Journal of Guangxi Normal University(Natural Science Edition) ›› 2018, Vol. 36 ›› Issue (1): 9-16.doi: 10.16088/j.issn.1001-6600.2018.01.002

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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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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

CLC Number: 

  • TP183
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