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All-pairs shortest-paths for large graphs on the GPU

Gary J. Katz, Joseph T. Kider
University of Pennsylvania
In GH ’08: Proceedings of the 23rd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware (2008), pp. 47-55.

@conference{katz2008all,

   title={All-pairs shortest-paths for large graphs on the GPU},

   author={Katz, G.J. and Kider Jr, J.T.},

   booktitle={Proceedings of the 23rd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware},

   pages={47–55},

   year={2008},

   organization={Eurographics Association}

}

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The all-pairs shortest-path problem is an intricate part in numerous practical applications. We describe a shared memory cache efficient GPU implementation to solve transitive closure and the all-pairs shortest-path problem on directed graphs for large datasets. The proposed algorithmic design utilizes the resources available on the NVIDIA G80 GPU architecture using the CUDA API. Our solution generalizes to handle graph sizes that are inherently larger then the DRAM memory available on the GPU. Experiments demonstrate that our method is able to significantly increase processing large graphs making our method applicable for bioinformatics, internet node traffic, social networking, and routing problems.
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