Ultra-fast data-mining hardware architecture based on stochastic computing.

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.

SUBMITTER: Morro A 

PROVIDER: S-EPMC4425430 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature