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Performance and Power Analysis of ATI GPU: A Statistical Approach

Ying Zhang, Yue Hu, Bin Li, Lu Peng
Department of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, LA, 70803
6th IEEE International Conference on Networking, Architecture and Storage (NAS), 2011

@inproceedings{zhang2011performance,

   title={Performance and Power Analysis of ATI GPU: A Statistical Approach},

   author={Zhang, Y. and Hu, Y. and Li, B. and Peng, L.},

   booktitle={Networking, Architecture and Storage (NAS), 2011 6th IEEE International Conference on},

   pages={149–158},

   organization={IEEE}

}

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We present a comprehensive study on the performance and power consumption of a recent ATI GPU. By employing a rigorous statistical model to analyze execution behaviors of representative general-purpose GPU (GPGPU) applications, we conduct insightful investigations on the target GPU architecture. Our results demonstrate that the GPU execution throughput and the power dissipation are dependent on different architectural variables. Furthermore, we design a set of micro-benchmarks to study the power consumption features of different function units on the GPU. Based on those results, we derive instructive principles that can guide the design of power-efficient high performance computing systems.
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