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Using mobile GPU for general-purpose computing – a case study of face recognition on smartphones

Kwang-Ting (Tim) Cheng, Yi-Chu Wang
University of California, Santa Barbara, CA, U.S.A.
International Symposium on VLSI Design, Automation and Test (VLSI-DAT), 2011

@inproceedings{cheng2011using,

   title={Using mobile GPU for general-purpose computing–a case study of face recognition on smartphones},

   author={Cheng, K.T.T. and Wang, Y.C.},

   booktitle={VLSI Design, Automation and Test (VLSI-DAT), 2011 International Symposium on},

   pages={1–4},

   year={2011},

   organization={IEEE}

}

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As GPU becomes an integrated component in handheld devices like smartphones, we have been investigating the opportunities and limitations of utilizing the ultra-low-power GPU in a mobile platform as a general-purpose accelerator, similar to its role in desktop and server platforms. The special focus of our investigation has been on mobile GPU’s role for energy-optimized real-time applications running on battery-powered handheld devices. In this work, we use face recognition as an application driver for our study. Our implementations on a smartphone reveals that, utilizing the mobile GPU as a co-processor can achieve significant speedup in performance as well as substantial reduction in total energy consumption, in comparison with a mobile-CPU-only implementation on the same platform.
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