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Parallelisation of sequence comparison algorithms using hybridised parallel techniques

机译:使用混合并行技术对序列比较算法进行并行化

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The aim of this work is how to speed up the process of the biological (DNA and proteins) sequence comparison process by using a hybrid parallelisation technique of combining different parallel methods. Smith-Waterman algorithm has been known as the most optimal algorithm for doing the sequence comparison. Unfortunately, this algorithm is considered slow due to its quadratic time complexity. Multiple Instruction Multiple Data (MIMD), Single Instruction Multiple Data (SIMD), and Single Program Multiple Data (SPMD) methods were chosen because of their efficiency, wide-availability in off-the-shelf inexpensive machines and simple network distributed systems. Based on the results, the combined (hybrid) algorithm has succeeded in reducing the overall algorithm execution time.
机译:这项工作的目的是如何通过结合使用不同并行方法的混合并行化技术来加快生物(DNA和蛋白质)序列比较过程的过程。 Smith-Waterman算法已被公认为是进行序列比较的最佳算法。不幸的是,由于其二次时间复杂度,该算法被认为是慢速的。选择多指令多数据(MIMD),单指令多数据(SIMD)和单程序多数据(SPMD)方法是因为它们的效率高,在现成的廉价机器中具有广泛的可用性以及简单的网络分布式系统。根据结果​​,组合(混合)算法已成功减少了整个算法的执行时间。

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