A Novel Ferroelectric FET-Based Adaptively-Stochastic Neuron for Stimulated-Annealing Based Optimizer With Ultra-Low Hardware Cost
Jin Luo, Tianyi Liu, Zhiyuan Fu, Xinming Wei, Mengxuan Yang, Liang Chen, Qianqian Huang, Ru Huang
Abstract
In this work, based on ferroelectric FET (FeFET), a novel capacitor-less and bio-inspired adaptively-stochastic neuron is proposed and experimentally demonstrated for the first time for solving optimization problems in spiking neural network with remarkably reduced hardware cost. By exploiting the physics of inherent stochastic dynamic process of ferroelectric domains nucleation, the proposed FeFET-based neuron with only three transistors can realize adaptively stochastic spike firing behavior, where its stochasticity gradually decreases during operation. The adaptive stochasticity is experimentally demonstrated for the hardware implementation of stochastic simulated annealing algorithm for optimization, providing a promising ultralow-hardware-cost solution for solving optimization problems.