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Optimization design for parallel coloring of a set of graphs in the High-Performance Computing

机译:高性能计算中一组图形的并行着色的优化设计

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This paper presents solution to problem of edge coloring of sizable set of cubic graphs and examination of relations between these graphs. We solved this problem on various computing systems and for various sizes of the problem (various number of graphs). For the computations we used High-Performance Computing Cluster and Amazon Web Services cloud environment. We measured and analyzed time of computation of edge coloring and other properties. Largest set we worked with contained almost 10 million graphs. We created new methodology, which can be used to finding order of the edges which optimizes time of computation of edge coloring for certain subset of graphs. On the basis of this methodology, we implemented algorithm for parallel edge coloring of set of graphs. For testing of the methodology, we designed 8 experiments. Results showed, that worst time of edge coloring of graph from set of 19 935 graphs before use of the methodology was 1260 ms. After application of our methodology, we found same order of edge coloring for whole group of 19 935 graphs and the highest time of coloring was 10 ms.
机译:本文提出了相当大的三次图集的边缘着色问题的解决方案,并研究了这些图之间的关系。我们在各种计算系统上以及针对各种大小的问题(各种数量的图)解决了该问题。对于计算,我们使用了高性能计算集群和Amazon Web Services云环境。我们测量并分析了边缘着色和其他属性的计算时间。我们使用的最大集合包含将近1000万张图表。我们创建了一种新的方法,该方法可用于查找边缘的顺序,从而优化图的某些子集的边缘着色计算时间。在此方法的基础上,我们实现了图形集的并行边缘着色算法。为了测试该方法,我们设计了8个实验。结果表明,在使用该方法之前,来自19 935个图形集的图形边缘着色的最差时间为1260 ms。应用我们的方法后,我们发现整组19 935张图的边缘着色顺序相同,并且着色的最高时间为10 ms。

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