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Parallel rate-distortion optimized intra mode decision on multi-core graphics processors using greedy-based encoding orders

Ngai-Man Cheung, Oscar C. Au, Man-Cheung Kung, Xiaopeng Fan
Department of Electronic & Computer Engineering, Hong Kong University of Science & Technolog, Hong Kong, China
16th IEEE International Conference on Image Processing (ICIP), 2009

@inproceedings{cheung2009parallel,

   title={Parallel rate-distortion optimized intra mode decision on multi-core graphics processors using greedy-based encoding orders},

   author={Cheung, N.M. and Au, O.C. and Kung, M.C. and Fan, X.},

   booktitle={Image Processing (ICIP), 2009 16th IEEE International Conference on},

   pages={2309–2312},

   organization={IEEE},

   year={2009}

}

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Rate-distortion (RD) optimized intra-prediction mode selection can lead to significant improvement in coding efficiency in intra-frame encoding. However, it would incur considerable increase in encoding complexity. In this paper, we investigate how multi-core Graphics Processing Units (GPUs) can be efficiently utilized to undertake the task of RD optimized intra mode selection in AVS and H.264 video encoding. Achieving efficient GPU-based intra mode decision, however, could be non-trivial. It is because the mode decision of the current block would depend on the reconstructed data of the neighboring blocks. Therefore, the coding modes of neighboring blocks would need to be computed first before that of the current block can be determined. This dependency poses challenge to computation on multi-core GPUs, which rely heavily on parallel data processing to achieve superior speedups. To address this issue, we analyze the data dependency in intra mode decision, and propose novel greedy-based encoding orders to achieve highly parallel processing. We also prove that the proposed greedy-based orders are optimal in terms of execution time. Experimental results suggest that the proposed GPU-based intra mode decision compares favorably to the counterpart implemented on a single-core CPU.
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