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Memristive dynamics enabled neuromorphic computing systems

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Abstract

The slowing down of transistor scaling and explosive growth for intelligence computing power emerge as the two driving factors for the study of novel devices and materials to pursue highly-efficient computing systems. Memristors, incorporating rich intrinsic dynamics, are a promising candidate for constructing efficient and scalable bio-inspired computing systems. In this progress report, we review the latest advances in novel types of memristors as well as their applications in implementing neuromorphic computing systems. This paper not only covers the memristive dynamics-enabled bionic computing systems but also discusses the memristive sensory systems that integrate sensing and computing. Eventually, device-circuit co-optimization methods are given to emphasize the trend of cross-layer co-design in this fast-evolving field. The innovation in memristor devices mainly focuses on specialized computing hardware and yields superior computing and sensing efficiency. At last, we offer our insight into the trend of state-of-the-art research in memristive materials, devices, circuits, and systems.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 61925401, 92064004, 61927901, 92164302) and 111 Project (Grant No. B18001). Yuchao YANG acknowledges support from Fok Ying-Tong Education Foundation and Tencent Foundation through the XPLORER PRIZE.

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Authors and Affiliations

  1. Center for Brain Inspired Chips, Institute for Artificial Intelligence, Peking University, Beijing, 100871, China

    Bonan Yan, Yuchao Yang & Ru Huang

  2. Beijing Advanced Innovation Center for Integrated Circuits, School of Integrated Circuits, Peking University, Beijing, 100871, China

    Bonan Yan, Yuchao Yang & Ru Huang

  3. School of Electronic and Computer Engineering, Peking University, Shenzhen, 518055, China

    Yuchao Yang

  4. Center for Brain Inspired Intelligence, Chinese Institute for Brain Research (CIBR), Beijing, 102206, China

    Yuchao Yang

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  1. Bonan Yan
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Yan, B., Yang, Y. & Huang, R. Memristive dynamics enabled neuromorphic computing systems. Sci. China Inf. Sci. 66, 200401 (2023). https://doi.org/10.1007/s11432-023-3739-0

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