Live Demonstration: Unlocking the Potential of Two-Point Neuronal Cells for Energy-Efficient Training of Deep Networks

Ahsan Adeel; Adewale Adetomi; W. A. Phillips; Mohsin Raza; Khubaib Ahmed; Amir Hussain; Tughrul Arslan

doi:10.1109/ISCAS46773.2023.10181836

Live Demonstration: Unlocking the Potential of Two-Point Neuronal Cells for Energy-Efficient Training of Deep Networks

Ahsan Adeel^*
, Adewale Adetomi
, W. A. Phillips
, Mohsin Raza
, Khubaib Ahmed
, Amir Hussain
, Tughrul Arslan

^*Corresponding author for this work

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

Abstract

This paper is the first live demonstration of the transformative computational potential of context-sensitive two-point layer 5 pyramidal cells (L5PCs). We will showcase a Multi-Processor System on Chip (MPSoC)-based implementation of a biologically plausible L5PC-driven deep neural network (DNN), termed multisensory cooperative computing (MCC). This will be shown to effectively process heterogeneous real-world audio-visual data consuming far less energy compared to state-of-the-art 'point' neuron-driven DNNs. Our approach opens new cross-disciplinary avenues for future on-chip DNN training implementations and posits a radical shift in current neuromorphic computing paradigms.

Original language	English
Title of host publication	ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665451093
DOIs	https://doi.org/10.1109/ISCAS46773.2023.10181836
State	Published - 2023
Externally published	Yes
Event	56th IEEE International Symposium on Circuits and Systems, ISCAS 2023 - Monterey, United States Duration: 21 May 2023 → 25 May 2023

Publication series

Name	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	2023-May
ISSN (Print)	0271-4310

Conference

Conference	56th IEEE International Symposium on Circuits and Systems, ISCAS 2023
Country/Territory	United States
City	Monterey
Period	21/05/23 → 25/05/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

audiovisual speech processing
deep learning
on-chip training
two-point neurons

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/ISCAS46773.2023.10181836

Cite this

Adeel, A., Adetomi, A., Phillips, W. A., Raza, M., Ahmed, K., Hussain, A., & Arslan, T. (2023). Live Demonstration: Unlocking the Potential of Two-Point Neuronal Cells for Energy-Efficient Training of Deep Networks. In ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 2023-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCAS46773.2023.10181836

Adeel, Ahsan ; Adetomi, Adewale ; Phillips, W. A. et al. / Live Demonstration : Unlocking the Potential of Two-Point Neuronal Cells for Energy-Efficient Training of Deep Networks. ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings - IEEE International Symposium on Circuits and Systems).

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title = "Live Demonstration: Unlocking the Potential of Two-Point Neuronal Cells for Energy-Efficient Training of Deep Networks",

abstract = "This paper is the first live demonstration of the transformative computational potential of context-sensitive two-point layer 5 pyramidal cells (L5PCs). We will showcase a Multi-Processor System on Chip (MPSoC)-based implementation of a biologically plausible L5PC-driven deep neural network (DNN), termed multisensory cooperative computing (MCC). This will be shown to effectively process heterogeneous real-world audio-visual data consuming far less energy compared to state-of-the-art 'point' neuron-driven DNNs. Our approach opens new cross-disciplinary avenues for future on-chip DNN training implementations and posits a radical shift in current neuromorphic computing paradigms.",

keywords = "audiovisual speech processing, deep learning, on-chip training, two-point neurons",

author = "Ahsan Adeel and Adewale Adetomi and Phillips, \{W. A.\} and Mohsin Raza and Khubaib Ahmed and Amir Hussain and Tughrul Arslan",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 56th IEEE International Symposium on Circuits and Systems, ISCAS 2023 ; Conference date: 21-05-2023 Through 25-05-2023",

year = "2023",

doi = "10.1109/ISCAS46773.2023.10181836",

language = "English",

series = "Proceedings - IEEE International Symposium on Circuits and Systems",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings",

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Adeel, A, Adetomi, A, Phillips, WA, Raza, M, Ahmed, K, Hussain, A & Arslan, T 2023, Live Demonstration: Unlocking the Potential of Two-Point Neuronal Cells for Energy-Efficient Training of Deep Networks. in ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings. Proceedings - IEEE International Symposium on Circuits and Systems, vol. 2023-May, Institute of Electrical and Electronics Engineers Inc., 56th IEEE International Symposium on Circuits and Systems, ISCAS 2023, Monterey, United States, 21/05/23. https://doi.org/10.1109/ISCAS46773.2023.10181836

Live Demonstration: Unlocking the Potential of Two-Point Neuronal Cells for Energy-Efficient Training of Deep Networks. / Adeel, Ahsan; Adetomi, Adewale; Phillips, W. A. et al.
ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (Proceedings - IEEE International Symposium on Circuits and Systems; Vol. 2023-May).

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

TY - GEN

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T2 - 56th IEEE International Symposium on Circuits and Systems, ISCAS 2023

AU - Adeel, Ahsan

AU - Adetomi, Adewale

AU - Phillips, W. A.

AU - Raza, Mohsin

AU - Ahmed, Khubaib

AU - Hussain, Amir

AU - Arslan, Tughrul

PY - 2023

Y1 - 2023

N2 - This paper is the first live demonstration of the transformative computational potential of context-sensitive two-point layer 5 pyramidal cells (L5PCs). We will showcase a Multi-Processor System on Chip (MPSoC)-based implementation of a biologically plausible L5PC-driven deep neural network (DNN), termed multisensory cooperative computing (MCC). This will be shown to effectively process heterogeneous real-world audio-visual data consuming far less energy compared to state-of-the-art 'point' neuron-driven DNNs. Our approach opens new cross-disciplinary avenues for future on-chip DNN training implementations and posits a radical shift in current neuromorphic computing paradigms.

AB - This paper is the first live demonstration of the transformative computational potential of context-sensitive two-point layer 5 pyramidal cells (L5PCs). We will showcase a Multi-Processor System on Chip (MPSoC)-based implementation of a biologically plausible L5PC-driven deep neural network (DNN), termed multisensory cooperative computing (MCC). This will be shown to effectively process heterogeneous real-world audio-visual data consuming far less energy compared to state-of-the-art 'point' neuron-driven DNNs. Our approach opens new cross-disciplinary avenues for future on-chip DNN training implementations and posits a radical shift in current neuromorphic computing paradigms.

KW - audiovisual speech processing

KW - deep learning

KW - on-chip training

KW - two-point neurons

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DO - 10.1109/ISCAS46773.2023.10181836

M3 - Conference contribution

AN - SCOPUS:85167728042

T3 - Proceedings - IEEE International Symposium on Circuits and Systems

BT - ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 21 May 2023 through 25 May 2023

ER -

Adeel A, Adetomi A, Phillips WA, Raza M, Ahmed K, Hussain A et al. Live Demonstration: Unlocking the Potential of Two-Point Neuronal Cells for Energy-Efficient Training of Deep Networks. In ISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. (Proceedings - IEEE International Symposium on Circuits and Systems). doi: 10.1109/ISCAS46773.2023.10181836

Live Demonstration: Unlocking the Potential of Two-Point Neuronal Cells for Energy-Efficient Training of Deep Networks

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this