Adaptive power efficiency control by computer power consumption prediction using performance counters

As the number of data centers has grown in pace with the burgeoning expansion in information technology (IT), reducing the power consumption of data centers has become an important social challenge. IT equipment is a primary contributor to data center power consumption and, as such, is an area where power conservation is indispensable. Nevertheless, while the efficiency of the power supply modules integrated into computers has recently seen significant improvements, their overall efficiency generally depends on load rates. This is especially true under low power load conditions, where it is known that efficiency decreases drastically. Recently, power-saving techniques that work by controlling the power module configuration under low power load conditions have been considered, and based on such techniques, further efficiency improvements can be expected by interlocking the real time computer load status with the power supply configuration control. In this study, the performance counters built into the processor of a computer are used to predict power load variations and an equation that predicts server power consumption levels is defined. In a server application experiment utilizing prototype computer hardware and multiple regression analysis, we validated that the equation could precisely predict computer power requirements. Furthermore, the adaptive efficiency control using the power prediction equation is considered. In order to validate the effect, the circuit simulation of the efficiency control was conducted. The simulation results show that power supply efficiency improvements up to 7.2% could be achieved using the model equations to control the efficiency of power supply modules.