Leaky Integrate and Fire Neuron by Charge-Discharge Dynamics in Floating-Body MOSFET

• Main Authors: Sangya Dutta, Vinay Kumar, Aditya Shukla, Nihar R. Mohapatra, Udayan Ganguly
• Format: Article
• Language: English
• Published: Nature Publishing Group 2017-08-01
• Series: Scientific Reports
• Online Access: https://doi.org/10.1038/s41598-017-07418-y

Abstract Neuro-biology inspired Spiking Neural Network (SNN) enables efficient learning and recognition tasks. To achieve a large scale network akin to biology, a power and area efficient electronic neuron is essential. Earlier, we had demonstrated an LIF neuron by a novel 4-terminal impact ionization based n+/p/n+ with an extended gate (gated-INPN) device by physics simulation. Excellent improvement in area and power compared to conventional analog circuit implementations was observed. In this paper, we propose and experimentally demonstrate a compact conventional 3-terminal partially depleted (PD) SOI- MOSFET (100 nm gate length) to replace the 4-terminal gated-INPN device. Impact ionization (II) induced floating body effect in SOI-MOSFET is used to capture LIF neuron behavior to demonstrate spiking frequency dependence on input. MHz operation enables attractive hardware acceleration compared to biology. Overall, conventional PD-SOI-CMOS technology enables very-large-scale-integration (VLSI) which is essential for biology scale (~1011 neuron based) large neural networks.