Double-Gated Asymmetric Floating-Gate-Based Synaptic Device for Effective Performance Enhancement Through Online Learning

Donghyun Ryu,Jong-Ho Lee,Tae-Hyung Kim,Byung-Gook Park,Taejin Jang,Junsu Yu

doi:10.1109/access.2020.3041734

Donghyun Ryu, Jong-Ho Lee + Show 4 more

Open Access

https://doi.org/10.1109/access.2020.3041734

Copy DOI

Abstract

In this paper, we propose a floating-gate-based synaptic transistor with two independent control gates that implement both offline and online learning. Unlike previous research on double-gated synaptic transistors, the proposed device is capable of online learning without facing a fan-out problem. Basic operation of the device was verified and a program/erase scheme based on Fowler-Northeim tunneling is suggested for the multi-conductance utilization of the synaptic device. With the proposed P/E scheme, an offline-trained single-layered hardware-based spiking neural network was simulated for MNIST classification, resulting in 87.37% classification accuracy with 10% conductance variation. To alleviate this performance degradation, the online learning method is applied on the offline-trained SNN by reusing 3,000 training images. The effectiveness of the proposed method is also verified under existence of the synaptic weight variance. As a result, up to 86.89% of the performance degradation is alleviated.

Highlights

Neuromorphic systems are rising candidates for the generation computing system due to their massively parallel data processing capability and minimal power consumption [1]–[8]
Neuromorphic systems consist of neuron circuits and synaptic devices, and their implementation differ depending on the specific combination of incorporated circuits and devices
Doped poly-silicon is used for gate1 and gate2 for effective program/erase and online learning

Summary

Introduction

Neuromorphic systems are rising candidates for the generation computing system due to their massively parallel data processing capability and minimal power consumption [1]–[8]. D. Ryu et al.: Double-Gated Asymmetric Floating-Gate-Based Synaptic Device for Effective Performance Enhancement TABLE 1. Conventional double-gated synaptic devices use output pulse of presynaptic neuron as current source to prevent drain current flowing when only teaching signal is given.

Results

Conclusion