Towards GPU HEVC intra decoding: Seizing fine-grain parallelism

D. Souza, A. Ilic, N. Roma, L. Sousa
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引用次数: 9

Abstract

To satisfy the growing demands on real-time video decoders for high frame resolutions, novel GPU parallel algorithms are proposed herein for fully compliant HEVC de-quantization, inverse transform and intra prediction. The proposed algorithms are designed to fully exploit and leverage the fine grain parallelism within these computationally demanding and highly data dependent modules. Moreover, the proposed approaches allow the efficient utilization of the GPU computational resources, while carefully managing the data accesses in the complex GPU memory hierarchy. The experimental results show that the real-time processing is achieved for all tested sequences and the most demanding QP, while delivering average fps of 118.6, 89.2 and 49.7 for Full HD, 2160p and Ultra HD 4K sequences, respectively.
对GPU HEVC内部解码:抓住细粒度并行
为了满足实时视频解码器对高帧分辨率的需求,本文提出了完全兼容HEVC去量化、逆变换和帧内预测的新型GPU并行算法。所提出的算法旨在充分利用和利用这些计算要求高且高度依赖数据的模块中的细粒度并行性。此外,所提出的方法允许高效利用GPU计算资源,同时仔细管理复杂GPU内存层次结构中的数据访问。实验结果表明,在全高清、2160p和超高清4K序列中,平均帧率分别为118.6、89.2和49.7,对所有测试序列和最苛刻的QP都实现了实时处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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