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28 September 2023 Neural networks three ways: unlocking novel computing schemes using magnetic tunnel junction stochasticity
Matthew W. Daniels, William A. Borders, Nitin Prasad, Advait Madhavan, Sidra Gibeault, Temitayo Adeyeye, Liam Pocher, Lei Wan, Michael Tran, Jordan A. Katine, Daniel Lathrop, Brian Hoskins, Tiffany Santos, Patrick Braganca, Mark D. Stiles, Jabez J. McClelland
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Proceedings Volume 12656, Spintronics XVI; 126560B (2023) https://doi.org/10.1117/12.2682099
Event: SPIE Nanoscience + Engineering, 2023, San Diego, California, United States
Abstract
Due to their interesting physical properties, myriad operational regimes, small size, and industrial fabrication maturity, magnetic tunnel junctions are uniquely suited for unlocking novel computing schemes for in-hardware neuromorphic computing. In this paper, we focus on the stochastic response of magnetic tunnel junctions, illustrating three different ways in which the probabilistic response of a device can be used to achieve useful neuromorphic computing power.
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(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Matthew W. Daniels, William A. Borders, Nitin Prasad, Advait Madhavan, Sidra Gibeault, Temitayo Adeyeye, Liam Pocher, Lei Wan, Michael Tran, Jordan A. Katine, Daniel Lathrop, Brian Hoskins, Tiffany Santos, Patrick Braganca, Mark D. Stiles, and Jabez J. McClelland "Neural networks three ways: unlocking novel computing schemes using magnetic tunnel junction stochasticity", Proc. SPIE 12656, Spintronics XVI, 126560B (28 September 2023); https://doi.org/10.1117/12.2682099
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KEYWORDS
Stochastic processes
Magnetic tunnel junctions
Neural networks
Magnetism
Computer architecture
Resistors
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