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

Antoni Morro | Zendy; Vincent Canals | Zendy; Antoni Oliver | Zendy; Miquel L. Alomar | Zendy; Josep L. Rosselló | Zendy

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

Author(s) -

Antoni Morro,

Vincent Canals,

Antoni Oliver,

Miquel L. Alomar,

Josep L. Rosselló

Publication year - 2015

Publication title -

plos one

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.99

H-Index - 332

ISSN - 1932-6203

DOI - 10.1371/journal.pone.0124176

Subject(s) - computer science , probabilistic logic , hardware architecture , process (computing) , architecture , implementation , stochastic computing , computer architecture , computer hardware , data mining , computer engineering , parallel computing , pattern recognition (psychology) , artificial intelligence , software , algorithm , computation , software engineering , programming language , art , visual arts

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.

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