gpu准备好促进基因组比对计算了吗

Fuhank Buntara, Bu-Sung Lee, Rikky W. Purbojati, Chan Xian Zhou
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引用次数: 1

摘要

本文介绍了下一代测序(NGS)序列比对中CPU和GPU性能的比较研究,特别是在短读段映射到参考基因组的背景下。本研究选择仅在CPU上运行的Bowtie2和BWA,以及同时在CPU和GPU上运行的NvBowtie和BarraCUDA作为基因组工具基准。我们选择的cpu是Intel Xeon Processor E5-2695v2(x2)和Intel Xeon Processor E5-2699 v4(x2)。我们选择的gpu是NVIDIA Tesla K80, Pascal 100 (P100)和Volta 100 (V100)。我们的研究结果表明,gpu在长读长度和大读次数方面的性能优于cpu。然而,考虑到性价比,结果表明新一代NVIDIA GPU的回报递减。
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Is GPUs Ready to Boost Genomic Alignment Computation
This paper presents a comparative study of CPU and GPU performance in sequence alignments for the Next Generation Sequencing (NGS), specifically in the context of short reads mapping to a reference genome. Bowtie2 and BWA which runs on CPU only and its equivalent, NvBowtie and BarraCUDA which runs on both CPU and GPU, is chosen as the genomic tools benchmark for this studies. The CPUs selected for our study is Intel Xeon Processor E5-2695v2(x2) and Intel Xeon Processor E5-2699 v4(x2). The GPUs that we have selected for our study are the NVIDIA Tesla K80, Pascal 100 (P100) and Volta 100 (V100). Our results show that GPUs performs better than CPUs for long read’s length and large number of reads. However, taking the price/performance ratio into account, the results suggests a case of diminishing return for the newer generation of NVIDIA GPU.
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