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Parallelizing fuzzy rule generation using GPGPU

Takesuke Uenishi, Tomoharu Nakashima and Noriyuki Fujimoto
Graduate School of Engineering, Osaka Prefecture University, 1-1, Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531, Japan
Artificial Life and Robotics, Volume 16, Number 2, 214-218, 2011

@article{springerlink:10.1007/s10015-011-0920-1,

   author={Uenishi, Takesuke and Nakashima, Tomoharu and Fujimoto, Noriyuki},

   affiliation={Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka, 599-8531 Japan},

   title={Parallelizing fuzzy rule generation using GPGPU},

   journal={Artificial Life and Robotics},

   publisher={Springer Japan},

   issn={1433-5298},

   keyword={Computer Science},

   pages={214-218},

   volume={16},

   issue={2},

   url={http://dx.doi.org/10.1007/s10015-011-0920-1},

   note={10.1007/s10015-011-0920-1},

   year={2011}

}

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This article proposes a method to parallelize the process of generating fuzzy if-then rules for pattern classification problems in order to reduce the computational time. The proposed method makes use of general purpose computation on graphics processing units (GPGPUs)’ parallel implementation with compute unified device architecture (CUDA), a development environment. CUDA contains a library to perform matrix operations in parallel. In the proposed method, published source codes of matrix multiplication are modified so that the membership values of given training patterns with antecedent fuzzy sets are calculated. In a series of computational experiments, it is shown that the computational time is reduced for those problems that require high computational effort.
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