Blind identification of power sources in processors

Abstract

The ability to measure power consumption is at the heart of power and thermal management techniques. Modern processors are equipped with hardware monitoring mechanisms that can measure total power. However, this lumped measurement is not sufficient if there is a need to execute fine-grain thermal and power management techniques. This paper proposes a new direction for identifying the fine-grain sources of power consumption in many-core processors. For the first time, we show that it is possible to simultaneously identify both the power consumption of different cores and the thermal model of the chip from just the measurements of the thermal sensors and the total power consumption measurement. Our identification technique is blind as it does not require design knowledge of the thermal model to identify the power sources. Furthermore, our technique makes no use of the performance counters, which reduces its overhead, and works seamlessly with dynamic voltage and frequency scaling. We implement our technique on a real multi-core CPU-GPU processor-based system, and we show the ability to identify the runtime power consumption of the individual cores using just the total power measurement and the measurements of the thermal sensors under different workloads. We also verify the superior accuracy of our approach using results from a controlled simulation environment.