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Parallel Algorithm of IDCT with GPUs and CUDA for Large-scale Video Quality of 3G

机译:使用GPU和CUDA的IDCT并行算法3G的大规模视频质量

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—When video is transmitted over 3G networks, the video quality might suffer from impairments caused by packet losses. Extracting video quality features is a set of algorithms and inverse discrete cosine transforms is an important algorithm in this field. To improve the performance and be suitable to apply to evaluating the 3G video quality in real-time, two different parallel algorithms with CUDA of the inverse discrete cosine transform are proposed. The parallel algorithms are exploited combined the high parallelism of GPUs with a high bandwidth in memory transfer at low cost. Moreover, the device memory accessing model is analyzed and considered the optimal use of the data cache. The experimental results show that the uberkernel algorithm with shared memory and texture memory outperforms other schemes for medium-sized tasks and the perisistent algorithm is better for large-scale tasks.
机译:- 当视频超过3G网络传输时,视频质量可能会受到包损耗引起的损伤。提取视频质量特征是一组算法和逆离散余弦变换是该字段中的重要算法。为了提高性能,适用于实时评估3G视频质量,提出了两种不同的并行算法与逆离散余弦变换的CUDA。利用并行算法将GPU的高并行性与低成本以低成本以高带宽组合。此外,分析了设备存储器访问模型,并考虑了数据高速缓存的最佳使用。实验结果表明,具有共享存储器和纹理存储器的Uberkernel算法优于中型任务的其他方案,并且对于大规模任务更好地更好地实现了痛心算法。

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