RabbitKSSD: accelerating genome distance estimation on modern multi-core architectures

Xiaoming Xu,Zekun Yin, Lifeng Yan, Huiguang Yi,Hua Wang, Bertil Schmidt,Weiguo Liu

BIOINFORMATICS(2023)

引用 0|浏览4
暂无评分
摘要
We propose RabbitKSSD, a high-speed genome distance estimation tool. Specifically, we leverage load-balanced task partitioning, fast I/O, efficient intermediate result accesses, and high-performance data structures to improve overall efficiency. Our performance evaluation demonstrates that RabbitKSSD achieves speedups ranging from 5.7 x to 19.8 x over Kssd for the time-consuming sketch generation and distance computation on commonly used workstations. In addition, it significantly outperforms Mash, BinDash, and Dashing2. Moreover, RabbitKSSD can efficiently perform all-vs-all distance computation for all RefSeq complete bacterial genomes (455 GB in FASTA format) in just 2 min on a 64-core workstation.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要