Analog Spiking Neuron in 28 nm CMOS
Authors:
- 19 June 2022
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 148-152
Abstract
Traditional computer clusters are facing a significant limitation as a result of the big data revolution. We need efficient edge devices to bring the power of machine learning algorithms from power-hungry room servers to mobile consumer platforms. Neuromorphic engineering is a promising avenue for developing the next generation of edge devices that combine high computing capabilities with low power consumption in a small form factor. This paper shows the proof of concept of an analog/mixed-signal CMOS neuromorphic system on a chip (NeuroSoC) by presenting a low-power design of a leaky integrate-and-fire (LIF) neuron. The design uses eight transistors and two capacitors for low complexity and potential to lead to very dense systems. The proposed model consumes 1.2 fJ/spike and occupies an active area of 6.73 µm by 5.09 µm when implemented in 28 nm CMOS. The maximum spiking frequency is 343 kHz.Keywords
This publication has 13 references indexed in Scilit:
- A Sub-35 pW Axon-Hillock artificial neuron circuitSolid-State Electronics, 2019
- A 4-fJ/Spike Artificial Neuron in 65 nm CMOS TechnologyFrontiers in Neuroscience, 2017
- A million spiking-neuron integrated circuit with a scalable communication network and interfaceScience, 2014
- Hardware spiking neurons design: Analog or digital?2012
- Energy-Efficient Neuron, Synapse and STDP Integrated CircuitsIEEE Transactions on Biomedical Circuits and Systems, 2012
- Compact silicon neuron circuit with spiking and bursting behaviourNeural Networks, 2008
- A Review of the Integrate-and-fire Neuron Model: I. Homogeneous Synaptic InputBiological Cybernetics, 2006
- A VLSI Array of Low-Power Spiking Neurons and Bistable Synapses With Spike-Timing Dependent PlasticityIEEE Transactions on Neural Networks, 2006
- Simple model of spiking neuronsIEEE Transactions on Neural Networks, 2003
- A quantitative description of membrane current and its application to conduction and excitation in nerveThe Journal of Physiology, 1952