Proposition of Adaptive Read Bias: A Solution to Overcome Power and Scaling Limitations in Ferroelectric-Based Neuromorphic System.

ABSTRACT: Hardware neuromorphic systems are crucial for the energy-efficient processing of massive amounts of data. Among various candidates, hafnium oxide ferroelectric tunnel junctions (FTJs) are highly promising for artificial synaptic devices. However, FTJs exhibit non-ideal characteristics that introduce variations in synaptic weights, presenting a considerable challenge in achieving high-performance neuromorphic systems. The primary objective of this study is to analyze the origin and impact of these variations in neuromorphic systems. The analysis reveals that the major bottleneck in achieving a high-performance neuromorphic system is the dynamic variation, primarily caused by the intrinsic 1/f noise of the device. As the device area is reduced and the read bias (V_Read ) is lowered

SUBMITTER: Koo RH 

PROVIDER: S-EPMC10837350 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature