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Code repository for graph analytics work utilizing Spark+GPU

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WACCPD-2016

Code repository for graph analytics work utilizing Spark+GPU. The subdirectories "WACCPD" and "IJHPCN" contain all source code and data used for the corresponding publications listed below.

Citation Information

WACCPD

Robert Searles*, Stephen Herbein*, and Sunita Chandrasekaran. A Portable, High-Level Graph Analytics Framework Targeting Distributed, Heterogeneous Systems. In IEEE Proceedings of third Workshop on Accelerator Programming Using Directives (WACCPD), pp. 79-88, Salt Lake City, UT, November 2016.

@inproceedings{searles2016portable,
 title={A portable, high-level graph analytics framework targeting distributed, heterogeneous systems},
 author={Searles, Robert and Herbein, Stephen and Chandrasekaran, Sunita},
 booktitle={Proceedings of the Third International Workshop on Accelerator Programming Using Directives},
 pages={79--88},
 year={2016},
 organization={IEEE Press}
}

IJHPCN

Robert Searles, Stephen Herbein, Travis Johnston, Michela Taufer, Sunita Chandrasekaran. Creating a Portable, High-Level Graph Analytics Framework For Compute and Data-Intensive Applications. In the International Journal of High Performance Computing and Networking (IJHPCN). [UNDER REVIEW]

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Code repository for graph analytics work utilizing Spark+GPU

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  • Python 84.8%
  • Cuda 9.3%
  • C 2.6%
  • C++ 2.4%
  • Shell 0.9%