Ternary Logic with Stateful Neural Networks Using a Bilayered TaOX-Based Memristor Exhibiting Ternary States

被引:29
作者
Kim, Young Seok [1 ]
An, Jangho [1 ]
Jeon, Jae Bum [1 ]
Son, Myeong Won [1 ]
Son, Seoil [1 ]
Park, Woojoon [1 ]
Lee, Younghyun [1 ]
Park, Juseong [1 ]
Kim, Geun Young [1 ]
Kim, Gwangmin [1 ]
Song, Hanchan [1 ]
Kim, Kyung Min [1 ]
机构
[1] Korea Adv Inst Sci & Technol, Dept Mat Sci & Engn, 291 Daehak Ro, Daejeon 34141, South Korea
基金
新加坡国家研究基金会;
关键词
in-memory computing; memristors; neural networks; stateful logic; ternary logic; MEMORY; OPERATIONS;
D O I
10.1002/advs.202104107
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
A memristive stateful neural network allowing complete Boolean in-memory computing attracts high interest in future electronics. Various Boolean logic gates and functions demonstrated so far confirm their practical potential as an emerging computing device. However, spatio-temporal efficiency of the stateful logic is still too limited to replace conventional computing technologies. This study proposes a ternary-state memristor device (simply a ternary memristor) for application to ternary stateful logic. The ternary-state implementable memristor device is developed with bilayered tantalum oxide by precisely controlling the oxygen content in each oxide layer. The device can operate 157 ternary logic gates in one operational clock, which allows an experimental demonstration of a functionally complete three-valued Lukasiewicz logic system. An optimized logic cascading strategy with possible ternary gates is approximate to 20% more efficient than conventional binary stateful logic, suggesting it can be beneficial for higher performance in-memory computing.
引用
收藏
页数:9
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