Index-shuffle图

M. Baumslag, B. Obrenic
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引用次数: 3

摘要

引入索引洗牌图作为并行计算机的候选互连网络。在图嵌入和网络仿真的理论框架中,论证了索引洗牌图相对于超立方体的标准有界度“逼近”,即蝴蝶图和洗牌图的比较优势。一个N节点索引洗牌图模拟:(1)一个N节点洗牌交换图没有减速,而目前由超立方体和蝴蝶模拟的最佳洗牌图会导致/spl Omega/(log N)的减速;(2)其相同大小的蝴蝶图的减速速度为O(log log log N),而目前用shuffle-like图模拟蝴蝶图的最佳减速速度为/spl Omega/(log log N);(3)一个N节点的超立方体,它执行在线分级算法,速度为O(log log N),没有数据循环,而目前最好的超立方体模拟的速度为/spl Omega/(log N),并且只有在允许每个处理器的整个本地数据集通过网络循环的情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Index-shuffle graphs
Index-shuffle graphs are introduced as candidate interconnection networks for parallel computers. The comparative advantages of index-shuffle graphs over the standard bounded-degree "approximations" of the hypercube, namely butterfly-like and shuffle-like graphs, are demonstrated in the theoretical framework of graph embedding and network emulations. An N-node index-shuffle graph emulates: (1) an N-node shuffle-exchange graph with no slowdown, while the currently best emulations of shuffle-like graphs by hypercubes and butterflies incur a slowdown of /spl Omega/(log N); (2) its like-sized butterfly graph with a slowdown O(log log log N), while the currently best emulations of butterfly-like graphs by shuffle-like graphs incur a slowdown of /spl Omega/(log log N); (3) an N-node hypercube that executes an on-line leveled algorithm with a slowdown O(log log N) and without data circulation, while the slowdown of currently best such emulations of the hypercube by its bounded-degree shuffle-like and butterfly-like derivatives remains /spl Omega/(log N), and only if the entire local data set of every processor is allowed to circulate through the network.
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