Adaptive Power Efficiency Control by Computer Power Consumption Prediction Using Performance Counters

Abstract

As the number of data centers has grown in pace with the burgeoning expansion in information technology (IT), reducing data center power consumption has become an important social challenge. Since IT equipment is a primary contributor to the data center power consumption, it is also an area where power conservation efforts are indispensable. Nevertheless, although the efficiency of the power supply modules integrated into computers has recently seen significant improvements, their overall efficiency primarily depends on load rates. This is particularly true under low-power load conditions, where efficiency is known to decrease drastically. Recently, power-saving techniques that work by controlling the power module configuration under low-power load conditions have been considered, and using such techniques, it is expected that further efficiency improvements can be achieved by interlocking the computer load status with the power supply configuration control in real time. In this paper, the performance counters built into computer processors are used to predict power load variations, and an equation that facilitates the prediction of server power consumption levels is defined. In a server application experiment utilizing prototype computer hardware and multiple regression analysis, we confirmed that the power prediction equation could precisely predict computer power requirements and achieve adaptive efficiency control. In order to further validate the efficiency control effect, a circuit simulation was conducted. The simulation results showed that a power loss reduction of up to 28.3% could be achieved using the model equations to control the power supply module efficiency.