A GPU Based Parallel Hierarchical Fuzzy ART Clustering
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.
S. Kim and D. C. Wunsch, "A GPU Based Parallel Hierarchical Fuzzy ART Clustering," Proceedings of the International Joint Conference on Neural Networks, pp. 2778-2782, Institute of Electrical and Electronics Engineers (IEEE), Jan 2011.
The definitive version is available at http://dx.doi.org/10.1109/IJCNN.2011.6033584
2011 International Joint Conference on Neural Network, IJCNN '11 (2011: Jul. 31-Aug. 5, San Jose, CA)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2011 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.