Publication: Efficient Parallel Video Encoding on Heterogeneous Systems
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2014-11
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Abstract
In this study we propose an efficient method for collaborative H.264/AVC inter-loop encoding in heterogeneous CPU+GPU systems. This method relies on specifically developed extensive library of highly optimized parallel algorithms for both CPU and GPU architectures, and all inter-loop modules. In order to minimize the overall encoding time, this method integrates adaptive load balancing for the most computationally intensive, inter-prediction modules, which is based on dynamically built functional performance models of heterogenous devices and inter-loop modules. The proposed method also introduces efficient communication-aware techniques, which maximize data reusing, and decrease the overhead of expensive data transfers in collaborative video encoding. The experimental results show that the proposed method is able of achieving real-time video encoding for very demanding video coding parameters, i.e., full HD video format, 64×64 pixels search area and the exhaustive motion estimation.
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Proceedings of: First International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2014). Porto (Portugal), August 27-28, 2014.
Keywords
Video coding, Divisible load theory, Load-balancing, CPU+GPU computing
Bibliographic citation
Carretero Pérez, Jesús; et.al. (eds.). (2014) Proceedings of the First International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2014): Porto, Portugal. Universidad Carlos III de Madrid, pp. 37-42.