.png){kind=icon}
返回
Hardware Accelerated Alignment Algorithm for Optical Labeled Genomes
.png){kind=icon}
OA
AI
DOI：10.1145/2840811.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
De novo assembly is a widely used methodology in bioinformatics. However, the conventional short-read-based de novo assembly is incapable of reliably reconstructing the large-scale structures of human genomes. Recently, a novel optical label-based technology has enabled reliable large-scale de novo assembly. Despite its advantage in large-scale genome analysis, this new technology requires a more computationally intensive alignment algorithm than its conventional counterpart. For example, the runtime of reconstructing a human genome is on the order of 10,000 hours on a sequential CPU. Therefore, in order to practically apply this new technology in genome research, accelerated approaches are desirable. In this article, we present three different accelerated approaches, multicore CPU, GPU, and FPGA. Against the sequential software baseline, our multicore CPU design achieved an 8.4x speedup, while the GPU and FPGA designs achieved 13.6x and 115x speedups, respectively. We also discuss the details of the design space exploration of this new assembly algorithm on these three different devices. Finally, we compare these devices in performance, optimization techniques, prices, and design efforts.
Keyword:
Design
Performance
Experimentation
Genome
acceleration
de novo assembly
GPU
FPGA
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
2.8
论文数:
597
被引数:
810
机构
引用论文
分享收藏Genome mapping on nanochannel arrays for structural variation analysis and sequence assembly用于结构变异分析和序列组装的纳米通道阵列上的基因组作图.png)
NATURE BIOTECHNOLOGYOAAI
NATURE BIOTECHNOLOGYIF41.7
OAAI分享收藏Real-Time Emotional Recognition for Sociable Robotics Based on Deep Neural Networks Ensemble基于深度神经网络集成技术的社交机器人实时情感识别
PREAI
分享收藏
查看更多内容