Biologically Plausible Ferroelectric Quasi-Leaky Integrate and Fire Neuron

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

doi:10.23919/VLSIT.2019.8776487

Biologically Plausible Ferroelectric Quasi-Leaky Integrate and Fire Neuron

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

24 Scopus citations

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 language	English
Title of host publication	2019 Symposium on VLSI Technology, VLSI Technology 2019 - Digest of Technical Papers
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	T140-T141
ISBN (Electronic)	9784863487178
DOIs	https://doi.org/10.23919/VLSIT.2019.8776487
State	Published - Jun 2019
Externally published	Yes
Event	39th Symposium on VLSI Technology, VLSI Technology 2019 - Kyoto, Japan Duration: 9 Jun 2019 → 14 Jun 2019

Publication series

Name	Digest of Technical Papers - Symposium on VLSI Technology
Volume	2019-June
ISSN (Print)	0743-1562

Conference

Conference	39th Symposium on VLSI Technology, VLSI Technology 2019
Country/Territory	Japan
City	Kyoto
Period	9/06/19 → 14/06/19

Bibliographical note

Publisher Copyright:
© 2019 The Japan Society of Applied Physics.

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10.23919/VLSIT.2019.8776487

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Dutta, S., Saha, A., Panda, P., Chakraborty, W., Gomez, J., Khanna, A., Gupta, S., 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 (pp. T140-T141). Article 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

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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, S, 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, 9/06/19. https://doi.org/10.23919/VLSIT.2019.8776487

Biologically Plausible Ferroelectric Quasi-Leaky Integrate and Fire Neuron. / Dutta, S.; Saha, A.; Panda, P. et al.
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 proceeding › Conference contribution › peer-review

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AB - 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 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). doi: 10.23919/VLSIT.2019.8776487

Biologically Plausible Ferroelectric Quasi-Leaky Integrate and Fire Neuron

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