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Parallel GPU-Based Hybrid String Matching Algorithm

机译:基于并行GPU的混合字符串匹配算法

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String or pattern matching is an essential part of most computer applications that are widely used in text processors, Internet-based search engines and computer security. A key concept of string matching is identifying the existence of a pattern with m characters in a much longer text string. String matching operations are basic to many algorithms such as indexing algorithms, search algorithms and bioinformatics algorithms that are used in molecular biology, adopted pattern matching concept in their programming structure. Although the mathematical and algorithmic calculations of pattern matching algorithms are simple, they are still the main reason of a large ratio of the computational load in many applications This research proposes to parallelize a hybrid string matching algorithm called Maximum-Shift algorithm, by using CUDA device (GPU) to increase its speed up during the matching process. The parallel Maximum-Shift algorithm shows slight improvement over the sequential version in terms of running time, speed up rate and percentage of performance gain.
机译:字符串或模式匹配是在文本处理器,基于Internet的搜索引擎和计算机安全性中广泛使用的大多数计算机应用程序的重要组成部分。字符串匹配的一个关键概念是,在更长的文本字符串中识别出m个字符的模式是否存在。字符串匹配操作是许多算法的基础,例如分子生物学中使用的索引算法,搜索算法和生物信息学算法,并且在程序结构中采用了模式匹配概念。尽管模式匹配算法的数学和算法计算很简单,但它们仍然是许多应用中计算负载比例很大的主要原因。本研究提出通过使用CUDA设备并行化称为最大移位算法的混合字符串匹配算法。 (GPU),以提高其在匹配过程中的速度。并行的Maximum-Shift算法在运行时间,加速速率和性能增益百分比方面比顺序版本略有改善。

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