Dynamic Voltage/Frequency Scaling (DVFS) is a useful tool for improving system energy efficiency, especially in multi-core chips where energy is more of a limiting factor. Per-core DVFS, where cores can independently scale their voltages and frequencies, is particularly effective. We present a DVFS policy using machine learning, which learns the best frequency choices for a machine as a decision tree.
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Moeng et al. (2010) studied this question.