TONE: Adaptive temperature optimization for the next generation video encoders

摘要

This paper presents an adaptive temperature optimization technique for the next generation video encoders. It exploits both application-specific knowledge (i.e. video encoding configurations) and video content properties in order to efficiently manage the temperature of advanced video coding systems at the software layer. For designing an efficient technique, we perform an extensive offline analysis to understand the impact of different video properties and configurations on the CPU thermal profiles when processing the next generation video encoder. Our temperature optimization technique performs an application-level prediction of the temperature trend followed by an application-level thermal management policy. The policy dynamically manages the temperature by performing an adaptive encoder configuration selection while providing minimum penalties in terms of bit rate and video quality. The experimental results show that our policy meets temperature constraints with negligible encoding performance loss. Moreover, when compared to state-of-the-art techniques, our policy provides a relatively reduced video quality loss while still meeting the temperature constraints.