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首页> 外文期刊>Journal of Parallel and Distributed Computing >All-Pairs Shortest Path algorithms for planar graph for GPU-accelerated clusters
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All-Pairs Shortest Path algorithms for planar graph for GPU-accelerated clusters

机译:GPU加速集群的平面图的全对最短路径算法

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We present a new approach for solving the All-Pairs Shortest-Path (APSP) problem for planar graphs that exploits the massive on-chip parallelism available in today's Graphics Processing Units (CPUs). We describe two new algorithms based on our approach. Both algorithms use Floyd-Warshall method, have near optimal complexity in terms of the total number of operations, while their 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 fastest known Dijkstra-based GPU implementation and a two-fold speedup over a parallel Dijkstra-based CPU implementation.
机译:我们提出了一种解决平面图全对最短路径(APSP)问题的新方法,该方法利用了当今图形处理单元(CPU)中可用的大规模片上并行性。我们基于我们的方法描述了两种新算法。两种算法都使用Floyd-Warshall方法,在操作总数方面具有接近最佳的复杂度,而它们基于矩阵的结构则足够规则以允许在GPU上高效并行实现。通过采用分而治之的方法,我们能够利用多节点GPU集群,与已知最快的基于Dijkstra的GPU实现相比,可实现超过一个数量级的提速,而与并行Dijkstra相比,可实现两倍的提速。基于CPU的实现。

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