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Local DNA sequence alignment in a cluster of workstations : algorithms and tools

机译:工作站集群中的DNa序列比对:算法和工具

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摘要

Distributed Shared Memory systems allow the use of the shared memory programming paradigm in distributed architectures where no physically shared memory exist. Scope consistent software DSMs provide a relaxed memory model that reduces the coherence overhead by ensuring consistency only at synchronization operations, on a per-lock basis. Much of the work in DSM systems is validated by benchmarks and there are only a few examples of real parallel applications running on DSM systems. Sequence comparison is a basic operation in DNA sequencing projects, and most of sequence comparison methods used are based on heuristics, that are faster but do not produce optimal alignments. Recently, many organisms had their DNA entirely sequenced, and this reality presents the need for comparing long DNA sequences, which is a challenging task due to its high demands for computational power and memory. In this article, we present and evaluate a parallelization strategy for implementing a sequence alignment algorithm for long sequences. This strategy was implemented in JIAJIA, a scope consistent software DSM system. Our results on an eight-machine cluster presented good speedups, showing that our parallelization strategy and programming support were appropriate.
机译:分布式共享内存系统允许在不存在物理共享内存的分布式体系结构中使用共享内存编程范例。范围一致的软件DSM提供了宽松的内存模型,通过确保仅在每个锁的同步操作中保持一致性,从而减少了一致性开销。 DSM系统中的许多工作均已通过基准测试验证,并且只有少数几个在DSM系统上运行的实际并行应用程序示例。序列比较是DNA测序项目中的基本操作,并且大多数使用的序列比较方法都是基于试探法,这些方法比较快,但不会产生最佳比对。最近,许多生物体的DNA都已完全测序,这一现实提出了比较长DNA序列的需求,由于其对计算能力和存储的高度需求,这是一项艰巨的任务。在本文中,我们介绍并评估了一种用于实现长序列的序列比对算法的并行化策略。此策略是在范围一致的软件DSM系统JIAJIA中实现的。我们在八台计算机集群上的结果显示出良好的加速效果,表明我们的并行化策略和编程支持是适当的。

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