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Matching search in fractal video compression and its parallel implementation in distributed computing environments

机译:分形视频压缩中的匹配搜索及其在分布式计算环境中的并行实现

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Fractal video compression is a relatively new video compression method. Its attraction is due to the high compression ratio and the simple decompression algorithm. But its computational complexity is high and as a result parallel algorithms on high performance machines become one way out. In this study we partition the matching search, which occupies the majority of the work in a fractal video compression process, into small tasks and implement them in two distributed computing environments, one using DCOM and the other using .NET Remoting technology, based on a local area network consists of loosely coupled PCs. Experimental results show that the parallel algorithm is able to achieve a high speedup in these distributed environments.
机译:分形视频压缩是一种相对较新的视频压缩方法。它的吸引力归因于高压缩比和简单的解压缩算法。但是它的计算复杂度很高,因此高性能计算机上的并行算法成为一种出路。在这项研究中,我们将匹配搜索(占分形视频压缩过程中大部分工作的搜索)划分为小任务,并在两个分布式计算环境中实现它们,一个使用DCOM,另一个使用.NET Remoting技术,基于局域网由松散耦合的PC组成。实验结果表明,并行算法能够在这些分布式环境中实现较高的加速比。

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