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Pairwise Sequence Alignment Method for Distributed Shared Memory Systems

机译:分布式共享存储系统的成对序列比对方法

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One of the initial key steps of the multiple sequence alignment problem is the pairwise alignment of all pairs of genomic sequences involved. With the increased requirements to align several thousand sequences, it is necessary to find efficient new ways to align as many pairs of sequences as possible. Traditional sequential algorithms are limited by their memory and processing capabilities while parallel implementations running over clusters are able to process considerably more sequences. Nowadays, computer systems are capable of running several processing threads using a shared memory model, which allows us to combine it with distributed memory model. This paper presents a parallel pairwise aligner based on Smith-Waterman capable of processing large numbers of sequences with a small memory footprint. Our implementation is based on the use of a message-passing library such as MPI combined with a threading library, such as pthreads. Our experimentation shows the gain in efficiency for processing different numbers of sequences with different numbers of threads.
机译:多序列比对问题的初始关键步骤之一是所涉及的所有基因组序列对的成对比对。随着对对齐几千个序列的需求的增加,有必要找到有效的新方法来对尽可能多的序列对进行比对。传统的顺序算法受其内存和处理能力的限制,而在集群上运行的并行实现则能够处理更多的序列。如今,计算机系统能够使用共享内存模型运行多个处理线程,这使我们可以将其与分布式内存模型结合在一起。本文提出了一种基于Smith-Waterman的并行成对对齐器,它能够以较小的内存占用空间处理大量序列。我们的实现是基于将消息传递库(例如MPI)与线程库(例如pthreads)结合使用的。我们的实验表明,使用不同数量的线程处理不同数量的序列的效率有所提高。

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