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The future of electronics based on memristive systems


A memristor is a resistive device with an inherent memory. The theoretical concept of a memristor was connected to physically measured devices in 2008 and since then there has been rapid progress in the development of such devices, leading to a series of recent demonstrations of memristor-based neuromorphic hardware systems. Here, we evaluate the state of the art in memristor-based electronics and explore where the future of the field lies. We highlight three areas of potential technological impact: on-chip memory and storage, biologically inspired computing and general-purpose in-memory computing. We analyse the challenges, and possible solutions, associated with scaling the systems up for practical applications, and consider the benefits of scaling the devices down in terms of geometry and also in terms of obtaining fundamental control of the atomic-level dynamics. Finally, we discuss the ways we believe biology will continue to provide guiding principles for device innovation and system optimization in the field.

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Fig. 1: The race towards future computing solutions.
Fig. 2: Hardware implementation of artificial neural networks in a memristor crossbar.
Fig. 3: Rapid advances in memristor technology.
Fig. 4: Possible evolution of the computing system.

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We acknowledge inspiring discussions with R. S. Williams, G. Astfalk, X. Zhu, W. Ma, F. Cai and Y. Jeong. This work was supported in part by the National Science Foundation (NSF) through grant CCF-1617315, by the Defense Advanced Research Program Agency (DARPA) through award HR0011-17-2-0018, and by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via contract number 2017-17013000002.

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W.D.L conceived the project. All authors performed the project planning and comparative analysis. All authors carried out the discussions and the manuscript writing at all stages.

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Correspondence to John Paul Strachan or Wei D. Lu.

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Zidan, M.A., Strachan, J.P. & Lu, W.D. The future of electronics based on memristive systems. Nat Electron 1, 22–29 (2018).

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