Chinese Journal on Internet of Things ›› 2022, Vol. 6 ›› Issue (1): 20-28.doi: 10.11959/j.issn.2096-3750.2022.00250

Special Issue: 边缘计算

• Topic: IoT Terminals and Chips • Previous Articles     Next Articles

Verification of an artificial intelligence vision chip design for edge computing based on hardware simulation system

Xuanzhe XU1,2, Ke NING1,2, Xuemin ZHENG1,2, Mingxin ZHAO1,2, Mengmeng XU1,2, Nanjian WU1,2, Liyuan LIU1,2   

  1. 1 The State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
    2 Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
  • Revised:2022-03-01 Online:2022-03-30 Published:2022-03-01
  • Supported by:
    The National Key Research and Development Program of China(2019YFB2204300);The National Natural Science Foundation of China(U20A20205);The National Natural Science Foundation of China(61874107);The Program of Youth Innovation Promotion Association, Chinese Academy of Sciences(2021109)

Abstract:

The rise of visual deep learning algorithms based on convolutional neural network (CNN) has promoted the rapid development of the artificial intelligence (AI) vision chip design research.The step of chip verification is a bottleneck in the development of AI vision chips.A software and hardware verification method for AI vision chip design based on hardware simulation system was introduced.Taking AI vision chip design for edge computing as an example, the chip was run on the hardware simulation system (ZeBu) and the simulation verification work of typical deep learning network MobileNet was completed.The results show that the network model implemented on the hardware chip architecture keeps accuracy while the detection time of a single frame is only 18.51 ms under a 200 MHz clock frequency.The spread of the hardware simulation is 7 times faster than than of the software simulation.

Key words: AI vision chip, deep learning, MobileNet, ZeBu

CLC Number: 

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