high performance computing on graphics processing units: hgpu.org

Embedded graphic processing unit (GPU) accelerates a real-time rendering process of a graphics application on mobile devices, however, at the cost of consuming a considerable portion of the system energy [1] which is one of the most critical design issues for battery-operated devices. To estimate the power consumption of a graphics application, conventional approaches collect run-time hardware activities of a GPU, and derive the power consumption of the graphics application based on hardware counters. Unfortunately, these hardware counters and power consumption information are difficult to evaluate from a programmer’s point of view. In order to provide graphics programmers a firm notion of how performance and quality relate to energy cost, a high-level power model to assist programmers to balance performance, quality, and energy budget is proposed in this study. Preliminary results demonstrate that the proposed approach is practical and can provide useful information to programmers to optimize the energy efficiency of graphics applications.