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首页> 外文期刊>Journal of computational biology: A journal of computational molecular cell biology >Massively Parallel Implementation of Sequence Alignment with Basic Local Alignment Search Tool Using Parallel Computing in Java Library
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Massively Parallel Implementation of Sequence Alignment with Basic Local Alignment Search Tool Using Parallel Computing in Java Library

机译：使用并行计算在Java库中使用并行计算的大规模并行实现与基本局部对齐搜索工具

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Basic Local Alignment Search Tool (BLAST) is an essential algorithm that researchers use for sequence alignment analysis. The National Center for Biotechnology Information (NCBI)-BLAST application is the most popular implementation of the BLAST algorithm. It can run on a single multithreading node. However, the volume of nucleotide and protein data is fast growing, making single node insufficient. It is more and more important to develop high-performance computing solutions, which could help researchers to analyze genetic data in a fast and scalable way. This article presents execution of the BLAST algorithm on high performance computing (HPC) clusters and supercomputers in a massively parallel manner using thousands of processors. The Parallel Computing in Java (PCJ) library has been used to implement the optimal splitting up of the input queries, the work distribution, and search management. It is used with the nonmodified NCBI-BLAST package, which is an additional advantage for the users. The result applicationPCJ-BLASTis responsible for reading sequence for comparison, splitting it up and starting multiple NCBI-BLAST executables. Since I/O performance could limit sequence analysis performance, the article contains an investigation of this problem. The obtained results show that using Java and PCJ library it is possible to perform sequence analysis using hundreds of nodes in parallel. We have achieved excellent performance and efficiency and we have significantly reduced the time required for sequence analysis. Our work also proved that PCJ library could be used as an effective tool for fast development of the scalable applications.
机译：基本的本地对齐搜索工具（BLAST）是一种研究人员用于序列对准分析的基本算法。国家生物技术信息中心（NCBI）-Blast应用程序是BLAST算法最受欢迎的实现。它可以在单个多线程节点上运行。然而，核苷酸和蛋白质数据的体积快速增长，使单节点不足。开发高性能计算解决方案越来越重要，这可以帮助研究人员以快速和可扩展的方式分析遗传数据。本文以一种使用数千个处理器的大规模并行方式呈现高性能计算（HPC）集群和超级计算机上的BLAST算法的执行。 Java（PCJ）库中的并行计算已用于实现输入查询，工作分发和搜索管理的最佳分割。它与非零化的NCBI-BLAST包一起使用，这对于用户来说是一种额外的优势。结果ApplicationPC-Blastis负责阅读序列以进行比较，将其拆分并启动多个NCBI-Blast可执行文件。由于I / O性能可能会限制序列分析性能，因此该文章包含对此问题的调查。所获得的结果表明，使用Java和PCJ库可以并行使用数百个节点进行序列分析。我们取得了良好的性能和效率，我们显着降低了序列分析所需的时间。我们的工作还证明了PCJ库可作为快速开发可扩展应用的有效工具。

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