广西师范大学学报（自然科学版） ›› 2018, Vol. 36 ›› Issue (1): 9-16.doi: 10.16088/j.issn.1001-6600.2018.01.002

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脉冲神经网络硬件系统性能监测平台

万雷,罗玉玲*,黄星月   

  1. 广西师范大学电子工程学院,广西桂林541004
  • 收稿日期:2017-05-23 出版日期:2018-01-20 发布日期:2018-07-17
  • 通讯作者: 罗玉玲(1984—),女,湖北武汉人,广西师范大学副教授。E-mail:yuling0616@mailbox.gxnu.edu.cn
  • 基金资助:
    国家自然科学基金(61603104);广西自然科学基金(2015GXNSFFBA139256,2016GXNSFCA380017);广西高校中青年骨干教师基础能力提升项目(KY2016YB059);广西人文社会科学发展研究中心项目(ZX2016030);广西研究生教育创新计划项目(YCSZ2016034)

Monitoring Platform for the Hardware Spike Neural Networks

WAN Lei,LUO Yuling*,HUANG Xingyue   

  1. College of Electronic Engineering,Guangxi Normal University,Guilin Guangxi 541004, China
  • Received:2017-05-23 Online:2018-01-20 Published:2018-07-17

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摘要： 随着脉冲神经网络规模不断增大、功能越来越复杂,如何快速地验证神经网络硬件系统结构各部分的功能,并准确地评估其性能成为设计者面临的严峻挑战。本文设计了一款可视化性能监测平台,用于脉冲神经网络硬件系统的功能验证和性能监测。以Xilinx Zynq-7000器件为例,测试结果表明该监测平台具有轻量化设计、良好的人机交互界面和通用性等优势,能够提高脉冲神经网络硬件系统的功能验证和性能评估效率,为其硬件系统设计提供了较好的辅助功能验证与性能分析手段。

关键词: 脉冲神经网络, 硬件系统, 监测平台, 可视化, 功能验证, 性能监测

Abstract: With the increasing size of the spike neural network with very complicated functions,how to quickly verify the functions of the hardware system structure of the neural network,and accurately assess its performance has become a serious challenge for designers. A visualization performance monitoring platform is designed in this paper,which is used as functional verification and performance monitoring for the hardware SNNs. The monitoring platform takes the Xilinx Zynq-7000 device as an example and has the advantages of lightweight design,good human-computer interaction interface and versatility,and can improve the efficiency of system function verification and performance evaluation of SNN hardware structure. It provides auxiliary functional verification and performance analysis for the design of SNN hardware systems.

Key words: spike neural network, hardware system, monitoring platform, visualization, functional verification, performance monitoring

中图分类号: 

  • TP183
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