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Title: 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 Bellman-Ford 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 (R-MAT) and small-world network graphs as well as real-world graphs from Facebook, Twitter, LiveJournal, and the road maps of California and Texas.

Authors:
 [1];  [2];  [1]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  2. 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:  
AC05-00OR22725
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:10.1007/978-3-319-73814-7_5.
Aderholdt, Ferrol, Graves, Jeffrey, & Venkata, Manjunath Gorentla. Parallelizing Single Source Shortest Path with OpenSHMEM. United States. doi:10.1007/978-3-319-73814-7_5.
Aderholdt, Ferrol, Graves, Jeffrey, and Venkata, Manjunath Gorentla. Mon . "Parallelizing Single Source Shortest Path with OpenSHMEM". United States. doi:10.1007/978-3-319-73814-7_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 Bellman-Ford 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 (R-MAT) and small-world network graphs as well as real-world graphs from Facebook, Twitter, LiveJournal, and the road maps of California and Texas.},
doi = {10.1007/978-3-319-73814-7_5},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {8}
}

Conference:
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Works referenced in this record:

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