Compact leak-integrate-fire neuron with auto-reset functionality based on a single spin-orbit torque magnetic tunnel junction device

被引:1
|
作者
Wang, Shiqi [1 ]
Chen, Runjie [2 ]
Wang, Chenyang [2 ]
Cai, Wenlong [1 ,3 ]
Zhu, Daoqian [1 ,3 ]
Du, Ao [1 ]
Wang, Zixi [1 ]
Chen, Zanhong [1 ]
Shi, Kewen [1 ,3 ]
Zhao, Weisheng [1 ,3 ]
机构
[1] Beihang Univ, Fert Beijing Inst, Sch Integrated Circuit Sci & Engn, Beijing 100191, Peoples R China
[2] Shanghai Starriver Bilingual Sch, Shanghai 200000, Peoples R China
[3] Beihang Univ, Inst Int Innovat, Natl Key Lab Spintron, Hangzhou 311115, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
SPIKING NEURONS; SPINTRONICS;
D O I
10.1063/5.0191119
中图分类号
O59 [应用物理学];
学科分类号
摘要
Leaky-integrate-fire (LIF) neurons are core components to construct a spiking neural network. The emulation of LIF neurons has been implemented in spintronic devices, but typically suffers from challenges, such as relatively complex design and the requirement of additional operations for resetting. In this Letter, we propose a compact LIF neuron device realized within a single spin-orbit torque (SOT) magnetic tunnel junction device. Distinct from standard memory devices, the input SOT current for the integrating process is applied in a manner such that the magnetization cannot cross the hard plane. Consequently, the device can automatically reset to its original state by the combined effects of anisotropy and damping, which play a vital role during the leaky process as well. We verify the proposal in three types of SOT devices by micromagnetic simulations, and the power consumption is estimated as 0.1 pJ/spike. The auto-reset process is further captured by our single-shot dynamic experiments. With the state-of-the-art SOT technology, our work provides a concise and plausible scheme to mimic LIF neurons, which is of practical interest for neuromorphic computing.
引用
收藏
页数:6
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