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A multi-source label-correcting algorithm for the all-pairs shortest paths problem

机译:用于全对最短路径问题的多源标签校正算法

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The All-Pairs Shortest Paths (APSP) problem seeks the shortest path distances between all pairs of vertices, and is one of the most fundamental graph problems. In this paper, a fast algorithm with a small working space for the APSP problem on sparse graphs is presented, which first divides the vertices into sets of vertices with each set having a constant number of vertices and then solves the multi-source shortest paths (MSSP) problem for each set in parallel. For solving the MSSP problems, we give a multi-source label-correcting algorithm, as an extension of a label-correcting algorithm for the single-source shortest path problem. Our algorithm uses fewer operations on the priority queue than an implementation based on Dijkstra's algorithm. Our experiments showed that an implementation of our algorithm with SIMD instructions achieves an order of magnitude speedup for real-world geometric graphs compared to an implementation based on Dijkstra's algorithm.
机译:全对最短路径(APSP)问题寻求所有顶点之间的最短路径距离,并且是最基本的图形问题之一。 在本文中,提出了一种快速算法,其在稀疏图上具有用于APSP问题的小型工作空间的快速算法,其首先将顶点划分为具有恒定数量的顶点的每个集合的顶点,然后解决多源最短路径( MSSP)每个并行设置的问题。 为了解决MSSP问题,我们提供了一种多源标签校正算法,作为标签校正算法的单源最短路径问题的扩展。 我们的算法在优先级队列上使用较少的操作而不是基于Dijkstra算法的实现。 我们的实验表明,与基于Dijkstra算法的实现相比,使用SIMD指令的算法实现了与实际几何图的数量级加速度。

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