A full-parallel implementation of Self-Organizing Maps on hardware.

Autor: Dias LA; Centre for Cyber Security and Privacy, School of Computer Science - University of Birmingham, Birmingham, United Kingdom. Electronic address: l.a.dias@bham.ac.uk., Damasceno AMP; Laboratory of Machine Learning and Intelligent Instrumentation, IMD/nPITI - Federal University of Rio Grande do Norte, Natal, Brazil. Electronic address: augustomatheuss@ufrn.edu.br., Gaura E; Centre for Data Science, Faculty of Engineering, Environment and Computing - Coventry University, Coventry, United Kingdom. Electronic address: csx216@coventry.ac.uk., Fernandes MAC; Laboratory of Machine Learning and Intelligent Instrumentation, IMD/nPITI - Federal University of Rio Grande do Norte, Natal, Brazil; Department of Computer and Automation Engineering - Federal University of Rio Grande do Norte, Natal, Brazil. Electronic address: mfernandes@dca.ufrn.br.
Jazyk: angličtina
Zdroj: Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2021 Nov; Vol. 143, pp. 818-827. Date of Electronic Publication: 2021 May 21.
DOI: 10.1016/j.neunet.2021.05.021
Abstrakt: Self-Organizing Maps (SOMs) are extensively used for data clustering and dimensionality reduction. However, if applications are to fully benefit from SOM based techniques, high-speed processing is demanding, given that data tends to be both highly dimensional and yet "big". Hence, a fully parallel architecture for the SOM is introduced to optimize the system's data processing time. Unlike most literature approaches, the architecture proposed here does not contain sequential steps - a common limiting factor for processing speed. The architecture was validated on FPGA and evaluated concerning hardware throughput and the use of resources. Comparisons to the state of the art show a speedup of 8.91× over a partially serial implementation, using less than 15% of hardware resources available. Thus, the method proposed here points to a hardware architecture that will not be obsolete quickly.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2021 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
Externí odkaz: