电讯技术2024，Vol.64Issue(1)：14-21,8.DOI:10.20079/j.issn.1001-893x.221208003
一种FPGA集群轻量级深度学习计算架构设计及实现
Design and Implementation of Lightweight Deep Learning Computing Architecture for FPGA Cluster
摘要
Abstract
With the development of sensor technology,the functions of edge or terminal equipment are rapidly upgraded,and the data quantity of front-end battlefield increases exponentially.According to the contradiction between the inability of chips and the sharp growth of data volume on edge and terminal equipment,combined with the Map/Reduce framework,a deep learning architecture based on field programmable gate array(FPGA)computing cluster resources is proposed,which can deploy multiple applications with deep learning algorithms and can be widely used in military scenes and civilian scenes such as forest fire prevention.关键词
深度学习/边缘计算/端设备/海量数据/实时处理Key words
deep learning/edge computing/terminal equipment/massive data/real-time processing分类
信息技术与安全科学引用本文复制引用
刘红伟,潘灵,吴明钦,韩毅辉,侯云,席国江..一种FPGA集群轻量级深度学习计算架构设计及实现[J].电讯技术,2024,64(1):14-21,8.基金项目
四川省重点研发计划项目(2022YFG0231) （2022YFG0231）
四川省自然科学基金项目(2023NSFSC0497) （2023NSFSC0497）
