Ultra-Fast Data-Mining Hardware Architecture Based on Stochastic Computing

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dc.contributor.author Morro, Antoni
dc.contributor.author Canals, Vincent
dc.contributor.author Oliver, Antoni
dc.contributor.author Alomar Barceló, Miquel L.
dc.contributor.author Rosselló, Josep L.
dc.date.accessioned 2015-07-06T10:16:38Z
dc.date.available 2015-07-06T10:16:38Z
dc.date.issued 2015-05-08
dc.identifier.citation 1932-6203
dc.identifier.uri http://hdl.handle.net/11201/1164
dc.description.abstract Minimal hardware implementations able to cope with the processing of large amounts of data in reasonable times are highly desired in our information-driven society. In this work we review the application of stochastic computing to probabilistic-based pattern-recognition analysis of huge database sets. The proposed technique consists in the hardware implementation of a parallel architecture implementing a similarity search of data with respect to different pre-stored categories. We design pulse-based stochastic-logic blocks to obtain an efficient pattern recognition system. The proposed architecture speeds up the screening process of huge databases by a factor of 7 when compared to a conventional digital implementation using the same hardware area.
dc.language.iso eng
dc.publisher Public Library of Science
dc.relation.isformatof Reproducció del document publicat a: http://dx.doi.org/10.1371/journal.pone.0124176
dc.relation.ispartof Plos One, 2015
dc.rights cc-by (c) Morro, Antoni et al., 2015
dc.rights.uri http://creativecommons.org/licenses/by/3.0/es
dc.title Ultra-Fast Data-Mining Hardware Architecture Based on Stochastic Computing
dc.type info:eu-repo/semantics/article
dc.type info:eu-repo/semantics/publishedVersion
dc.date.updated 2015-07-06T10:16:39Z
dc.rights.accessRights info:eu-repo/semantics/openAccess

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cc-by (c) Morro, Antoni et al., 2015 Except where otherwise noted, this item's license is described as cc-by (c) Morro, Antoni et al., 2015

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