Large Memristor Crossbars for Analog Computing

被引：504

作者：

Li, Can ^{[1
]}

Li, Yunning ^{[1
]}

Jiang, Hao ^{[1
]}

Song, Wenhao ^{[1
]}

Lin, Peng ^{[1
]}

Wang, Zhongrui ^{[1
]}

Yang, J. Joshua ^{[1
]}

Xia, Qiangfei ^{[1
]}

Hu, Miao ^{[2
]}

Montgomery, Eric ^{[2
]}

Zhang, Jiaming ^{[2
]}

Davila, Noraica ^{[2
]}

Graves, Catherine E. ^{[2
]}

Li, Zhiyong ^{[2
]}

Strachan, John Paul ^{[2
]}

Williams, R. Stanley ^{[2
]}

Ge, Ning ^{[3
]}

Barnell, Mark ^{[4
]}

Wu, Qing ^{[4
]}

机构：

[1] Univ Massachusetts, Dept Elect & Comp Engn, Amherst, MA 01003 USA

[2] Hewlett Packard Enterprise, Hewlett Packard Labs, Palo Alto, CA 94304 USA

[3] Hewlett Pachard Inc, HP Labs, Palo Alto, CA 94304 USA

[4] Air Force Res Lab, Informat Directorate, Rome, NY 94304 USA

来源：

2018 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | 2018年

关键词：

memristor; resistance switching; analog computing; signal processing; image processing; vector matrix multiplication; REDUCTION; ARRAY;

D O I：

10.1109/ISCAS.2018.8351877

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Memristor with tunable non-volatile resistance offers in-memory computing capability that avoids the von-Neumann bottleneck. However, large-scale experimental demonstration to this end is yet to be implemented due to the immaturity of the device and integration technologies. Here in this paper we report our recent process in analog computing using analog-voltage-amplitude-vector input and analog-memristor-conductance matrix, with applications in signal and image processing. The vector matrix multiplication is processed in the memristor crossbars in one step, with 5-8 bit precision depending on the array size. The demonstration is made possible by high memristor yield (99.8%), stable multilevel memresistance states, linear current-voltage (IV) relation in the operation range, and low wire resistance between the cells.

引用

页数：4

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