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BarraCUDA——一种使用图形处理单元的快速短读序列比对工具。

BarraCUDA - a fast short read sequence aligner using graphics processing units.

作者信息

Klus Petr, Lam Simon, Lyberg Dag, Cheung Ming Sin, Pullan Graham, McFarlane Ian, Yeo Giles Sh, Lam Brian Yh

机构信息

University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Hill's Road, Cambridge CB2 0QQ, UK.

出版信息

BMC Res Notes. 2012 Jan 13;5:27. doi: 10.1186/1756-0500-5-27.

DOI:10.1186/1756-0500-5-27
PMID:22244497
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3278344/
Abstract

BACKGROUND

With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence.

FINDINGS

Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput.

CONCLUSIONS

BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.BarraCUDA is currently available from http://seqbarracuda.sf.net.

摘要

背景

随着下一代DNA测序(NGS)技术的成熟,单次仪器运行产生的DNA测序读数通量已飙升至超过600千兆碱基。图形处理器通用计算(GPGPU)从图形处理核心内的数百个并行流处理器中提取计算能力,为传统高性能计算(HPC)集群提供了一种经济高效的替代方案。在本文中,我们描述了BarraCUDA的实现,这是一种基于BWA的GPGPU序列比对软件,用于加速这些仪器产生的测序读数与参考DNA序列的比对。

研究结果

使用NVIDIA计算统一设备架构(CUDA)软件开发环境,我们将BWA中计算量最大的比对组件移植到GPU上,以利用其大规模并行性。结果,与CPU核心相比,BarraCUDA在比对通量方面提供了数量级的性能提升,同时保持相同水平的比对保真度。该软件还能够并行支持多个CUDA设备,以进一步加速比对通量。

结论

BarraCUDA旨在利用GPU的并行性来加速NGS仪器产生的数百万测序读数的比对。通过这样做,我们至少可以部分简化当前的生物信息学流程,以便更广泛的科学界能够从测序技术中受益。BarraCUDA目前可从http://seqbarracuda.sf.net获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67a6/3278344/5cc35414a64d/1756-0500-5-27-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67a6/3278344/68e4bf885ba6/1756-0500-5-27-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67a6/3278344/8fd9cf1cba41/1756-0500-5-27-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67a6/3278344/faedbab6d5c3/1756-0500-5-27-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67a6/3278344/5cc35414a64d/1756-0500-5-27-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67a6/3278344/68e4bf885ba6/1756-0500-5-27-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67a6/3278344/8fd9cf1cba41/1756-0500-5-27-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67a6/3278344/faedbab6d5c3/1756-0500-5-27-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67a6/3278344/5cc35414a64d/1756-0500-5-27-4.jpg

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