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基于硬件加速器的蛋白质-蛋白质对接:GPU与MIC架构的比较

Protein-protein docking on hardware accelerators: comparison of GPU and MIC architectures.

作者信息

Shimoda Takehiro, Suzuki Shuji, Ohue Masahito, Ishida Takashi, Akiyama Yutaka

出版信息

BMC Syst Biol. 2015;9 Suppl 1(Suppl 1):S6. doi: 10.1186/1752-0509-9-S1-S6. Epub 2015 Jan 21.

Abstract

BACKGROUND

The hardware accelerators will provide solutions to computationally complex problems in bioinformatics fields. However, the effect of acceleration depends on the nature of the application, thus selection of an appropriate accelerator requires some consideration.

RESULTS

In the present study, we compared the effects of acceleration using graphics processing unit (GPU) and many integrated core (MIC) on the speed of fast Fourier transform (FFT)-based protein-protein docking calculation. The GPU implementation performed the protein-protein docking calculations approximately five times faster than the MIC offload mode implementation. The MIC native mode implementation has the advantage in the implementation costs. However, the performance was worse with larger protein pairs because of memory limitations.

CONCLUSION

The results suggest that GPU is more suitable than MIC for accelerating FFT-based protein-protein docking applications.

摘要

背景

硬件加速器将为生物信息学领域中计算复杂的问题提供解决方案。然而,加速效果取决于应用的性质,因此选择合适的加速器需要一些考量。

结果

在本研究中,我们比较了使用图形处理单元(GPU)和众核处理器(MIC)加速基于快速傅里叶变换(FFT)的蛋白质-蛋白质对接计算速度的效果。GPU实现方式进行蛋白质-蛋白质对接计算的速度比MIC卸载模式实现方式快约五倍。MIC原生模式实现在实现成本方面具有优势。然而,由于内存限制,对于较大的蛋白质对,其性能较差。

结论

结果表明,在加速基于FFT的蛋白质-蛋白质对接应用方面,GPU比MIC更合适。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/db70/4331681/a27e2133d2ad/1752-0509-9-S1-S6-1.jpg

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