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Evaluation of an OpenCL-Based FPGA Platform for Particle Filter

Shunsuke Tatsumi, Masanori Hariyama, Norikazu Ikoma
Graduate School of Information Sciences, Tohoku University, 6-6-05 Aramaki Aza Aoba, Aoba, Sendai 980-8579, Japan
Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.20, No.5, 2016

@article{tatsumi2016evaluation,

   title={Evaluation of an OpenCL-Based FPGA Platform for Particle Filter},

   author={Tatsumi, Shunsuke and Hariyama, Masanori and Ikoma, Norikazu},

   journal={Journal of Advanced Computational Intelligence Vol},

   volume={20},

   number={5},

   year={2016}

}

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Particle filter is one promising method to estimate the internal states in dynamical systems, and can be used for various applications such as visual tracking and mobile-robot localization. The major drawback of particle filter is its large computational amount, which causes long computational-time and large powerconsumption. In order to solve this problem, this paper proposes an Field-Programmable Gate Array (FPGA) platform for particle filter. The platform is designed using the OpenCL-based design tool that allows users to develop using a high-level programming language based on C and to change designs easily for various applications. The implementation results demonstrate the proposed FPGA implementation is 106 times faster than the CPU one, and the power-delay product of the FPGA implementation is 1.1% of the CPU one. Moreover, implementations for three different systems are shown to demonstrate flexibility of the proposed platform.
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