Spintronic leaky-integrate-fire spiking neurons with self-reset and winner-takes-all for neuromorphic computing

Di Wang, Ruifeng Tang, Huai Lin, Long Liu, Nuo Xu, Yan Sun, Xuefeng Zhao, Ziwei Wang, Dandan Wang, Zhihong Mai, Yongjian Zhou, Nan Gao, Cheng Song, Lijun Zhu, Tom Wu, Ming Liu, Guozhong Xing

Research output: Journal article publicationJournal articleAcademic researchpeer-review

27 Citations (Scopus)

Abstract

Neuromorphic computing using nonvolatile memories is expected to tackle the memory wall and energy efficiency bottleneck in the von Neumann system and to mitigate the stagnation of Moore’s law. However, an ideal artificial neuron possessing bio-inspired behaviors as exemplified by the requisite leaky-integrate-fire and self-reset (LIFT) functionalities within a single device is still lacking. Here, we report a new type of spiking neuron with LIFT characteristics by manipulating the magnetic domain wall motion in a synthetic antiferromagnetic (SAF) heterostructure. We validate the mechanism of Joule heating modulated competition between the Ruderman–Kittel–Kasuya–Yosida interaction and the built-in field in the SAF device, enabling it with a firing rate up to 17 MHz and energy consumption of 486 fJ/spike. A spiking neuron circuit is implemented with a latency of 170 ps and power consumption of 90.99 μW. Moreover, the winner-takes-all is executed with a current ratio >104 between activated and inhibited neurons. We further establish a two-layer spiking neural network based on the developed spintronic LIFT neurons. The architecture achieves 88.5% accuracy on the handwritten digit database benchmark. Our studies corroborate the circuit compatibility of the spintronic neurons and their great potential in the field of intelligent devices and neuromorphic computing.

Original languageEnglish
Article number1068
JournalNature Communications
Volume14
Issue number1
DOIs
Publication statusPublished - Feb 2023

ASJC Scopus subject areas

  • General Chemistry
  • General Biochemistry,Genetics and Molecular Biology
  • General Physics and Astronomy

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