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Title: Neuromorphic spintronics

Abstract

Neuromorphic computing uses brain-inspired principles to design circuits that can perform computational tasks with superior power efficiency to conventional computers. Approaches that use traditional electronic devices to create artificial neurons and synapses are, however, currently limited by the energy and area requirements of these components. Spintronic nanodevices, which exploit both the magnetic and electrical properties of electrons, can increase the energy efficiency and decrease the area of these circuits, and magnetic tunnel junctions are of particular interest as neuromorphic computing elements because they are compatible with standard integrated circuits and can support multiple functionalities. Here, we review the development of spintronic devices for neuromorphic computing. We examine how magnetic tunnel junctions can serve as synapses and neurons, and how magnetic textures, such as domain walls and skyrmions, can function as neurons. We also explore spintronics-based implementations of neuromorphic computing tasks, such as pattern recognition in an associative memory, and discuss the challenges that exist in scaling up these systems.

Authors:
ORCiD logo [1];  [1]; ORCiD logo [2];  [2]; ORCiD logo [3]; ORCiD logo [4]
+ Show Author Affiliations
  1. Univ. Paris-Saclay, Palaiseau (France)
  2. Purdue Univ., West Lafayette, IN (United States)
  3. Tohoku Univ., Sendai (Japan)
  4. National Inst. of Standards and Technology (NIST), Boulder, CO (United States)
Publication Date:
Research Org.:
Energy Frontier Research Centers (EFRC) (United States). Quantum Materials for Energy Efficient Neuromorphic Computing; Univ. of California, San Diego, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
OSTI Identifier:
1767684
Grant/Contract Number:  
SC0019273
Resource Type:
Accepted Manuscript
Journal Name:
Nature Electronics
Additional Journal Information:
Journal Volume: 3; Journal Issue: 7; Journal ID: ISSN 2520-1131
Publisher:
Springer Nature
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; bio-inspired; charge transport; magnetism and spin physics; quantum information science; mesoscale science; materials and chemistry by design; mesostructured materials; synthesis (novel materials); synthesis (predictive)

Citation Formats

Grollier, J., Querlioz, D., Camsari, K. Y., Everschor-Sitte, K., Fukami, S., and Stiles, M. D. Neuromorphic spintronics. United States: N. p., 2020. Web. doi:10.1038/s41928-019-0360-9.
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Grollier, J., Querlioz, D., Camsari, K. Y., Everschor-Sitte, K., Fukami, S., & Stiles, M. D. Neuromorphic spintronics. United States. https://doi.org/10.1038/s41928-019-0360-9
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Grollier, J., Querlioz, D., Camsari, K. Y., Everschor-Sitte, K., Fukami, S., and Stiles, M. D. Mon . "Neuromorphic spintronics". United States. https://doi.org/10.1038/s41928-019-0360-9. https://www.osti.gov/servlets/purl/1767684.
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@article{osti_1767684,
title = {Neuromorphic spintronics},
author = {Grollier, J. and Querlioz, D. and Camsari, K. Y. and Everschor-Sitte, K. and Fukami, S. and Stiles, M. D.},
abstractNote = {Neuromorphic computing uses brain-inspired principles to design circuits that can perform computational tasks with superior power efficiency to conventional computers. Approaches that use traditional electronic devices to create artificial neurons and synapses are, however, currently limited by the energy and area requirements of these components. Spintronic nanodevices, which exploit both the magnetic and electrical properties of electrons, can increase the energy efficiency and decrease the area of these circuits, and magnetic tunnel junctions are of particular interest as neuromorphic computing elements because they are compatible with standard integrated circuits and can support multiple functionalities. Here, we review the development of spintronic devices for neuromorphic computing. We examine how magnetic tunnel junctions can serve as synapses and neurons, and how magnetic textures, such as domain walls and skyrmions, can function as neurons. We also explore spintronics-based implementations of neuromorphic computing tasks, such as pattern recognition in an associative memory, and discuss the challenges that exist in scaling up these systems.},
doi = {10.1038/s41928-019-0360-9},
journal = {Nature Electronics},
number = 7,
volume = 3,
place = {United States},
year = {Mon Mar 02 00:00:00 EST 2020},
month = {Mon Mar 02 00:00:00 EST 2020}
}
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