Shashank Misra, Leslie C. Bland, Suma G. Cardwell, Jean Anne C. Incorvia, Conrad D. James, Andrew D. Kent, Catherine D. Schuman, J. Darby Smith, and James B. Aimone

November, 2022

Advanced Materials

https://onlinelibrary.wiley.com/doi/full/10.1002/adma.202204569

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Abstract

The brain has effectively proven a powerful inspiration for the development of computing architectures in which processing is tightly integrated with memory, communication is event-driven, and analog computation can be performed at scale. These neuromorphic systems increasingly show an ability to improve the efficiency and speed of scientific computing and artificial intelligence applications. Herein, it is proposed that the brain's ubiquitous stochasticity represents an additional source of inspiration for expanding the reach of neuromorphic computing to probabilistic applications. To date, many efforts exploring probabilistic computing have focused primarily on one scale of the microelectronics stack, such as implementing probabilistic algorithms on deterministic hardware or developing probabilistic devices and circuits with the expectation that they will be leveraged by eventual probabilistic architectures. A co-design vision is described by which large numbers of devices, such as magnetic tunnel junctions and tunnel diodes, can be operated in a stochastic regime and incorporated into a scalable neuromorphic architecture that can impact a number of probabilistic computing applications, such as Monte Carlo simulations and Bayesian neural networks. Finally, a framework is presented to categorize increasingly advanced hardware-based probabilistic computing technologies.

Citation Information

Text

author      S. Misra and L. C. Bland and S. G. Cardwell and J. A. C. Incorvia and C. D. Jamesand A. D. Kent and C. D. Schuman and J. D. Smith and J. B. Aimone
title       Probabilistic Neural Computing with Stochastic Devices
journal     Advanced Materials
year        2022
url         https://onlinelibrary.wiley.com/doi/full/10.1002/adma.202204569
doi         10.1002/adma.202204569

Bibtex

@ARTICLE{mbc:22:pnc,
    author = "S. Misra and L. C. Bland and S. G. Cardwell and J. A. C. Incorvia and C. D. Jamesand A. D. Kent and C. D. Schuman and J. D. Smith and J. B. Aimone",
    title = "Probabilistic Neural Computing with Stochastic Devices",
    journal = "Advanced Materials",
    year = "2022",
    url = "https://onlinelibrary.wiley.com/doi/full/10.1002/adma.202204569",
    doi = "10.1002/adma.202204569"
}