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Two-Hit Filter Synthesis for Genomic Database Search

机译:基因组数据库搜索的两命题过滤器综合

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摘要

Advancements in genomic sequencing technology is causing genomic database growth to outpace Moore's Law. This continues to make genomic database search a difficult problem and a popular target for emerging processing technologies. The de facto software tool for genomic database search is NCBI BLAST, which operates by transforming each database query into a filter that is subsequently applied to the database. This requires a database scan for every query, fundamentally limiting its performance by I/O bandwidth. In this paper we present a functionally-equivalent variation on the NCBI BLAST algorithm that maps more suitably to an FPGA implementation. This variation of the algorithm attempts to reduce the I/O requirement by leveraging FPGA-specific capabilities, such as high pattern matching throughput and explicit on chip memory structure and allocation. Our algorithm transforms the database -- not the query -- into a filter that is stored as a hierarchical arrangement of three tables, the first two of which are stored on chip and the third off chip. Our results show that -- while performance is data dependent -- it is possible to achieve speedups of up to 8X based on the relative reduction in I/O of our approach versus that of NCBI BLAST. More importantly, the performance relative to NCBI BLAST improves with larger databases and query workload sizes.
机译:基因组测序技术的进步导致基因组数据库的增长超过了摩尔定律。这继续使基因组数据库搜索成为难题,并且成为新兴处理技术的普遍目标。用于基因组数据库搜索的事实上的软件工具是NCBI BLAST,它通过将每个数据库查询转换为一个过滤器进行操作,然后将该过滤器应用于数据库。这需要对每个查询进行数据库扫描,从根本上限制了I / O带宽的性能。在本文中,我们介绍了NCBI BLAST算法的功能等效版本,该版本更适合映射至FPGA实现。该算法的这种变化试图通过利用FPGA特定的功能(例如高模式匹配吞吐量以及显式的片上存储器结构和分配)来减少I / O需求。我们的算法将数据库(而不是查询)转换为过滤器,该过滤器按三个表的层次结构存储,其中前两个存储在芯片上,第三个不在芯片上。我们的结果表明,尽管性能取决于数据,但基于我们的方法与NCBI BLAST相比,I / O的相对减少,可以使速度提高多达8倍。更重要的是,相对于NCBI BLAST而言,性能随着较大的数据库和更大的查询工作负载而得以提高。

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