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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Adaptative Resonance Theory Fuzzy Networks Parallel Computation Using CUDA
verfasst von : M. Martínez-Zarzuela, F. J. Díaz Pernas, A. Tejero de Pablos, M. Antón Rodríguez, J. F. Díez Higuera, D. Boto Giralda, D. González Ortega
Erschienen in: Bio-Inspired Systems: Computational and Ambient Intelligence
Verlag: Springer Berlin Heidelberg
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Programming of Graphics Processing Units (GPUs) has evolved in a way they can be used to address and speed-up computation of algorithms exemplified by data-parallel models. In this paper parallelization of a Fuzzy ART algorithm is described and a detailed explanation of its implementation under CUDA is given. Experimental results show the algorithm runs up to 52 times faster on the GPU than on the CPU for testing and 18 times faster for training under specific conditions.