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Ferroelectric devices and circuits for neuro-inspired computing

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Abstract

Recent discovery of ferroelectricity in doped HfO2 has reignited research interest in the ferroelectric field-effect transistor (FeFET) as emerging embedded nonvolatile memory with the potential for neuro-inspired computing. This paper reviews two major aspects for its application in neuro-inspired computing: ferroelectric devices as multilevel synaptic devices and the circuit primitive design with FeFET for in-memory computing. First, the authors survey representative FeFET-based synaptic devices. Then, the authors introduce 2T-1FeFET synaptic cell design that improves its in situ training accuracy to approach software baseline. Then, the authors introduce the FeFET drain–erase scheme for array-level operations, which makes the in situ training feasible for FeFET-based hardware accelerator. Finally, the authors give an outlook on the future 3D-integrated 2T-1FeFET design.

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Acknowledgments

This work was supported, in part, by ASCENT, one of the SRC/DARPA JUMP centers. The authors thank the collaborators Prof. Suman Datta and Prof. Asif Khan and other group members Xiaoyu Sun, Xiaochen Peng, Yandong Luo, Jae Hur, and Zheng Wang.

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  1. School of Electrical and Computer Engineering, Georgia Institute of Technology, 791 Atlantic Dr NW, Atlanta, GA, 30332, USA

    Panni Wang & Shimeng Yu

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  1. Panni Wang
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  2. Shimeng Yu
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Correspondence to Shimeng Yu.

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Wang, P., Yu, S. Ferroelectric devices and circuits for neuro-inspired computing. MRS Communications 10, 538–548 (2020). https://doi.org/10.1557/mrc.2020.71

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