Handle URI:
http://hdl.handle.net/10754/599963
Title:
The STAPL Parallel Graph Library
Authors:
Harshvardhan,; Fidel, Adam; Amato, Nancy M.; Rauchwerger, Lawrence
Abstract:
This paper describes the stapl Parallel Graph Library, a high-level framework that abstracts the user from data-distribution and parallelism details and allows them to concentrate on parallel graph algorithm development. It includes a customizable distributed graph container and a collection of commonly used parallel graph algorithms. The library introduces pGraph pViews that separate algorithm design from the container implementation. It supports three graph processing algorithmic paradigms, level-synchronous, asynchronous and coarse-grained, and provides common graph algorithms based on them. Experimental results demonstrate improved scalability in performance and data size over existing graph libraries on more than 16,000 cores and on internet-scale graphs containing over 16 billion vertices and 250 billion edges. © Springer-Verlag Berlin Heidelberg 2013.
Citation:
Harshvardhan, Fidel A, Amato NM, Rauchwerger L (2013) The STAPL Parallel Graph Library. Lecture Notes in Computer Science: 46–60. Available: http://dx.doi.org/10.1007/978-3-642-37658-0_4.
Publisher:
Springer Science + Business Media
Journal:
Languages and Compilers for Parallel Computing
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
2013
DOI:
10.1007/978-3-642-37658-0_4
Type:
Book Chapter
ISSN:
0302-9743; 1611-3349
Sponsors:
This research supported in part by NSF awards CRI-0551685, CCF-0833199, CCF-0830753, IIS-096053, IIS-0917266, NSF/DNDO award 2008-DN-077-ARI018-02, byDOE NNSA under the Predictive Science Academic Alliances Program grant DE-FC52-08NA28616, by THECBNHARP award000512-0097-2009, by Chevron, IBM,Intel, Oracle/Sun and by Award KUS-C1-016-04 made by King Abdullah Universityof Science and Technology (KAUST). This research used resources of the NationalEnergy Research Scientific Computing Center, which is supported by the Office ofScience of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorHarshvardhan,en
dc.contributor.authorFidel, Adamen
dc.contributor.authorAmato, Nancy M.en
dc.contributor.authorRauchwerger, Lawrenceen
dc.date.accessioned2016-02-28T06:33:22Zen
dc.date.available2016-02-28T06:33:22Zen
dc.date.issued2013en
dc.identifier.citationHarshvardhan, Fidel A, Amato NM, Rauchwerger L (2013) The STAPL Parallel Graph Library. Lecture Notes in Computer Science: 46–60. Available: http://dx.doi.org/10.1007/978-3-642-37658-0_4.en
dc.identifier.issn0302-9743en
dc.identifier.issn1611-3349en
dc.identifier.doi10.1007/978-3-642-37658-0_4en
dc.identifier.urihttp://hdl.handle.net/10754/599963en
dc.description.abstractThis paper describes the stapl Parallel Graph Library, a high-level framework that abstracts the user from data-distribution and parallelism details and allows them to concentrate on parallel graph algorithm development. It includes a customizable distributed graph container and a collection of commonly used parallel graph algorithms. The library introduces pGraph pViews that separate algorithm design from the container implementation. It supports three graph processing algorithmic paradigms, level-synchronous, asynchronous and coarse-grained, and provides common graph algorithms based on them. Experimental results demonstrate improved scalability in performance and data size over existing graph libraries on more than 16,000 cores and on internet-scale graphs containing over 16 billion vertices and 250 billion edges. © Springer-Verlag Berlin Heidelberg 2013.en
dc.description.sponsorshipThis research supported in part by NSF awards CRI-0551685, CCF-0833199, CCF-0830753, IIS-096053, IIS-0917266, NSF/DNDO award 2008-DN-077-ARI018-02, byDOE NNSA under the Predictive Science Academic Alliances Program grant DE-FC52-08NA28616, by THECBNHARP award000512-0097-2009, by Chevron, IBM,Intel, Oracle/Sun and by Award KUS-C1-016-04 made by King Abdullah Universityof Science and Technology (KAUST). This research used resources of the NationalEnergy Research Scientific Computing Center, which is supported by the Office ofScience of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.en
dc.publisherSpringer Science + Business Mediaen
dc.titleThe STAPL Parallel Graph Libraryen
dc.typeBook Chapteren
dc.identifier.journalLanguages and Compilers for Parallel Computingen
dc.contributor.institutionTexas A and M University, College Station, United Statesen
kaust.grant.numberKUS-C1-016-04en
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