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Coarse Grained Parallel Algorithm for Hamiltonian Circuit in Convex Bipartite Graphs

机译:凸覆双子图中Hamiltonian电路的粗粒度并行算法

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A bipartite graph G = (V, W, E) is convex if there exists an ordering of the vertices of W such that, for each v ∈ V, the neighbors of v are consecutive in W. In this work, we address the Hamiltonian Circuit Problem, a well-known problem in Combinatorial Optimization. We present a novel sequential linear-time algorithm for determining a Hamiltonian circuit in convex bipartite graphs which can be easily parallelized. We also describe a coarse grained parallel algorithm for that problem which runs in time O((|V|/p) lg(|V|/p) lg p), for p processors, using O(lg p) communication rounds. We also show how to efficiently implement our solution into PRAM and coarse grained parallel models. Our algorithm provides parallel scalability on commodity clusters. We have made experiments in a cluster composed of 64 processors, obtaining increasing speedups in our implementation. As far as we know, that is the first coarse grained parallel algorithm for the problem.
机译:二分拉图G =(V,W,e)是凸的,如果存在W的顶点,例如,对于每个V≠V,则V的邻居在W中是连续的。在这项工作中,我们地址汉密尔顿人电路问题,组合优化中的众所周知的问题。我们提出了一种新型连续的线性时间算法,用于确定凸形二角形图中的哈密顿电路,其可以容易地并行化。我们还描述了一种用于P处理器的时间O((| v | / p)Lg(| v | / p)Lg(| v | / p)Lg P),使用O(LG P)通信轮运行的该问题的粗粒并行算法。我们还展示了如何将我们的解决方案有效地进入PRAM和粗粒色的并行模型。我们的算法在商品集群上提供了并行可扩展性。我们在由64个处理器组成的群集中进行了实验,从而在我们的实施中获得了增加的速度。据我们所知,这是问题的第一个粗粒粗粒并行算法。

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