Cellular Neural Networks simulation on a parallel graphics processing unit

The last generation of graphics cards hosts an array of processors, which can be efficiently employed to simulate the cellular neural networks dynamic. In this paper we show an implementation done using CUDA (compute unified device architecture), a language expressively created for architectures wit...

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Bibliographic Details
Published in2008 11th International Workshop on Cellular Neural Networks and Their Applications pp. 208 - 212
Main Authors Fernandez, A., San Martin, R., Farguell, E., Pazienza, G.E.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2008
Subjects
Cellular neural networks
Computational modeling
Graphics
Hardware
Mathematical model
Program processors
Propagation
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ISBN142442089X
9781424420896
ISSN2165-0144
DOI10.1109/CNNA.2008.4588679

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Summary:The last generation of graphics cards hosts an array of processors, which can be efficiently employed to simulate the cellular neural networks dynamic. In this paper we show an implementation done using CUDA (compute unified device architecture), a language expressively created for architectures with a multiprocessor core. We compare the results with an optimized CNN implementation on CPU, showing how the current graphics cards technology can be competitively applied to this field.
ISBN:142442089X
9781424420896
ISSN:2165-0144
DOI:10.1109/CNNA.2008.4588679