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G-MSA - A GPU-based, fast and accurate algorithm for multiple sequence alignment

机译:G-MSA-基于GPU的快速准确的多序列比对算法

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Multiple sequence alignment (MSA) methods are essential in biological analysis. Several MSA algorithms have been proposed in recent years. The quality of the results produced by those methods is reasonable, but there is no single method that consistently outperforms others. Additionally, the increasing number of sequences in the biological databases is perceived as one of the upcoming challenges for alignment methods in the nearest future. The lack of performance concerns not only the alignment problems, but may be observed in many areas of biologically related research. To overcome this problem in the field of pairwise alignment, several GPU (Graphics Processing Unit) computing approaches have been proposed lately. These solutions show a great potential of GPU platform. Therefore, our main idea was to design and implement an MSA method which can take advantage of modern graphics cards. Our solution is based on T-Coffee - well known for its high accuracy MSA algorithm. Its computational time, however, is often unacceptable. Performed tests show that our method, named G-MSA, is highly efficient achieving up to 193-fold speedup on a single GPU while the quality of its results remains very good. Due to effective memory usage the method can perform alignment for huge sets of sequences that previously could only be aligned on computer clusters. Moreover, multiple CPUs support with load balancing makes the application very scalable.
机译:多重序列比对(MSA)方法在生物学分析中至关重要。近年来已经提出了几种MSA算法。这些方法产生的结果质量是合理的,但是没有一个方法能够始终胜过其他方法。另外,生物学数据库中越来越多的序列被认为是在不久的将来比对方法所面临的挑战之一。性能的缺乏不仅涉及对准问题,而且在生物学相关研究的许多领域中可能会观察到。为了克服成对对准领域中的这个问题,最近已经提出了几种GPU(图形处理单元)计算方法。这些解决方案显示了GPU平台的巨大潜力。因此,我们的主要思想是设计和实现一种可以利用现代图形卡的MSA方法。我们的解决方案基于T-Coffee-以其高精度MSA算法而闻名。但是,其计算时间通常是不可接受的。进行的测试表明,我们的名为G-MSA的方法在单个GPU上的效率高达193倍,效率很高,而结果的质量仍然非常好。由于有效的内存使用,该方法可以对以前只能在计算机群集上进行对齐的大量序列进行对齐。此外,负载均衡支持多个CPU,使应用程序具有很高的可扩展性。

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