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引用次数: 5
摘要
BLAST (Basic Local Alignment Search)是使用最广泛的生物信息学程序之一,它使用序列比对技术在所有可用的序列数据库中搜索蛋白质或DNA查询与预定义序列之间的相似性。最近,许多人尝试使该算法在大型并行集群上与公开可用的基因组数据库运行。本文介绍了我们在大型基于infiniband的无磁盘高性能集群(HPC)上评估串行和并行BLAST算法的经验,与传统的全磁盘集群相比,该集群提供了更低的硬件成本和更高的可靠性。本文还给出了评估方法和实验结果,以说明BLAST算法在我们的高性能计算系统上的可扩展性。对于我们的测量和比较,我们考虑集群大小为32个计算节点。我们的结果表明,使用无磁盘集群仍然可以保留BLAST运行时,同时提高运行时可靠性。
Evaluating BLAST Runtime Using NAS-Based High Performance Clusters
The Basic Local Alignment Search (BLAST) is one of the most widely used bioinformatics programs for searching all available sequence databases for similarities between a protein or DNA query and predefined sequences, using sequence alignment technique. Recently, many attempts have been made to make the algorithm practical to run against the publicly available genome databases on large parallel clusters. This paper presents our experience in evaluating both the serial and parallel BLAST algorithms onto a large Infiniband-based diskless High Performance Cluster (HPC) that offers lower hardware cost and improved reliability, as opposed to traditional disk full clusters. The paper also presents the evaluation methodology along with the experimental results to illustrate the scalability of the BLAST algorithm on our HPC system. For our measurement and comparison, we considered cluster sizes up to 32 compute nodes. Our results show that BLAST runtime can still be retained with the use of the diskless clusters, while improving the runtime reliability.