Suppr超能文献

一种混合短读映射加速器。

A hybrid short read mapping accelerator.

机构信息

School of Computer Engineering, Nanyang Technological University, Singapore, Singapore.

出版信息

BMC Bioinformatics. 2013 Feb 26;14:67. doi: 10.1186/1471-2105-14-67.

Abstract

BACKGROUND

The rapid growth of short read datasets poses a new challenge to the short read mapping problem in terms of sensitivity and execution speed. Existing methods often use a restrictive error model for computing the alignments to improve speed, whereas more flexible error models are generally too slow for large-scale applications. A number of short read mapping software tools have been proposed. However, designs based on hardware are relatively rare. Field programmable gate arrays (FPGAs) have been successfully used in a number of specific application areas, such as the DSP and communications domains due to their outstanding parallel data processing capabilities, making them a competitive platform to solve problems that are "inherently parallel".

RESULTS

We present a hybrid system for short read mapping utilizing both FPGA-based hardware and CPU-based software. The computation intensive alignment and the seed generation operations are mapped onto an FPGA. We present a computationally efficient, parallel block-wise alignment structure (Align Core) to approximate the conventional dynamic programming algorithm. The performance is compared to the multi-threaded CPU-based GASSST and BWA software implementations. For single-end alignment, our hybrid system achieves faster processing speed than GASSST (with a similar sensitivity) and BWA (with a higher sensitivity); for pair-end alignment, our design achieves a slightly worse sensitivity than that of BWA but has a higher processing speed.

CONCLUSIONS

This paper shows that our hybrid system can effectively accelerate the mapping of short reads to a reference genome based on the seed-and-extend approach. The performance comparison to the GASSST and BWA software implementations under different conditions shows that our hybrid design achieves a high degree of sensitivity and requires less overall execution time with only modest FPGA resource utilization. Our hybrid system design also shows that the performance bottleneck for the short read mapping problem can be changed from the alignment stage to the seed generation stage, which provides an additional requirement for the future development of short read aligners.

摘要

背景

短读数据集的快速增长给短读映射问题在灵敏度和执行速度方面带来了新的挑战。现有的方法通常使用限制错误模型来计算比对以提高速度,而更灵活的错误模型对于大规模应用通常太慢。已经提出了许多短读映射软件工具。然而,基于硬件的设计相对较少。由于其出色的并行数据处理能力,现场可编程门阵列(FPGA)已成功应用于许多特定应用领域,如 DSP 和通信领域,使其成为解决“固有并行”问题的具有竞争力的平台。

结果

我们提出了一种利用基于 FPGA 的硬件和基于 CPU 的软件的混合系统进行短读映射。计算密集型比对和种子生成操作被映射到 FPGA 上。我们提出了一种计算效率高的、并行的块式比对结构(Align Core)来近似传统的动态规划算法。性能与基于多线程的 CPU 的 GASSST 和 BWA 软件实现进行了比较。对于单端比对,我们的混合系统比 GASSST(具有相似的灵敏度)和 BWA(具有更高的灵敏度)更快的处理速度;对于对端比对,我们的设计比 BWA 的灵敏度略差,但处理速度更高。

结论

本文表明,我们的混合系统可以有效地加速基于种子和扩展方法的短读向参考基因组的映射。在不同条件下与 GASSST 和 BWA 软件实现的性能比较表明,我们的混合设计在适度利用 FPGA 资源的情况下,达到了很高的灵敏度,并且需要更少的总执行时间。我们的混合系统设计还表明,短读映射问题的性能瓶颈可以从比对阶段转移到种子生成阶段,这为短读比对器的未来发展提供了额外的要求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/206c/3598928/7971f03e448d/1471-2105-14-67-1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验