Ferroelectric devices and circuits for neuro-inspired computing

被引:0
|
作者
Panni Wang
Shimeng Yu
机构
[1] Georgia Institute of Technology,School of Electrical and Computer Engineering
来源
MRS Communications | 2020年 / 10卷
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摘要
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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页码:538 / 548
页数:10
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