A Survey and Measurement Study of GPU DVFS on Energy Conservation

October 06, 2016 ยท The Cartographer ยท ๐Ÿ› Digit. Commun. Networks

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
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"Title-pattern auto-detect: A Survey and Measurement Study of GPU DVFS on Energy Conservation"

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Authors Xinxin Mei, Qiang Wang, Xiaowen Chu arXiv ID 1610.01784 Category cs.DC: Distributed Computing Citations 51 Venue Digit. Commun. Networks Last Checked 1 day ago
Abstract
Energy efficiency has become one of the top design criteria for current computing systems. The dynamic voltage and frequency scaling (DVFS) has been widely adopted by laptop computers, servers, and mobile devices to conserve energy, while the GPU DVFS is still at a certain early age. This paper aims at exploring the impact of GPU DVFS on the application performance and power consumption, and furthermore, on energy conservation. We survey the state-of-the-art GPU DVFS characterizations, and then summarize recent research works on GPU power and performance models. We also conduct real GPU DVFS experiments on NVIDIA Fermi and Maxwell GPUs. According to our experimental results, GPU DVFS has significant potential for energy saving. The effect of scaling core voltage/frequency and memory voltage/frequency depends on not only the GPU architectures, but also the characteristic of GPU applications.
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