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Parallel Hashing-N-Gram-Hirschberg algorithm

机译:并行散列-N-GRAM-HIRSCHBERG算法

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摘要

Fast and efficient protein sequence alignment and comparison algorithms have become significance as the size of databases grow very rapidly. This paper introduces a parallel algorithm for Hashing-N-Gram-Hirschberg (HNGH) algorithm. The HNGH algorithm is an extension of N-Gram-Hirschberg (NGH) algorithm which was proposed by Abdul Rashid in 2007. The parallel algorithm is proposed to speed up the sequential HNGH when run on large database. Our parallel algorithm has two levels of parallelization, one on processors level and the other one on the cores level. By testing our previous work with different Gram lengths ranges from 3–6 letters, HNGH algorithm outperforms the former algorithm (NGH algorithm) in most cases. The parallel algorithm shows an enhancement in the execution time but the speed up is a bit low because of the high communication among processers and the high dependency among the tasks.
机译:快速高效的蛋白质序列对准和比较算法具有重要性,因为数据库的大小非常迅速增长。本文介绍了一种散列-N-GRAM-HIRSCHBERG(HNGH)算法的并行算法。 HNGH算法是N-GRAM-HIRSCHBERG(NGH)算法的扩展,该算法由ABDUL Rashid于2007年提出。建议并行算法在大型数据库上运行时加速顺序HNGH。我们的并行算法具有两个平行化级别,一个在处理器级别,另一个在核心水平上。通过测试我们以前的不同克长度的工作范围从3-6字母,HNGH算法在大多数情况下优于前算法(NGH算法)。并行算法显示了执行时间的增强,但由于处理器之间的高级别以及任务之间的高依赖性,因此加速度为一点。

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