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Local Alignment Tool Based on Hadoop Framework and GPU Architecture

机译:基于Hadoop框架和GPU架构的本地对齐工具

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With the rapid growth of next generation sequencing technologies, such as Slex, more and more data have been discovered and published. To analyze such huge data the computational performance is an important issue. Recently, many tools, such as SOAP, have been implemented on Hadoop and GPU parallel computing architectures. BLASTP is an important tool, implemented on GPU architectures, for biologists to compare protein sequences. To deal with the big biology data, it is hard to rely on single GPU. Therefore, we implement a distributed BLASTP by combining Hadoop and multi-GPUs. The experimental results present that the proposed method can improve the performance of BLASTP on single GPU, and also it can achieve high availability and fault tolerance.
机译:随着诸如Slex之类的下一代测序技术的迅猛发展,越来越多的数据被发现和发布。为了分析如此巨大的数据,计算性能是一个重要的问题。最近,许多工具(例如SOAP)已在Hadoop和GPU并行计算架构上实现。 BLASTP是在GPU架构上实施的重要工具,生物学家可以比较蛋白质序列。要处理大的生物学数据,很难依靠单个GPU。因此,我们通过结合Hadoop和多GPU来实现分布式BLASTP。实验结果表明,该方法可以提高单GPU上的BLASTP性能,并且可以实现高可用性和容错能力。

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