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Visualization of Pareto Solutions by Spherical Self-Organizing Map and It’s acceleration on a GPU
Factuly of Engineering, Doshisha University, Kyoto, Japan
Factuly of Engineering, Doshisha University, Kyoto, Japan
Factuly of Engineering, Doshisha University, Kyoto, Japan
Factuly of Engineering, Doshisha University, Kyoto, Japan
Faculty of department of life and medical science, Doshisha University, Kyoto, Japan
- 1 Factuly of Engineering, Doshisha University, Kyoto, Japan
- 2 Factuly of Engineering, Doshisha University, Kyoto, Japan
- 3 Factuly of Engineering, Doshisha University, Kyoto, Japan
- 4 Factuly of Engineering, Doshisha University, Kyoto, Japan
- 5 Faculty of department of life and medical science, Doshisha University, Kyoto, Japan
Journal of Software Engineering and Applications·Volume 05 (2012)·Pages 129–137·Published 29 March 2012·DOI10.4236/jsea.2012.53020
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Abstract
In this study, we visualize Pareto-optimum solutions derived from multiple-objective optimization using spherical self-organizing maps (SOMs) that lay out SOM data in three dimensions. There have been a wide range of studies involving plane SOMs where Pareto-optimal solutions are mapped to a plane. However, plane SOMs have an issue that similar data differing in a few specific variables are often placed at far ends of the map, compromising intuitiveness of the visualization. We show in this study that spherical SOMs allow us to find similarities in data otherwise undetectable with plane SOMs. We also implement and evaluate the performance using parallel sphere processing with several GPU environments.
KeywordsSelf-Organizing MapSOMSphericalGPUPareto-Optimal SolutionsGPU Acceleration
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