Proactive Energy Optimization Algorithms for Wavelet-Based Video Codecs on Power-Aware Processors

We propose a systematic technique for characterizing the workload of a video decoder at a given time and transforming the shape of the workload to optimize the utilization of a critical resource without compromising the distortion incurred in the process. We call our approach proactive resource management. We will illustrate our techniques by addressing the problem of minimizing the energy consumption during decoding a video sequence on a programmable processor that supports multiple voltages and frequencies. We evaluate two different heuristics for the underlying optimization problem that result in 50% to 92% improvements in energy savings compared to techniques that do not use dynamic adaptation