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dc.contributor.authorNaous, Rawan
dc.contributor.authorSiemon, Anne
dc.contributor.authorSchulten, Michael
dc.contributor.authorAlahmadi, Hamzah
dc.contributor.authorKindsmüller, Andreas
dc.contributor.authorLübben, Michael
dc.contributor.authorHeittmann, Arne
dc.contributor.authorWaser, Rainer
dc.contributor.authorSalama, Khaled Nabil
dc.contributor.authorMenzel, Stephan
dc.date.accessioned2021-02-21T07:29:34Z
dc.date.available2021-02-21T07:29:34Z
dc.date.issued2021-02-19
dc.date.submitted2020-02-04
dc.identifier.citationNaous, R., Siemon, A., Schulten, M., Alahmadi, H., Kindsmüller, A., Lübben, M., … Menzel, S. (2021). Theory and experimental verification of configurable computing with stochastic memristors. Scientific Reports, 11(1). doi:10.1038/s41598-021-83382-y
dc.identifier.issn2045-2322
dc.identifier.pmid33603012
dc.identifier.doi10.1038/s41598-021-83382-y
dc.identifier.urihttp://hdl.handle.net/10754/667516
dc.description.abstractThe inevitable variability within electronic devices causes strict constraints on operation, reliability and scalability of the circuit design. However, when a compromise arises among the different performance metrics, area, time and energy, variability then loosens the tight requirements and allows for further savings in an alternative design scope. To that end, unconventional computing approaches are revived in the form of approximate computing, particularly tuned for resource-constrained mobile computing. In this paper, a proof-of-concept of the approximate computing paradigm using memristors is demonstrated. Stochastic memristors are used as the main building block of probabilistic logic gates. As will be shown in this paper, the stochasticity of memristors' switching characteristics is tightly bound to the supply voltage and hence to power consumption. By scaling of the supply voltage to appropriate levels stochasticity gets increased. In order to guide the design process of approximate circuits based on memristors a realistic device model needs to be elaborated with explicit emphasis of the probabilistic switching behavior. Theoretical formulation, probabilistic analysis, and simulation of the underlying logic circuits and operations are introduced. Moreover, the expected output behavior is verified with the experimental measurements of valence change memory cells. Hence, it is shown how the precision of the output is varied for the sake of the attainable gains at different levels of available design metrics. This approach represents the first proposition along with physical verification and mapping to real devices that combines stochastic memristors into unconventional computing approaches.
dc.description.sponsorshipThis work is supported in parts by the DFG (Deutsche Forschungsgemeinschaft) under Grant SFB 917 Nanoswitches.
dc.description.sponsorshipOpen Access funding enabled and organized by Projekt DEAL.
dc.publisherSpringer Science and Business Media LLC
dc.relation.urlhttp://www.nature.com/articles/s41598-021-83382-y
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. Te images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titleTheory and experimental verification of configurable computing with stochastic memristors.
dc.typeArticle
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.identifier.journalScientific reports
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionDepartment of Electrical Engineering and Computer Science, University of California Berkeley, Berkeley, CA, USA.
dc.contributor.institution(PGI‑7), Forschungszentrum Jülich GmbH, Jülich, Germany.
dc.contributor.institutionInstitut für Werkstofe der Elektrotechnik II (IWE II), RWTH Aachen University, Aachen, Germany.
dc.contributor.institutionJARA - Fundamentals for Future Information Technology, Jülich, Germany.
dc.contributor.institutionPeter Grünberg Institut 10 (PGI‑10), Forschungszentrum Jülich GmbH, Jülich, Germany.
dc.contributor.institutionPeter Grünberg Institut .
dc.identifier.volume11
dc.identifier.issue1
kaust.personNaous, Rawan
dc.date.accepted2021-02-02
refterms.dateFOA2021-02-21T07:30:56Z


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This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. Te images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Except where otherwise noted, this item's license is described as This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. Te images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.