Modeling power consumption in multicore CPUs with multithreading and frequency scaling

The rapid growth of energy requirements in large data-center has motivated several research projects focusing on the reduction of power consumption. Several techniques have been studied to tackle this problem, and most of them require simple power models to estimate the energy consumption starting from known system parameters. It has been proven that the CPU is the component of a server that is most responsible for its total power consumption: for this reason several power models focusing on this resource has been developed. However, only a few accounts for standard CPU features like dynamic frequency scaling and hyperthreading, which can have a significant impact on the estimation accuracy. In this paper, we present the results from a set of experiments focusing on these CPU features, and we propose a simple power model able to provide accurate power estimates by taking them into account.