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Parallel domain decomposition and load balancing using space-filling curves

机译:使用空间填充曲线并行域分解和负载平衡

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Partitioning techniques based on space filling curves have received much recent attention due to their low running time and good load balance characteristics. The basic idea underlying these methods is to order the multidimensional data according to a space filling curve and partition the resulting one dimensional order. However, space filling curves are defined for points that lie on a uniform grid of a particular resolution. It is typically assumed that the coordinates of the points are representable using a fixed number of bits, and the run times of the algorithms depend upon the number of bits used. We present a simple and efficient technique for ordering arbitrary and dynamic multidimensional data using space filling curves and its application to parallel domain decomposition and load balancing. Our technique is based on a comparison routine that determines the relative position of two points in the order induced by a space filling curve. The comparison routine could then be used in conjunction with any parallel sorting algorithm to effect parallel domain decomposition.
机译:由于其低运行时间和良好的负载平衡特性,基于空间填充曲线的分区技术最近受到了最近的关注。这些方法的基本思想是根据空间填充曲线订购多维数据,并将结果一维顺序分配。然而,为位于特定分辨率的均匀网格上的点定义空间填充曲线。通常假设点的坐标是使用固定数量的比特表示的,并且算法的运行时间取决于所使用的比特数。我们介绍了一种简单而有效的技术,可以使用空间填充曲线订购任意和动态多维数据,并应用于并行域分解和负载平衡。我们的技术基于比较例程,其在空间填充曲线引起的顺序中确定两个点的相对位置。然后可以与任何并行分选算法结合使用的比较例程来实现平行域分解。

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