Using low-power platforms for Evolutionary Multi-Objective Optimization algorithms

Nowadays, the application of Evolutionary Multi-Objective Optimization (EMO) algorithms in real-time systems receives considerable interest. In this context, the energy efficiency of computational systems is of paramount relevance. Recently, the use of embedded systems based on heterogeneous (CPU + ...

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Veröffentlicht in:	The Journal of supercomputing Jg. 73; H. 1; S. 302 - 315
Hauptverfasser:	Moreno, J. J., Ortega, G., Filatovas, E., Martínez, J. A., Garzón, Ester M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.01.2017 Springer Nature B.V
Schlagworte:	Cards Clocks Compilers Computer Science Embedded systems Evolutionary algorithms Graphics processing units Interpreters Multiple objective analysis Optimization Platforms Power management Processor Architectures Programming Languages Sorting algorithms Evolutionary Multi-Objective algorithms NSGA-II Energy efficiency Low-power platform Jetson
ISSN:	0920-8542, 1573-0484
Online-Zugang:	Volltext
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