修边
计算机科学
适配器(计算)
现场可编程门阵列
管道(软件)
管道运输
并行计算
嵌入式系统
计算机硬件
操作系统
工程类
环境工程
作者
Behnam Khaleghi,Tianqi Zhang,Niya Shao,Ameen Akel,Ken Curewitz,Justin Eno,Sean Eilert,Niema Moshiri,Tajana Rosing
标识
DOI:10.1109/biocas54905.2022.9948621
摘要
The sheer amount of genomic sequencing data generated daily that requires time-sensitive processing for downstream analysis calls for accelerating the bioinformatics pipelines. Previous studies mainly have attempted accelerating the alignment stage, leaving the other pipeline stages as performance bottlenecks. In this work, we propose the first FPGA-based framework dubbed FAST to accelerate the stages that deal with sequence trimming, in particular adapter and primer removal. FAST supports a comprehensive set of functionalities and is convenient to use by operating on standard genomics data formats. The proposed framework is fully configurable and supports variety of runtime settings. It surpasses the state-of-the-art widely-used adapter trimmer (fastp) by 4.7×–29.4× speed-up, with 10.1×–54.9 less energy, respectively. For clipping primers, which with current existing tool (iVar) accounts for ∼50% of SARS-CoV-2 analysis pipeline, FAST achieves up to 62× speed-up in trimming the virus sequences with a low FPGA resource utilization of 12%.
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