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    The STAPL Parallel Graph Library

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    Type
    Book Chapter
    Authors
    Harshvardhan
    Fidel, Adam
    Amato, Nancy M.
    Rauchwerger, Lawrence
    KAUST Grant Number
    KUS-C1-016-04
    Date
    2013
    Permanent link to this record
    http://hdl.handle.net/10754/599963
    
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    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.
    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.
    Publisher
    Springer Nature
    Journal
    Languages and Compilers for Parallel Computing
    DOI
    10.1007/978-3-642-37658-0_4
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-642-37658-0_4
    Scopus Count
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