Distributed peak power management for many-core architectures

Recently proposed techniques for peak power management involve centralized decision-making and assume quick evaluation of the various power management states. These techniques do not prevent instantaneous power from exceeding the peak power budget, but instead trigger corrective action when the budget has been exceeded. Similarly, they are not suitable for many-core architectures (processors with tens or possibly hundreds of cores on the same die) due to an exponential explosion in the number of global power management states. In this paper, we look at a hierarchical and a gradient ascent-based technique for decentralized peak power management for many-core architectures. The proposed techniques prevent power from exceeding the peak power budget and enable the placement of several more cores on a die than what the power budget would normally allow. We show up to 47% (33% on average) improvements in throughput for a given power budget. Our techniques outperform the static oracle by 22%.