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4K-memristor analog-grade passive crossbar circuit

Author

Listed:
  • H. Kim

    (University of California
    Department of Electronic Engineering of Inha University)

  • M. R. Mahmoodi

    (University of California)

  • H. Nili

    (University of California)

  • D. B. Strukov

    (University of California)

Abstract

The superior density of passive analog-grade memristive crossbar circuits enables storing large neural network models directly on specialized neuromorphic chips to avoid costly off-chip communication. To ensure efficient use of such circuits in neuromorphic systems, memristor variations must be substantially lower than those of active memory devices. Here we report a 64 × 64 passive crossbar circuit with ~99% functional nonvolatile metal-oxide memristors. The fabrication technology is based on a foundry-compatible process with etch-down patterning and a low-temperature budget. The achieved

Suggested Citation

  • H. Kim & M. R. Mahmoodi & H. Nili & D. B. Strukov, 2021. "4K-memristor analog-grade passive crossbar circuit," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-25455-0
    DOI: 10.1038/s41467-021-25455-0
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    Cited by:

    1. Peng Chen & Fenghao Liu & Peng Lin & Peihong Li & Yu Xiao & Bihua Zhang & Gang Pan, 2023. "Open-loop analog programmable electrochemical memory array," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    2. Choi, Woo Sik & Kim, Donguk & Yang, Tae Jun & Chae, Inseok & Kim, Changwook & Kim, Hyungjin & Kim, Dae Hwan, 2022. "Electrode-dependent electrical switching characteristics of InGaZnO memristor," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    3. Kim, Tae-Hyeon & Kim, Sungjoon & Hong, Kyungho & Park, Jinwoo & Hwang, Yeongjin & Park, Byung-Gook & Kim, Hyungjin, 2021. "Multilevel switching memristor by compliance current adjustment for off-chip training of neuromorphic system," Chaos, Solitons & Fractals, Elsevier, vol. 153(P2).
    4. Lee, Geun Ho & Kim, Tae-Hyeon & Song, Min Suk & Park, Jinwoo & Kim, Sungjoon & Hong, Kyungho & Kim, Yoon & Park, Byung-Gook & Kim, Hyungjin, 2022. "Effect of weight overlap region on neuromorphic system with memristive synaptic devices," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    5. Sang Hyun Sung & Tae Jin Kim & Hyera Shin & Tae Hong Im & Keon Jae Lee, 2022. "Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    6. Jaeseoung Park & Ashwani Kumar & Yucheng Zhou & Sangheon Oh & Jeong-Hoon Kim & Yuhan Shi & Soumil Jain & Gopabandhu Hota & Erbin Qiu & Amelie L. Nagle & Ivan K. Schuller & Catherine D. Schuman & Gert , 2024. "Multi-level, forming and filament free, bulk switching trilayer RRAM for neuromorphic computing at the edge," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    7. Choi, Woo Sik & Jang, Jun Tae & Kim, Donguk & Yang, Tae Jun & Kim, Changwook & Kim, Hyungjin & Kim, Dae Hwan, 2022. "Influence of Al2O3 layer on InGaZnO memristor crossbar array for neuromorphic applications," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    8. Lee, Geun Ho & Kim, Tae-Hyeon & Youn, Sangwook & Park, Jinwoo & Kim, Sungjoon & Kim, Hyungjin, 2023. "Low-fluctuation nonlinear model using incremental step pulse programming with memristive devices," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).

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