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Exploiting task and data parallelism for advanced video coding on hybrid CPU + GPU platforms

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Abstract

Considering the prevalent usage of multimedia applications on commodity computers equipped with both CPU and GPU devices, the possibility of simultaneously exploiting all parallelization capabilities of such hybrid platforms for high performance video encoding has been highly quested for. Accordingly, a method to concurrently implement the H.264/ advanced video coding (AVC) inter-loop on hybrid GPU + CPU platforms is proposed in this manuscript. This method comprises dynamic dependency aware task distribution methods and real-time computational load balancing over both the CPU and the GPU, according to an efficient dynamic performance modeling. With such optimal balance, the set of rather optimized parallel algorithms that were conceived for video coding on both the CPU and the GPU are dynamically instantiated in any of the existing processing devices, to minimize the overall encoding time. The proposed model does not only provide an efficient task scheduling and load balancing for H.264/AVC inter-loop, but it also does not introduce any significant computational burden to the time-limited video coding application. Furthermore, according to the presented set of experimental results, the proposed scheme has proved to provide speedup values as high as 2.5 when compared with highly optimized GPU-only encoding solutions or even other state of the art algorithm. Moreover, by simply using the existing computational resources that usually equip most commodity computers the proposed scheme is able to achieve inter-loop encoding rates as high as 40 fps at a HD 1920 × 1080 resolution.

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Acknowledgments

This work was partially supported by national funds through Fundação para a Ciência e a Tecnologia (FCT), under project PEst-OE/EEI/LA0021/2013.

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  1. INESC-ID IST-TU Lisbon, Rua Alves Redol, 9, 1000-029, Lisbon, Portugal

    Svetislav Momcilovic, Nuno Roma & Leonel Sousa

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  1. Svetislav Momcilovic
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  2. Nuno Roma
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  3. Leonel Sousa
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Correspondence to Svetislav Momcilovic.

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Momcilovic, S., Roma, N. & Sousa, L. Exploiting task and data parallelism for advanced video coding on hybrid CPU + GPU platforms. J Real-Time Image Proc 11, 571–587 (2016). https://doi.org/10.1007/s11554-013-0357-y

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  • DOI: https://doi.org/10.1007/s11554-013-0357-y

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