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Hybrid Embarrassingly Parallel on heterogeneous platform

Chunye Gong, Jie Liu, Jin Qin, Qingfeng Hu, Zhenghu Gong
Dept. of Comput. Sci., Nat. Univ. of Defense Technol., Changsha, China
3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT), 2010

@inproceedings{gong2010hybrid,

   title={Hybrid Embarrassingly Parallel on heterogeneous platform},

   author={Gong, C. and Liu, J. and Qin, J. and Hu, Q. and Gong, Z.},

   booktitle={Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on},

   volume={3},

   pages={95–99},

   year={2010},

   organization={IEEE}

}

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The Embarrassingly Parallel (EP) is one kernel benchmark of NAS Parallel Benchmarks (NPB). EP generates pairs of Gaussian Random Deviates (GRDs) of large random numbers which produced by Linear Congruential Generator (LCG). In this paper, the Hybrid EP is efficient implemented on CPU/GPU heterogeneous platform. Experimental results show that the Hybrid EP is 11.98 times faster than equivalent multicore CPU and outperforms equivalent GPU by 7.52%.
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