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An Approach to Parallelize Kruskal's Algorithm Using Helper Threads

机译:一种使用助手线程并行化Kruskal算法的方法

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摘要

In this paper we present a Helper Threading scheme used to parallelize efficiently Kruskal's Minimum Spanning Forest algorithm. This algorithm is known for exhibiting inherently sequential characteristics. More specifically, the strict order by which the algorithm checks the edges of a given graph is the main reason behind the lack of explicit parallelism. Our proposed scheme attempts to overcome the imposed restrictions and improve the performance of the algorithm. The results show that for a wide range of graphs of varying structure, size and density the parallelization of Kruskal's algorithm is feasible. Observed speedups reach up to 5.5 for 8 running threads, revealing the potentials of our approach.
机译:在本文中,我们提出了一种用于高效并行化Kruskal最小生成林算法的助手线程方案。该算法因具有固有的顺序特性而闻名。更具体地说,算法检查给定图边缘的严格顺序是缺少显式并行性的主要原因。我们提出的方案试图克服所施加的限制并提高算法的性能。结果表明,对于各种结构,大小和密度变化的图形,Kruskal算法的并行化是可行的。观察到的8个运行线程的加速比最高可达到5.5,这揭示了我们方法的潜力。

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