1. 2022 roadmap on neuromorphic devices and applications research in China
- Author
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Qing Wan, Changjin Wan, Huaqiang Wu, Yuchao Yang, Xiaohe Huang, Peng Zhou, Lin Chen, Tian-Yu Wang, Yi Li, Kan-Hao Xue, Yu-Hui He, Xiang-Shui Miao, Xi Li, Chenchen Xie, Houpeng Chen, Zhitang Song, Hong Wang, Yue Hao, Junyao Zhang, Jia Huang, Zheng Yu Ren, Li Qiang Zhu, Jianyu Du, Chen Ge, Yang Liu, Guanglong Ding, Ye Zhou, Su-Ting Han, Guosheng Wang, Xiao Yu, Bing Chen, Zhufei Chu, Lunyao Wang, Yinshui Xia, Chen Mu, Feng Lin, Chixiao Chen, Bojun Cheng, Yannan Xing, Weitao Zeng, Hong Chen, Lei Yu, Giacomo Indiveri, and Ning Qiao
- Subjects
General Medicine - Abstract
The data throughput in the von Neumann architecture-based computing system is limited by its separated processing and memory structure, and the mismatching speed between the two units. As a result, it is quite difficult to improve the energy efficiency in conventional computing system, especially for dealing with unstructured data. Meanwhile, artificial intelligence and robotics nowadays still behave poorly in autonomy, creativity, and sociality, which has been considered as the unimaginable computational requirement for sensorimotor skills. These two plights have urged the imitation and replication of the biological systems in terms of computing, sensing, and even motoring. Hence, the so-called neuromorphic system has drawn worldwide attention in recent decade, which is aimed at addressing the aforementioned needs from the mimicking of neural system. The recent developments on emerging memory devices, nanotechnologies, and materials science have provided an unprecedented opportunity for this aim.
- Published
- 2022
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