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The Parallel Algorithm for the 2-D Discrete Wavelet Transform

机译:二维离散小波变换的并行算法

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The discrete wavelet, transform can be found at, the heart of many image-processing algorithms. Until now, the transform on general-purpose processors (CPUs) was mostly computed using a separable lifting scheme. As the lifting scheme consists of a small number of operations, it is preferred for processing using single-core CPUs. However, considering a parallel processing using multi-core processors, this scheme is inappropriate due to a large number of steps. On such architectures, the number of steps corresponds to the number of points that represent the exchange of data. Consequently, these points often form a performance bottleneck. Our approach appropriately rearranges calculations inside the transform, and thereby reduces the number of steps. In other words, we propose a new scheme that is friendly to parallel environments. When evaluating on multi-core CPUs, we consistently overcome the original lifting scheme. The evaluation was performed on 61-core Intel Xeon Phi and 8-core Intel Xeon processors.
机译:离散小波变换是许多图像处理算法的核心。到目前为止,通用处理器(CPU)上的转换大部分是使用可分离的提升方案来计算的。由于提升方案由少量操作组成,因此首选使用单核CPU进行处理。然而,考虑到使用多核处理器的并行处理,由于大量步骤,该方案是不合适的。在这样的体系结构上,步骤数与代表数据交换的点数相对应。因此,这些要点通常构成性能瓶颈。我们的方法在转换内部适当地重新排列了计算,从而减少了步骤数。换句话说,我们提出了一种对并行环境友好的新方案。在多核CPU上进行评估时,我们始终克服原始的提升方案。评估是在61核Intel Xeon Phi和8核Intel Xeon处理器上进行的。

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