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MEMRISTORS

Multiplication on the edge

Nature Electronics volume 1, pages 8–9 (2018)Cite this article

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Analogue computing based on memristors could offer a faster and more energy-efficient alternative to conventional digital computing in IoT applications.

We live in an analogue world, where the information around us is best represented by analogue parameters. Traditional computing technologies, in contrast, operate predominantly in the digital domain. This means that processing analogue signals is inefficient in terms of speed and energy consumption, as the analogue information must be converted to digital data. In the near future, these problems are likely to be exacerbated as the development of the Internet of Things (IoT) leads to the proliferation of devices whose vast amounts of generated data must be processed at the source — commonly known as ‘edge’ computing. Future conventional edge devices are expected to be connected to sensors or actuators but have limited processing power, which presents difficulties when processing real-time data with high speed and low energy consumption. New technologies and approaches are therefore required to process analogue signals. Writing in Nature Electronics, John Paul Strachan, J. Joshua Yang, Qiangfei Xia and colleagues show that large-scale memristor arrays can be used for efficient analogue computing in specific cases1.

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Fig. 1: Applications for analogue computing based on memristor crossbar arrays.

robot, Alexey Kotelnikov / Alamy Stock Photo.

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Authors and Affiliations

  1. Institute of Microelectronics, Tsinghua University, Beijing, China

    Huaqiang Wu, Peng Yao, Bin Gao & He Qian

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  1. Huaqiang Wu
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  2. Peng Yao
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  3. Bin Gao
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  4. He Qian
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Correspondence to Huaqiang Wu.

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Wu, H., Yao, P., Gao, B. et al. Multiplication on the edge. Nat Electron 1, 8–9 (2018). https://doi.org/10.1038/s41928-017-0011-y

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