A tunable and versatile 28nm FD-SOI crossbar output circuit for low power analog SNN inference with eNVM synapses

Joao Henrique Quintino Palhares; Yann Beilliard; Jury Sandrini; Franck Arnaud; Kevin Garello; Guillaume Prenat; Lorena Anghel; Fabien Alibart; Dominique Drouin; Philippe Galy

arXiv · 2305.16187

A tunable and versatile 28nm FD-SOI crossbar output circuit for low power analog SNN inference with eNVM synapses

Joao Henrique Quintino Palhares·Yann Beilliard·Jury Sandrini·Franck Arnaud·Kevin Garello·Guillaume Prenat·Lorena Anghel·Fabien Alibart·Dominique Drouin·Philippe Galy

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Abstract

In this work we report a study and a co-design methodology of an analog SNN crossbar output circuit designed in a 28nm FD-SOI technology node that comprises a tunable current attenuator and a leak-integrate and fire neurons that would enable the integration of emerging non-volatile memories (eNVMs) for synaptic arrays based on various technologies including phase change (PCRAM), oxide-based (OxRAM), spin transfer and spin orbit torque magnetic memories (STT, SOT-MRAM). Circuit SPICE simulation results and eNVM experimental data are used to showcase and estimate the neurons fan-in for each type of eNVM considering the technology constraints and design trade-offs that set its limits such as membrane capacitance and supply voltage, etc.

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Joao Henrique Quintino Palhares, Yann Beilliard, Jury Sandrini, Franck Arnaud, Kevin Garello, Guillaume Prenat, Lorena Anghel, Fabien Alibart, Dominique Drouin, Philippe Galy. 2023-05-25. A tunable and versatile 28nm FD-SOI crossbar output circuit for low power analog SNN inference with eNVM synapses. https://arxiv.org/abs/2305.16187

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