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

2012; IOP Publishing; Volume: 23; Issue: 7 Linguagem: Inglês

10.1088/0957-4484/23/7/075201

1361-6528

Fabien Alibart, Ligang Gao, Brian D. Hoskins, Dmitri B. Strukov,

Neuroscience and Neural Engineering

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.