Optimizing energy management in multi-core servers

Abstract

In this paper we develop techniques for analyzing and optimizing energy management in multi-core servers with speed scaling capabilities. Our framework incorporates the processor's dynamic power, and it also accounts for other intricate and important power features such as the static (leakage) power and switching overhead between speed levels. Using stochastic fluid models to capture traffic burst dynamics, we propose and study different strategies for adapting the multi-core server speeds based on the observable buffer content, so as to optimize objective functions that balance energy consumption and performance. It is shown that, for a reasonable switching overhead and a small number of thresholds, a substantial efficiency gain is achieved. In addition, the optimal power consumptions of the different strategies are hardly sensitive to perturbations in the input parameters, so that the performance is robust to misspecifications of the system's input traffic.