Department of Computer Science
A measurement study of GPU DVFS on energy conservation
Nowadays, GPUs are widely used to accelerate many high performance computing applications. Energy conservation of such computing systems has become an important research topic. Dynamic voltage/frequency scaling (DVFS) is proved to be an appealing method for saving energy for traditional computing centers. However, there is still a lack of firsthand study on the effectiveness of GPU DVFS. This paper presents a thorough measurement study that aims to explore how GPU DVFS affects the system energy consumption. We conduct experiments on a real GPU platform with 37 benchmark applications. Our results show that GPU voltage/frequency scaling is an effective approach to conserving energy. For example, by scaling down the GPU core voltage and frequency, we have achieved an average of 19.28% energy reduction compared with the default setting, while giving up no more than 4% of performance. For all tested GPU applications, core voltage scaling is significantly effective to reduce system energy consumption. Meanwhile the effects of scaling core frequency and memory frequency depend on the characteristics of GPU applications. © 2013 ACM.
energy conservation, GPU, voltage/frequency scaling
Source Publication Title
Proceedings of the Workshop on Power-Aware Computing and Systems
Farmington, United States
Link to Publisher's Edition
Mei, Xinxin, Ling Sing Yung, Kaiyong Zhao, and Xiaowen Chu. "A measurement study of GPU DVFS on energy conservation." Proceedings of the Workshop on Power-Aware Computing and Systems (2013).