基因组大数据的多线程并发压缩算法

2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT) Pub Date : 2019-12-01 DOI:10.1109/PDCAT46702.2019.00093

Yimu Ji, Shuai Chen, Haichang Yao, Houzhi Fang, Kui Li, Shangdong Liu, Zhengyuan Xie, Kairui Wang

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引用次数: 2

摘要

目前，有许多优秀的基因组压缩算法都具有较高的基因组压缩比。然而，目前还缺乏能够同时压缩大量基因组的高效压缩算法。本文提出了一种基于多线程并发的海量基因组数据同时压缩算法FastLNGC。该算法以LNGC (Large Number of Genomes Compressor)算法为基础，采用多线程技术实现基因组数据压缩的并发处理。大量实验表明，FastLNGC在压缩大量基因方面具有较好的性能。FastLNGC的源代码可从https://github.com/APandaThief/FastLNGC获得。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Multi-Thread Concurrent Compression Algorithm for Genomic Big Data

At present, there are many excellent genome compression algorithms with high genome compression ratio. However, there is a lack of highly efficient compression algorithms for simultaneous compression of a large number of genomes. This manuscript presents an algorithm, which is called FastLNGC, for simultaneous compression of a large amount of genome data based on multi-thread concurrency. This algorithm is based on the LNGC (Large Number of Genomes Compressor) algorithm, and adopts multi-thread technology to achieve concurrent processing of genome data compression. A large number of experiments show that FastLNGC has better performance on compression of a large number of genes. The source code of FastLNGC is available at https://github.com/APandaThief/FastLNGC.

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2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)

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