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Power and Performance Characterization of Computational Kernels on the GPU

Y. Jiao, H. Lin, P. Balaji, W. Feng
Department of Computer Science, Virginia Tech, Blacksburg, VA, USA
IEEE/ACM International Conference on & International Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and Communications (GreenCom), 2010

@inproceedings{jiao2010power,

   title={Power and Performance Characterization of Computational Kernels on the GPU},

   author={Jiao, Y. and Lin, H. and Balaji, P. and Feng, W.},

   booktitle={Proceedings of the 2010 IEEE/ACM Int’l Conference on Green Computing and Communications & Int’l Conference on Cyber, Physical and Social Computing},

   pages={221–228},

   year={2010},

   organization={IEEE Computer Society}

}

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Nowadays Graphic Processing Units (GPU) are gaining increasing popularity in high performance computing (HPC). While modern GPUs can offer much more computational power than CPUs, they also consume much more power. Energy efficiency is one of the most important factors that will affect a broader adoption of GPUs in HPC. In this paper, we systematically characterize the power and energy efficiency of GPU computing. Specifically, using three different applications with various degrees of compute and memory intensiveness, we investigate the correlation between power consumption and different computational patterns under various voltage and frequency levels. Our study revealed that energy saving mechanisms on GPUs behave considerably different than CPUs. The characterization results also suggest possible ways to improve the ‘greenness’ of GPU computing.
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