Efficient Multi-GPU Computation of All-Pairs Shortest Paths

H. Djidjev, S. Thulasidasan, Guillaume Chapuis, R. Andonov, D. Lavenier
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引用次数: 37

Abstract

We describe a new algorithm for solving the all-pairs shortest-path (APSP) problem for planar graphs and graphs with small separators that exploits the massive on-chip parallelism available in today's Graphics Processing Units (GPUs). Our algorithm, based on the Floyd-War shall algorithm, has near optimal complexity in terms of the total number of operations, while its matrix-based structure is regular enough to allow for efficient parallel implementation on the GPUs. By applying a divide-and-conquer approach, we are able to make use of multi-node GPU clusters, resulting in more than an order of magnitude speedup over the fastest known Dijkstra-based GPU implementation and a two-fold speedup over a parallel Dijkstra-based CPU implementation.
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全对最短路径的高效多gpu计算
我们描述了一种新的算法,用于解决平面图形和具有小分隔符的图形的全对最短路径(APSP)问题,该算法利用了当今图形处理单元(gpu)中可用的大量片上并行性。我们的算法基于Floyd-War shall算法,在操作总数方面具有接近最优的复杂性,而其基于矩阵的结构足够规则,可以在gpu上有效地并行实现。通过应用分而治之的方法,我们能够利用多节点GPU集群,从而比已知最快的基于dijkstra的GPU实现提高一个数量级以上,比并行的基于dijkstra的CPU实现提高两倍。
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