6th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing

Research Article

An architecture design of GPU-accelerated VoD streaming servers with network coding

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  • @INPROCEEDINGS{10.4108/icst.collaboratecom.2010.37,
        author={Jin Zhao and Xinya Zhang and Xin Wang},
        title={An architecture design of GPU-accelerated VoD streaming servers with network coding},
        proceedings={6th International ICST Conference on Collaborative Computing: Networking, Applications, Worksharing},
        publisher={IEEE},
        proceedings_a={COLLABORATECOM},
        year={2011},
        month={5},
        keywords={Video-on-demand network coding GPU streaming server},
        doi={10.4108/icst.collaboratecom.2010.37}
    }
    
  • Jin Zhao
    Xinya Zhang
    Xin Wang
    Year: 2011
    An architecture design of GPU-accelerated VoD streaming servers with network coding
    COLLABORATECOM
    ICST
    DOI: 10.4108/icst.collaboratecom.2010.37
Jin Zhao1,2,*, Xinya Zhang1,2,*, Xin Wang1,2,*
  • 1: School of Computer Science, Fudan University, Shanghai 200433, China
  • 2: Shanghai Key Lab of Intelligent Information Processing, Shanghai 200433, China
*Contact email: jzhao@fudan.edu.cn, 06300720198@fudan.edu.cn, xinw@fudan.edu.cn

Abstract

Graphics processing unit (GPU) has evolved into a general-purpose computing platform. Inspired by the GPU technology advantage, this paper concerns the design and performance evaluation of practical GPU-accelerated server architecture for Video-on-Demand (VoD) services with network coding. Following the proposal of an optimized network coding algorithm based on parallel threads on GPU, a GPU-Accelerated Server (GAS) for VoD streaming is designed to leverage the workload between GPU and CPU and thus improve the performance of the VoD server. Extensive real-world experimental results have proved that compared with the approaches with network coding performed only on CPU or GPU, the proposed GAS architecture is more advantageous in serving capacity, response time, and CPU usage. Our study has investigated a way of designing high performance VoD streaming servers with network coding and GPU-acceleration incorporated.