Parallelizing Single Source Shortest Path with OpenSHMEM
Abstract
Single Source Shortest Path (SSSP) is one of the widely occurring graph problems where the paths are discovered from an origin vertex to all other vertices in the graph. In this paper, we discuss our experience parallelizing SSSP using OpenSHMEM. We start with the serial Dijkstra and BellmanFord algorithms, parallelize these algorithms, and adapt them to the Partitioned Global Address Space (PGAS) programming model. We implement the parallel algorithms using OpenSHMEM and introduce a series of optimizations to achieve higher scaling and performance characteristics. The implementation is evaluated on Titan with various graphs including synthetic Recursive Matrix (RMAT) and smallworld network graphs as well as realworld graphs from Facebook, Twitter, LiveJournal, and the road maps of California and Texas.
 Authors:

 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
 Tennessee Technological Univ., Cookeville, TN (United States)
 Publication Date:
 Research Org.:
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
 Sponsoring Org.:
 USDOE Office of Science (SC)
 OSTI Identifier:
 1567473
 DOE Contract Number:
 AC0500OR22725
 Resource Type:
 Conference
 Resource Relation:
 Conference: OpenSHMEM 2017: OpenSHMEM and Related Technologies. Big Compute and Big Data Convergence
 Country of Publication:
 United States
 Language:
 English
 Subject:
 97 MATHEMATICS AND COMPUTING; Computer Science
Citation Formats
Aderholdt, Ferrol, Graves, Jeffrey, and Venkata, Manjunath Gorentla. Parallelizing Single Source Shortest Path with OpenSHMEM. United States: N. p., 2017.
Web. doi:10.1007/9783319738147_5.
Aderholdt, Ferrol, Graves, Jeffrey, & Venkata, Manjunath Gorentla. Parallelizing Single Source Shortest Path with OpenSHMEM. United States. doi:10.1007/9783319738147_5.
Aderholdt, Ferrol, Graves, Jeffrey, and Venkata, Manjunath Gorentla. Mon .
"Parallelizing Single Source Shortest Path with OpenSHMEM". United States. doi:10.1007/9783319738147_5.
@article{osti_1567473,
title = {Parallelizing Single Source Shortest Path with OpenSHMEM},
author = {Aderholdt, Ferrol and Graves, Jeffrey and Venkata, Manjunath Gorentla},
abstractNote = {Single Source Shortest Path (SSSP) is one of the widely occurring graph problems where the paths are discovered from an origin vertex to all other vertices in the graph. In this paper, we discuss our experience parallelizing SSSP using OpenSHMEM. We start with the serial Dijkstra and BellmanFord algorithms, parallelize these algorithms, and adapt them to the Partitioned Global Address Space (PGAS) programming model. We implement the parallel algorithms using OpenSHMEM and introduce a series of optimizations to achieve higher scaling and performance characteristics. The implementation is evaluated on Titan with various graphs including synthetic Recursive Matrix (RMAT) and smallworld network graphs as well as realworld graphs from Facebook, Twitter, LiveJournal, and the road maps of California and Texas.},
doi = {10.1007/9783319738147_5},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {8}
}
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