Discrete Anomalous Hall Resistance-based Quantized Convolutional Neural Network

Aijaz H. Lone; Xuecui Zou; Hanrui Li; Nazek El-Atab; Hossein Fariborzi

doi:10.1109/INTERMAGShortPapers58606.2023.10228622

Discrete Anomalous Hall Resistance-based Quantized Convolutional Neural Network

Aijaz H. Lone^*, Xuecui Zou, Hanrui Li, Nazek El-Atab, Hossein Fariborzi

^*Corresponding author for this work

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

Abstract

Spintronic devices have shown promise for energy-efficient storage and neuromorphic computing. In this abstract, we present the realization of a spintronic device exhibiting discrete anomalous Hall resistance states. We attribute this discrete resistance behavior to the magnetic domain wall pinning and depinning and gradual switching of different magnetic layers. The number of resistance states is a function of the temperature. Furthermore, this discrete resistance behavior of the device allows us to employ these resistance states as weights in a quantized convolutional neural network. The network is trained and tested on the CIFAR-10 data set and the system achieves an accuracy of around 86.95%.

Original language	English (US)
Title of host publication	2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350338362
DOIs	https://doi.org/10.1109/INTERMAGShortPapers58606.2023.10228622
State	Published - 2023
Event	2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Sendai, Japan Duration: May 15 2023 → May 19 2023

Publication series

Name	2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings

Conference

Conference	2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023
Country/Territory	Japan
City	Sendai
Period	05/15/23 → 05/19/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Anomalous Hall effect
Discrete resistive states
Domain wall pinning
neuromorphic computing
Spintronics

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering
Mechanical Engineering
Electronic, Optical and Magnetic Materials
Instrumentation

Access to Document

10.1109/INTERMAGShortPapers58606.2023.10228622

Cite this

Lone, A. H., Zou, X., Li, H., El-Atab, N., & Fariborzi, H. (2023). Discrete Anomalous Hall Resistance-based Quantized Convolutional Neural Network. In 2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings (2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INTERMAGShortPapers58606.2023.10228622

Lone, Aijaz H. ; Zou, Xuecui ; Li, Hanrui et al. / Discrete Anomalous Hall Resistance-based Quantized Convolutional Neural Network. 2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings).

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title = "Discrete Anomalous Hall Resistance-based Quantized Convolutional Neural Network",

abstract = "Spintronic devices have shown promise for energy-efficient storage and neuromorphic computing. In this abstract, we present the realization of a spintronic device exhibiting discrete anomalous Hall resistance states. We attribute this discrete resistance behavior to the magnetic domain wall pinning and depinning and gradual switching of different magnetic layers. The number of resistance states is a function of the temperature. Furthermore, this discrete resistance behavior of the device allows us to employ these resistance states as weights in a quantized convolutional neural network. The network is trained and tested on the CIFAR-10 data set and the system achieves an accuracy of around 86.95%.",

keywords = "Anomalous Hall effect, Discrete resistive states, Domain wall pinning, neuromorphic computing, Spintronics",

author = "Lone, {Aijaz H.} and Xuecui Zou and Hanrui Li and Nazek El-Atab and Hossein Fariborzi",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 ; Conference date: 15-05-2023 Through 19-05-2023",

year = "2023",

doi = "10.1109/INTERMAGShortPapers58606.2023.10228622",

language = "English (US)",

series = "2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings",

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

booktitle = "2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings",

address = "United States",

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Lone, AH , Zou, X , Li, H , El-Atab, N & Fariborzi, H 2023, Discrete Anomalous Hall Resistance-based Quantized Convolutional Neural Network. in 2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings. 2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023, Sendai, Japan, 05/15/23. https://doi.org/10.1109/INTERMAGShortPapers58606.2023.10228622

Discrete Anomalous Hall Resistance-based Quantized Convolutional Neural Network. / Lone, Aijaz H.; Zou, Xuecui ; Li, Hanrui et al.
2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings).

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

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T1 - Discrete Anomalous Hall Resistance-based Quantized Convolutional Neural Network

AU - Lone, Aijaz H.

AU - Zou, Xuecui

AU - Li, Hanrui

AU - El-Atab, Nazek

AU - Fariborzi, Hossein

PY - 2023

Y1 - 2023

N2 - Spintronic devices have shown promise for energy-efficient storage and neuromorphic computing. In this abstract, we present the realization of a spintronic device exhibiting discrete anomalous Hall resistance states. We attribute this discrete resistance behavior to the magnetic domain wall pinning and depinning and gradual switching of different magnetic layers. The number of resistance states is a function of the temperature. Furthermore, this discrete resistance behavior of the device allows us to employ these resistance states as weights in a quantized convolutional neural network. The network is trained and tested on the CIFAR-10 data set and the system achieves an accuracy of around 86.95%.

AB - Spintronic devices have shown promise for energy-efficient storage and neuromorphic computing. In this abstract, we present the realization of a spintronic device exhibiting discrete anomalous Hall resistance states. We attribute this discrete resistance behavior to the magnetic domain wall pinning and depinning and gradual switching of different magnetic layers. The number of resistance states is a function of the temperature. Furthermore, this discrete resistance behavior of the device allows us to employ these resistance states as weights in a quantized convolutional neural network. The network is trained and tested on the CIFAR-10 data set and the system achieves an accuracy of around 86.95%.

KW - Anomalous Hall effect

KW - Discrete resistive states

KW - Domain wall pinning

KW - neuromorphic computing

KW - Spintronics

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U2 - 10.1109/INTERMAGShortPapers58606.2023.10228622

DO - 10.1109/INTERMAGShortPapers58606.2023.10228622

M3 - Conference contribution

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T3 - 2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings

BT - 2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023

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Lone AH , Zou X , Li H , El-Atab N, Fariborzi H. Discrete Anomalous Hall Resistance-based Quantized Convolutional Neural Network. In 2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023 - Proceedings). doi: 10.1109/INTERMAGShortPapers58606.2023.10228622

Discrete Anomalous Hall Resistance-based Quantized Convolutional Neural Network

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