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Ferroelectric devices and circuits for neuro-inspired computing

Published online by Cambridge University Press:  21 September 2020

Panni Wang Open the ORCID record for Panni Wang [Opens in a new window]  and
Shimeng Yu
Panni Wang
Affiliation:
School of Electrical and Computer Engineering, Georgia Institute of Technology, 791 Atlantic Dr NW, Atlanta, GA 30332, USA
Shimeng Yu*
Affiliation:
School of Electrical and Computer Engineering, Georgia Institute of Technology, 791 Atlantic Dr NW, Atlanta, GA 30332, USA
*
Address all correspondence to Shimeng Yu at [email protected]
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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.

Type
Prospective Articles
Information
MRS Communications , Volume 10 , Issue 4 , December 2020 , pp. 538 - 548
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Copyright
Copyright © The Author(s), 2020, published on behalf of Materials Research Society by Cambridge University Press

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