Journal ArticleDOI
Neuro-inspired computing chips
Wenqiang Zhang,Bin Gao,Jianshi Tang,Peng Yao,Shimeng Yu,Meng-Fan Chang,Hoi-Jun Yoo,He Qian,Huaqiang Wu +8 more
- Vol. 3, Iss: 7, pp 371-382
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TLDR
The development of neuro-inspired computing chips and their key benchmarking metrics are reviewed, providing a co-design tool chain and proposing a roadmap for future large-scale chips are provided and a future electronic design automation tool chain is proposed.Abstract:
The rapid development of artificial intelligence (AI) demands the rapid development of domain-specific hardware specifically designed for AI applications. Neuro-inspired computing chips integrate a range of features inspired by neurobiological systems and could provide an energy-efficient approach to AI computing workloads. Here, we review the development of neuro-inspired computing chips, including artificial neural network chips and spiking neural network chips. We propose four key metrics for benchmarking neuro-inspired computing chips — computing density, energy efficiency, computing accuracy, and on-chip learning capability — and discuss co-design principles, from the device to the algorithm level, for neuro-inspired computing chips based on non-volatile memory. We also provide a future electronic design automation tool chain and propose a roadmap for the development of large-scale neuro-inspired computing chips. This Review Article examines the development of neuro-inspired computing chips and their key benchmarking metrics, providing a co-design tool chain and proposing a roadmap for future large-scale chips.read more
Citations
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Journal ArticleDOI
2D materials-based homogeneous transistor-memory architecture for neuromorphic hardware.
Lei Tong,Zhuiri Peng,Runfeng Lin,Zheng Li,Yilun Wang,Xinyu Huang,Kan-Hao Xue,Hangyu Xu,Feng Liu,Hui Xia,Peng Wang,Mingsheng Xu,Wei Xiong,Weida Hu,Jianbin Xu,Xinliang Zhang,Lei Ye,Xiangshui Miao +17 more
TL;DR: In neuromorphic hardware, peripheral circuits and memories based on heterogeneous devices are generally physically separated as mentioned in this paper, and exploration of homogeneous devices for these components is key for their exploration.
Journal ArticleDOI
Dynamical memristors for higher-complexity neuromorphic computing
TL;DR: How novel material properties enable complex dynamics and define different orders of complexity in memristor devices and systems are discussed, which enable new computing architectures that offer dramatically greater computing efficiency than conventional computers.
Journal ArticleDOI
Negative Photoconductance Effect: An Extension Function of the TiOx-Based Memristor
Guangdong Zhou,Bai Sun,Xiaofang Hu,Linfeng Sun,Zhuo Zou,Bo Xiao,Wuke Qiu,Bo Wu,Jie Li,Juanjuan Han,Liping Liao,Cunyun Xu,Gang Xiao,Lihua Xiao,Jianbo Cheng,Shaohui Zheng,Lidan Wang,Qunliang Song,Shukai Duan +18 more
Journal ArticleDOI
Memristive Crossbar Arrays for Storage and Computing Applications
Huihan Li,Shaocong Wang,Xumeng Zhang,Wei Wang,Rui Yang,Zhong Sun,Wanxiang Feng,Peng Lin,Zhongrui Wang,Linfeng Sun,Yugui Yao +10 more
TL;DR: Crossbar architecture is introduced, the origin of sneak‐path current is reviewed, techniques to mitigate this issue from the angle of materials and circuits are discussed, and the applications of memristive crossbars in both machine learning and neuromorphic computing are surveyed.
Journal ArticleDOI
Noise-assisted persistence and recovery of memory state in a memristive spiking neuromorphic network
Igor A. Surazhevsky,Vyacheslav A. Demin,A.I. Ilyasov,A.I. Ilyasov,Andrey V. Emelyanov,Andrey V. Emelyanov,K. E. Nikiruy,Vladimir V. Rylkov,S.A. Shchanikov,I. A. Bordanov,S. A. Gerasimova,Davud V. Guseinov,N. V. Malekhonova,D. A. Pavlov,Alexey Belov,Alexey Mikhaylov,Victor B. Kazantsev,Davide Valenti,Bernardo Spagnolo,Bernardo Spagnolo,Mikhail V. Kovalchuk,Mikhail V. Kovalchuk +21 more
TL;DR: This work investigates the constructive role of an external noise signal, in the form of a low-rate Poisson sequence of pulses supplied to all inputs of a spiking neural network, consisting in maintaining for a long time or even recovering a memory trace of the image without its direct renewal (or rewriting).
References
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