High precision tuning of state for memristive devices by adaptable variation-tolerant algorithm

被引:445
作者
Alibart, Fabien [1 ]
Gao, Ligang [1 ]
Hoskins, Brian D. [2 ]
Strukov, Dmitri B. [1 ]
机构
[1] Univ Calif Santa Barbara, Dept Elect & Comp Engn, Santa Barbara, CA 93106 USA
[2] Univ Calif Santa Barbara, Dept Mat, Santa Barbara, CA 93106 USA
基金
美国国家科学基金会;
关键词
MEMORY; CIRCUITS; RESISTANCE; SYNAPSE; ANALOG; FILMS;
D O I
10.1088/0957-4484/23/7/075201
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Using memristive properties common for titanium dioxide thin film devices, we designed a simple write algorithm to tune device conductance at a specific bias point to 1% relative accuracy (which is roughly equivalent to seven-bit precision) within its dynamic range even in the presence of large variations in switching behavior. The high precision state is nonvolatile and the results are likely to be sustained for nanoscale memristive devices because of the inherent filamentary nature of the resistive switching. The proposed functionality of memristive devices is especially attractive for analog computing with low precision data. As one representative example we demonstrate hybrid circuitry consisting of an integrated circuit summing amplifier and two memristive devices to perform the analog multiply-and-add (dot-product) computation, which is a typical bottleneck operation in information processing.
引用
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页数:7
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