All-Pairs Shortest-Paths for Large Graphs on the GPU
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Date
2008
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
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.
Description
@inproceedings{:10.2312/EGGH/EGGH08/047-055,
booktitle = {Graphics Hardware},
editor = {David Luebke and John Owens},
title = {{All-Pairs Shortest-Paths for Large Graphs on the GPU}},
author = {Katz, Gary J. and Jr., Joseph T. Kider},
year = {2008},
publisher = {The Eurographics Association},
ISSN = {1727-3471},
ISBN = {978-3-905674-09-5},
DOI = {/10.2312/EGGH/EGGH08/047-055}
}