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Introduction to noise-resilient computing

Noise abatement is the key problem of small-scaled circuit design. New computational paradigms are needed -- as these circuits shrink, they become very vulnerable to noise and soft errors. In this lecture, we present a probabilistic computation framework for improving the resiliency of logic gates a...

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Detalles Bibliográficos
Autores principales: Yanushkevich, Svetlana N, Kasai, Seiya, Tangim, Golam
Lenguaje:eng
Publicado: Morgan & Claypool Publ. 2013
Materias:
Acceso en línea:http://cds.cern.ch/record/2122819
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author Yanushkevich, Svetlana N
Kasai, Seiya
Tangim, Golam
author_facet Yanushkevich, Svetlana N
Kasai, Seiya
Tangim, Golam
author_sort Yanushkevich, Svetlana N
collection CERN
description Noise abatement is the key problem of small-scaled circuit design. New computational paradigms are needed -- as these circuits shrink, they become very vulnerable to noise and soft errors. In this lecture, we present a probabilistic computation framework for improving the resiliency of logic gates and circuits under random conditions induced by voltage or current fluctuation. Among many probabilistic techniques for modeling such devices, only a few models satisfy the requirements of efficient hardware implementation -- specifically, Boltzman machines and Markov Random Field (MRF) models. These
id cern-2122819
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2013
publisher Morgan & Claypool Publ.
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spelling cern-21228192021-04-21T19:52:20Zhttp://cds.cern.ch/record/2122819engYanushkevich, Svetlana NKasai, SeiyaTangim, GolamIntroduction to noise-resilient computingEngineeringNoise abatement is the key problem of small-scaled circuit design. New computational paradigms are needed -- as these circuits shrink, they become very vulnerable to noise and soft errors. In this lecture, we present a probabilistic computation framework for improving the resiliency of logic gates and circuits under random conditions induced by voltage or current fluctuation. Among many probabilistic techniques for modeling such devices, only a few models satisfy the requirements of efficient hardware implementation -- specifically, Boltzman machines and Markov Random Field (MRF) models. TheseMorgan & Claypool Publ.oai:cds.cern.ch:21228192013
spellingShingle Engineering
Yanushkevich, Svetlana N
Kasai, Seiya
Tangim, Golam
Introduction to noise-resilient computing
title Introduction to noise-resilient computing
title_full Introduction to noise-resilient computing
title_fullStr Introduction to noise-resilient computing
title_full_unstemmed Introduction to noise-resilient computing
title_short Introduction to noise-resilient computing
title_sort introduction to noise-resilient computing
topic Engineering
url http://cds.cern.ch/record/2122819
work_keys_str_mv AT yanushkevichsvetlanan introductiontonoiseresilientcomputing
AT kasaiseiya introductiontonoiseresilientcomputing
AT tangimgolam introductiontonoiseresilientcomputing