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A full spectrum of computing-in-memory technologies

Nature Electronics volume 6, pages 823–835 (2023)Cite this article

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Abstract

Computing in memory (CIM) could be used to overcome the von Neumann bottleneck and to provide sustainable improvements in computing throughput and energy efficiency. Underlying the different CIM schemes is the implementation of two kinds of computing primitive: logic gates and multiply–accumulate operations. Considering the input and output in either operation, CIM technologies differ in regard to how memory cells participate in the computation process. This complexity makes it difficult to build a comprehensive understanding of CIM technologies. Here, we provide a full-spectrum classification of all CIM technologies by identifying the degree of memory cells participating in the computation as inputs and/or output. We elucidate detailed principles for standard CIM technologies across this spectrum, and provide a platform for comparing the advantages and disadvantages of each of the different technologies. Our taxonomy could also potentially be used to develop other CIM schemes by applying the spectrum to different memory devices and computing primitives.

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Fig. 1: Computing primitives and CIM basics.
Fig. 2: A full spectrum of CIM technologies.
Fig. 3: XYZ-CIM, XZ-CIM and Z-CIM.
Fig. 4: XY-CIM and X-CIM.

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Acknowledgements

This work has received funding from the National Key R&D Program of China (2020YFB2206001, 2022ZD0118901), the National Natural Science Foundation of China (62004002, 92064004, 61927901, 62025401, 61834001, 92264203), the 111 Project (B18001) and the NSF-BSF (2020-613). A.M. acknowledges financial support from the Royal Academy of Engineering in the form of a Senior Research Fellowship.

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  1. Institute for Artificial Intelligence, School of Integrated Circuits, Peking University, Beijing Advanced Innovation Center for Integrated Circuits, Beijing, China

    Zhong Sun, Yimao Cai & Ru Huang

  2. The Andrew and Erna Viterbi Faculty of Electrical and Computer Engineering, Technion—Israel Institute of Technology, Haifa, Israel

    Shahar Kvatinsky

  3. Department of Electronic Engineering, Southeast University, Nanjing, China

    Xin Si

  4. Department of Electronic & Electrical Engineering, UCL, London, UK

    Adnan Mehonic

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A.M. is a founder and director of Intrinsic Semiconductor Technologies Ltd (www.intrinsicst.com), a spin-out company commercializing silicon oxide RRAM.

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Sun, Z., Kvatinsky, S., Si, X. et al. A full spectrum of computing-in-memory technologies. Nat Electron 6, 823–835 (2023). https://doi.org/10.1038/s41928-023-01053-4

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