Biologically Plausible Ferroelectric Quasi-Leaky Integrate and Fire Neuron

S. Dutta, A. Saha, P. Panda, W. Chakraborty, J. Gomez, A. Khanna, Sumeet Kumar Gupta, K. Roy, S. Datta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Biologically plausible mechanism like homeostasis compliments Hebbian learning to allow unsupervised learning in spiking neural networks [1]. In this work, we propose a novel ferroelectric-based quasi-LIF neuron that induces intrinsic homeostasis. We experimentally characterize and perform phase-field simulations to delineate the non-trivial transient polarization relaxation mechanism associated with multi-domain interaction in poly-crystalline ferroelectric, such as Zr doped HfO2, that underlines the Q-LIF behavior. Network level simulations with the Q-LIF neuron model exhibits a 2.3x reduction in firing rate compared to traditional LIF neuron while maintaining iso-accuracy of 84-85% across varying network sizes. Such an energy-efficient hardware for spiking neuron can enable ultra-low power data processing in energy constrained environments suitable for edge-intelligence.

Original languageEnglish (US)
Title of host publication2019 Symposium on VLSI Technology, VLSI Technology 2019 - Digest of Technical Papers
PublisherInstitute of Electrical and Electronics Engineers Inc.
PagesT140-T141
ISBN (Electronic)9784863487178
DOIs
StatePublished - Jun 1 2019
Event39th Symposium on VLSI Technology, VLSI Technology 2019 - Kyoto, Japan
Duration: Jun 9 2019Jun 14 2019

Publication series

NameDigest of Technical Papers - Symposium on VLSI Technology
Volume2019-June
ISSN (Print)0743-1562

Conference

Conference39th Symposium on VLSI Technology, VLSI Technology 2019
CountryJapan
CityKyoto
Period6/9/196/14/19

Fingerprint

Neurons
Ferroelectric materials
Fires
Unsupervised learning
Polarization
Crystalline materials
Neural networks
Hardware

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Dutta, S., Saha, A., Panda, P., Chakraborty, W., Gomez, J., Khanna, A., ... Datta, S. (2019). Biologically Plausible Ferroelectric Quasi-Leaky Integrate and Fire Neuron. In 2019 Symposium on VLSI Technology, VLSI Technology 2019 - Digest of Technical Papers (pp. T140-T141). [8776487] (Digest of Technical Papers - Symposium on VLSI Technology; Vol. 2019-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/VLSIT.2019.8776487
Dutta, S. ; Saha, A. ; Panda, P. ; Chakraborty, W. ; Gomez, J. ; Khanna, A. ; Gupta, Sumeet Kumar ; Roy, K. ; Datta, S. / Biologically Plausible Ferroelectric Quasi-Leaky Integrate and Fire Neuron. 2019 Symposium on VLSI Technology, VLSI Technology 2019 - Digest of Technical Papers. Institute of Electrical and Electronics Engineers Inc., 2019. pp. T140-T141 (Digest of Technical Papers - Symposium on VLSI Technology).
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abstract = "Biologically plausible mechanism like homeostasis compliments Hebbian learning to allow unsupervised learning in spiking neural networks [1]. In this work, we propose a novel ferroelectric-based quasi-LIF neuron that induces intrinsic homeostasis. We experimentally characterize and perform phase-field simulations to delineate the non-trivial transient polarization relaxation mechanism associated with multi-domain interaction in poly-crystalline ferroelectric, such as Zr doped HfO2, that underlines the Q-LIF behavior. Network level simulations with the Q-LIF neuron model exhibits a 2.3x reduction in firing rate compared to traditional LIF neuron while maintaining iso-accuracy of 84-85{\%} across varying network sizes. Such an energy-efficient hardware for spiking neuron can enable ultra-low power data processing in energy constrained environments suitable for edge-intelligence.",
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Dutta, S, Saha, A, Panda, P, Chakraborty, W, Gomez, J, Khanna, A, Gupta, SK, Roy, K & Datta, S 2019, Biologically Plausible Ferroelectric Quasi-Leaky Integrate and Fire Neuron. in 2019 Symposium on VLSI Technology, VLSI Technology 2019 - Digest of Technical Papers., 8776487, Digest of Technical Papers - Symposium on VLSI Technology, vol. 2019-June, Institute of Electrical and Electronics Engineers Inc., pp. T140-T141, 39th Symposium on VLSI Technology, VLSI Technology 2019, Kyoto, Japan, 6/9/19. https://doi.org/10.23919/VLSIT.2019.8776487

Biologically Plausible Ferroelectric Quasi-Leaky Integrate and Fire Neuron. / Dutta, S.; Saha, A.; Panda, P.; Chakraborty, W.; Gomez, J.; Khanna, A.; Gupta, Sumeet Kumar; Roy, K.; Datta, S.

2019 Symposium on VLSI Technology, VLSI Technology 2019 - Digest of Technical Papers. Institute of Electrical and Electronics Engineers Inc., 2019. p. T140-T141 8776487 (Digest of Technical Papers - Symposium on VLSI Technology; Vol. 2019-June).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Dutta S, Saha A, Panda P, Chakraborty W, Gomez J, Khanna A et al. Biologically Plausible Ferroelectric Quasi-Leaky Integrate and Fire Neuron. In 2019 Symposium on VLSI Technology, VLSI Technology 2019 - Digest of Technical Papers. Institute of Electrical and Electronics Engineers Inc. 2019. p. T140-T141. 8776487. (Digest of Technical Papers - Symposium on VLSI Technology). https://doi.org/10.23919/VLSIT.2019.8776487