Computer Power Supply Efficiency Improvement by Power Consumption Prediction Procedure Using Performance Counters

As the use of information technology (IT) is explosively spreading, reducing the power consumption of IT devices such as servers has become an important social challenge. 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. Based on such techniques, further efficiency improvements, can be expected by an adaptive efficiency controls which interlocks the real-time data processing 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 the power consumption levels is defined. In a server application experiment utilizing prototype computer hardware and regression analysis, it is validated that the equation could precisely predict processor power consumption. The evaluation shows that significant power supply efficiency improvements could be achieved especially for light load condition. The dependency of the efficiency improvement and operation period is investigated and preferable time scale of the adaptive control is proposed.