Thermal optimization using adaptive approximate computing for video coding

This paper presents a thermal optimization technique that adaptively employs varying degree of approximations at both algorithm and data levels in order to reduce the temperature associated with the high efficiency video coding process while maintaining good quality results. The technique evaluates, at run-time, the regions of a video sequence, frame-by-frame, in terms of tolerance to imprecise computations. It adapts the amount of approximation errors based on the video sequence properties and application-specific knowledge. The proposed technique adaptively controls the strength of approximations (at both algorithm and data levels) depending upon the varying resilience properties of coding different regions with different texture/motion properties. Our content-driven approximate computing technique demonstrates the potential to improve the thermal profile of a chip. Experimental results show that our technique improves temperature profiles by reducing the on-chip temperature by about 10° C on average, while maintaining good quality results.