths m and n, respectively, the all-substrings longest common subsequence (ALCS) problem obtains the lengths of the subsequences common to X and any substring of Y. The sequential algorithm takes O(mn) time and O(n) space. We present a parallel algorithm for ALCS on a coarse-grained multicomputer (BSP/CGM) model with p < /spl radic/m processors that takes O(mn/p) time and O(n/spl radic/m) space per processor, with O(log p) communication rounds. The proposed parallel algorithm also solves the well-known LCS problem. To our knowledge this is the best BSP/CGM algorithm for the ALCS problem in the literature.
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