Abstract
We develop an efficient parallel algorithm for answering shortest-path queries in planar graphs and implement it on a multi-node CPU-GPU clusters. The algorithm uses a divide-and-conquer approach for decomposing the input graph into small and roughly equal subgraphs and constructs a distributed data structure containing shortest distances within each of those subgraphs and between their boundary vertices. For a planar graph with n vertices, that data structure needs O(n) storage per processor and allows queries to be answered in \(O(n^{1/4})\) time.
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Chapuis, G., Djidjev, H. (2015). Shortest-Path Queries in Planar Graphs on GPU-Accelerated Architectures. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2015. Lecture Notes in Computer Science(), vol 9374. Springer, Cham. https://doi.org/10.1007/978-3-319-26520-9_5
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DOI: https://doi.org/10.1007/978-3-319-26520-9_5
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