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Algorithmic-Level Approximate Computing Applied to Energy Efficient HEVC Decoding

机译:算法级近似计算在高能效HEVC解码中的应用

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This paper presents a novel method for applying approximate computing at the level of a complete application. The method decomposes the application into processing blocks which types define the classes of approximate computing techniques they may tolerate. By applying these approximation techniques to the most computationally intensive blocks, drastic energy reduction can be obtained at a limited cost in terms of Quality of Service. The algorithmic-level approximate computing method is applied to a software High Efficiency Video Coding (HEVC) video decoder. The method is shown to offer multiple trade-offs between the quality of the decoded video and the energy required for the decoding process. The algorithmic-level approximate computing method offers new possibilities in terms of application energy budgeting. Energy reductions of up to 40 percent are demonstrated for a limited degradation of the application Quality of Service.
机译:本文提出了一种在完整应用程序级别上应用近似计算的新颖方法。该方法将应用程序分解为处理块,这些处理块的类型定义了它们可以容许的近似计算技术的类别。通过将这些近似技术应用于计算量最大的块,就可以在服务质量方面以有限的成本获得大幅降低的能耗。算法级别的近似计算方法应用于软件高效视频编码(HEVC)视频解码器。示出该方法在解码视频的质量和解码过程所需的能量之间提供多种折衷。算法级的近似计算方法在应用能源预算方面提供了新的可能性。事实证明,由于服务质量的有限下降,能耗降低了40%。

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