Dual-Layer-Per-Array Operation Using Local Polarization Switching of Ferroelectric Tunnel FETs for Massive Neural Networks

Abstract

A novel dual-layer-per-array (DLPA) operation is proposed and experimentally demonstrated by using ferroelectric tunnel field-effect transistors (FeTFETs) as synaptic transistors for high-density and low-power neuromorphic computing applications for the first time. Through local polarization switching (LPS), two distinct synaptic weight sets are stored and processed by utilizing the symmetrical and independent forward and ambipolar current regions within a single FeTFET. The stored weights of each region are multiplied by input gate voltages in the two-layer operation modes of TFETs: forward and ambipolar layer, enabling separate vector-matrix multiplication (VMM) operations within a single device array and doubling computational density. It is expected that the DLPA operation of FeTFETs will facilitate the implementation of large neural networks by reducing the footprint of conventional neuromorphic hardware by 50%.