A Dual Magnetic Tunnel Junction-Based Neuromorphic Device

被引：18

作者：

Hong, Jeongmin ^{[1
,2
]}

Li, Xin ^{[1
]}

Xu, Nuo ^{[2
]}

Chen, Hong ^{[3
]}

Cabrini, Stefano ^{[4
]}

Khizroev, Sakhrat ^{[5
]}

Bokor, Jeffrey ^{[2
]}

You, Long ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Opt & Elect Informat, Wuhan 430074, Peoples R China

[2] Univ Calif Berkeley, Dept Elect Engn & Comp Sci, Berkeley, CA 94720 USA

[3] Foshan Univ, Sch Mat Sci & Energy Engn, Foshan 528000, Guangdong, Peoples R China

[4] Lawrence Berkeley Natl Lab, Mol Foundry, Berkeley, CA 94720 USA

[5] Univ Miami, Dept Elect & Comp Engn, Coral Gables, FL 33146 USA

来源：

ADVANCED INTELLIGENT SYSTEMS | 2020年 / 2卷 / 12期

基金：

中国国家自然科学基金; 美国国家科学基金会;

关键词：

artificial synapses; domain walls; magnetic tunnel junction; memristors; spin-transfer torque; SYNAPSE;

D O I：

10.1002/aisy.202000143

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With the advent of artificial intelligence (AI) in computational devices technology, various synaptic array architectures are proposed for neuromorphic computing applications. Among them, the non-volatile memory (NVM) architectures are very promising for their small cell size, ultra-low energy consumption, and capability for large parallel data processing through 3D configurations capable of multilevel signal processing. Herein, the viability of such magnetic tunnel junction (MTJ)-based synaptic devices via fabrication and characterization of multi-junction spintronic devices is demonstrated, with the experimental results supported through micromagnetic simulations.

引用

页数：8

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