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MEMRISTORS

Device solutions to scientific computing

Nature Electronics volume 1, pages 382–383 (2018)Cite this article

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A memristor-based system can solve partial differential equations with better energy efficiency than methods based on conventional computers.

Memristors are nanoscale electrical devices that can simultaneously store and process data at a very low energy cost. As a result, there is significant research interest in using them to develop the next generation of computer architectures and memory. The electrical behaviour of memristors is, however, partially random, which has limited their application in domains like high-precision scientific computing. Writing in Nature Electronics, Wei Lu and colleagues at the University of Michigan now propose an approach to overcome this limitation, and demonstrate a memristor-based system that can solve partial differential equations1. Notably, the results indicate that scientific computing with memristors can significantly outperform other approaches.

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Fig. 1: Memristor crossbar performing matrix–vector multiplication.

References

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  1. Air Force Research Laboratory, Rome, NY, USA

    Cory Merkel

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  1. Cory Merkel
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Correspondence to Cory Merkel.

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Any opinions, findings and conclusions or recommendations expressed here are those of the author and do not necessarily reflect the views of the Air Force Research Laboratory or its contractors.

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Merkel, C. Device solutions to scientific computing. Nat Electron 1, 382–383 (2018). https://doi.org/10.1038/s41928-018-0108-y

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