6404

A GPU based Parallel Hierarchical Fuzzy ART Clustering

Sejun Kim
Department of Computer Engineering, Missouri University of Science and Technology
The 2011 International Joint Conference on Neural Networks (IJCNN), 2011

@inproceedings{kim2011gpu,

   title={A GPU based Parallel Hierarchical Fuzzy ART Clustering},

   author={Kim, S. and Wunsch, D.C.},

   booktitle={Neural Networks (IJCNN), The 2011 International Joint Conference on},

   pages={2778–2782},

   year={2011},

   organization={IEEE}

}

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Hierarchical clustering is an important and powerful but computationally extensive operation. Its complexity motivates the exploration of highly parallel approaches such as Adaptive Resonance Theory (ART). Although ART has been implemented on GPU processors, this paper presents the first hierarchical ART GPU implementation we are aware of. Each ART layer is distributed in the GPU’s multiprocessors and is trained simultaneously. The experimental results show that for deep trees, the GPU’s performance advantage is significant.
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