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Asynchronous Parallel Computing Model of Global Motion Estimation with CUDA

Zuo Chen, Jialiang Ji, Renfa Li
School of Computer and Communication, Hunan University, Chang sha, China
Journal of Computers, Vol 7, No 2 (2012), 341-348, 2012

@article{chen2012asynchronous,

   title={Asynchronous Parallel Computing Model of Global Motion Estimation with CUDA},

   author={Chen, Z. and Ji, J. and Li, R.},

   journal={Journal of Computers},

   volume={7},

   number={2},

   pages={341–348},

   year={2012}

}

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For video coding, weighing the balance between and coding rate image quality, we apply global motion search algorithm to avoid loss of image quality and parallel computing capacity of graphics processors to accelerate the encoding process. According to the heterogeneous system of CPU+GPU, and the multi-threaded parallel structure, thread synchronization features of CUDA platform, we build a proper global motion search on CUDA computing model; taking CUDA thread synchronization mechanism to solve the problem of data consistency and improve the efficiency of on-chip data communication; taking CUDA asynchronous mechanism to hide the delay caused by the CPU functions. Demonstrated by the experimental results, parallel computing model based on CUDA could significantly improve the efficiency of motion estimation algorithm and a certain improvement gains from the asynchronous parallel model based on CUDA asynchronous system.
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