Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference

Abstract Probabilistic inference from real-time input data is becoming increasingly popular and may be one of the potential pathways at enabling cognitive intelligence. As a matter of fact, preliminary research has revealed that stochastic functionalities also underlie the spiking behavior of neuron...

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Autores principales:	Yong Shim, Shuhan Chen, Abhronil Sengupta, Kaushik Roy
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d15416ec63bb42e59eee4b750f36ada8
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spelling	oai:doaj.org-article:d15416ec63bb42e59eee4b750f36ada82021-12-02T11:53:00ZStochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference10.1038/s41598-017-14240-z2045-2322https://doaj.org/article/d15416ec63bb42e59eee4b750f36ada82017-10-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-14240-zhttps://doaj.org/toc/2045-2322Abstract Probabilistic inference from real-time input data is becoming increasingly popular and may be one of the potential pathways at enabling cognitive intelligence. As a matter of fact, preliminary research has revealed that stochastic functionalities also underlie the spiking behavior of neurons in cortical microcircuits of the human brain. In tune with such observations, neuromorphic and other unconventional computing platforms have recently started adopting the usage of computational units that generate outputs probabilistically, depending on the magnitude of the input stimulus. In this work, we experimentally demonstrate a spintronic device that offers a direct mapping to the functionality of such a controllable stochastic switching element. We show that the probabilistic switching of Ta/CoFeB/MgO heterostructures in presence of spin-orbit torque and thermal noise can be harnessed to enable probabilistic inference in a plethora of unconventional computing scenarios. This work can potentially pave the way for hardware that directly mimics the computational units of Bayesian inference.Yong ShimShuhan ChenAbhronil SenguptaKaushik RoyNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-9 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yong Shim Shuhan Chen Abhronil Sengupta Kaushik Roy Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference
description	Abstract Probabilistic inference from real-time input data is becoming increasingly popular and may be one of the potential pathways at enabling cognitive intelligence. As a matter of fact, preliminary research has revealed that stochastic functionalities also underlie the spiking behavior of neurons in cortical microcircuits of the human brain. In tune with such observations, neuromorphic and other unconventional computing platforms have recently started adopting the usage of computational units that generate outputs probabilistically, depending on the magnitude of the input stimulus. In this work, we experimentally demonstrate a spintronic device that offers a direct mapping to the functionality of such a controllable stochastic switching element. We show that the probabilistic switching of Ta/CoFeB/MgO heterostructures in presence of spin-orbit torque and thermal noise can be harnessed to enable probabilistic inference in a plethora of unconventional computing scenarios. This work can potentially pave the way for hardware that directly mimics the computational units of Bayesian inference.
format	article
author	Yong Shim Shuhan Chen Abhronil Sengupta Kaushik Roy
author_facet	Yong Shim Shuhan Chen Abhronil Sengupta Kaushik Roy
author_sort	Yong Shim
title	Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference
title_short	Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference
title_full	Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference
title_fullStr	Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference
title_full_unstemmed	Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference
title_sort	stochastic spin-orbit torque devices as elements for bayesian inference
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/d15416ec63bb42e59eee4b750f36ada8
work_keys_str_mv	AT yongshim stochasticspinorbittorquedevicesaselementsforbayesianinference AT shuhanchen stochasticspinorbittorquedevicesaselementsforbayesianinference AT abhronilsengupta stochasticspinorbittorquedevicesaselementsforbayesianinference AT kaushikroy stochasticspinorbittorquedevicesaselementsforbayesianinference
_version_	1718394954732011520

Stochastic Spin-Orbit Torque Devices as Elements for Bayesian Inference

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