Abstract
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.
Funder
Science and Technology Commission of Shanghai Municipality
Shanghai Educational Development Foundation
Major Scientific Project of Zhejiang Laboratory
State Key Laboratory of ASIC and System, Fudan University
National Natural Science Foundation of China
Science, Technology and Innovation Commission of Shenzhen Municipality
Shanghai Rising-Star Program
Program of Shanghai Subject Chief Scientist
Natural Science Foundation of Zhejiang Province
Youth Innovation Promotion Association of the Chinese Academy of Sciences
National Key Research and Development Program of China
Shanghai Municipal Education Commission
Cited by
6 articles.
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