2964

Statistical Power Consumption Analysis and Modeling for GPU-based Computing

Xiaohan Ma, Mian Dong, Lin Zhong, Zhigang Deng
University of Houston
In Workshop on Power Aware Computing and Systems (HotPower ’09) (2009)

@conference{ma2009statistical,

   title={Statistical Power Consumption Analysis and Modeling for GPU-based Computing},

   author={Ma, X. and Dong, M. and Zhong, L. and Deng, Z.},

   booktitle={Proc. of ACM SOSP Workshop on Power Aware Computing and Systems (HotPower)},

   year={2009},

   organization={Citeseer}

}

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In recent years, more and more transistors have been integrated within the GPU, which has resulted in steadily rising power consumption requirements. In this paper we present a preliminary scheme to statistically analyze and model the power consumption of a mainstream GPU (NVidia GeForce 8800gt) by exploiting the innate coupling among power consumption characteristics, runtime performance, and dynamic workloads. Based on the recorded runtime GPU workload signals, our trained statistical model is capable of robustly and accurately predicting power consumption of the target GPU. To the best of our knowledge, this study is the first work that applies statistical analysis to model the power consumption of a mainstream GPU, and its results provide useful insights for future endeavors of building energy-efficient GPU computing paradigms.
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