Center for Human Modeling and Simulation

Document Type

Conference Paper

Date of this Version

2008

Publication Source

Proceedings of the 23rd ACM SIGGRAPH/EUROGRAPHICS Symposium on Graphics Hardware (GH '08)

Start Page

47

Last Page

55

DOI

10.2312/EGGH/EGGH08/047-055

Abstract

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.

Copyright/Permission Statement

The definitive version is available at http://diglib.eg.org/handle/10.2312/EGGH.EGGH08.047-055.

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Date Posted: 13 January 2016