一维和二维的最优快速并行预处理和模式匹配算法

R. Cole, M. Crochemore, Z. Galil, L. Gąsieniec, R. Hariharan, S. Muthukrishnan, Kunsoo Park, W. Rytter
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引用次数: 59

摘要

下面所有算法都是最优的与字母无关的并行CRCW PRAM算法。在一个维度上:给定一个长度为m的模式字符串用于字符串匹配问题,我们设计了一个算法,该算法在常数时间内计算一个足够长的子字符串的确定性样本。这一问题一直是一维和二维模式匹配的模式预处理瓶颈。之前的最佳时间范围为O(log/sup 2/ m/log log m)。我们使用该算法得到如下结果:1. 将恒时文本搜索算法的预处理从O(log/sup 2/ m/log log m)改进到n(log log m),这是目前最好的可能。2. 对于常数/spl epsiv/>0,文本长度n满足n=/spl Omega/(m/sup 1+/spl epsiv//)的情况下的恒定时间确定性字符串匹配算法。3.一个简单的概率字符串匹配算法,具有恒定的时间和高概率随机输入。4. 一种常数期望时间的Las-Vegas算法,用于计算模式和所有证人的周期,从而解决字符串匹配中遗留的主要开放问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimally fast parallel algorithms for preprocessing and pattern matching in one and two dimensions
All algorithms below are optimal alphabet-independent parallel CRCW PRAM algorithms. In one dimension: Given a pattern string of length m for the string-matching problem, we design an algorithm that computes a deterministic sample of a sufficiently long substring in constant time. This problem used to be a bottleneck in the pattern preprocessing for one- and two-dimensional pattern matching. The best previous time bound was O(log/sup 2/ m/log log m). We use this algorithm to obtain the following results. 1. Improving the preprocessing of the constant-time text search algorithm from O(log/sup 2/ m/log log m) to n(log log m), which is now best possible. 2. A constant-time deterministic string-matching algorithm in the case that the text length n satisfies n=/spl Omega/(m/sup 1+/spl epsiv//) for a constant /spl epsiv/>0. 3. A simple probabilistic string-matching algorithm that has constant time with high probability for random input. 4. A constant expected time Las-Vegas algorithm for computing the period of the pattern and all witnesses and thus string matching itself, solving the main open problem remaining in string matching.<>
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