Power-agility metrics: Measuring dynamic characteristics of energy proportionality

There has been a recent call for energy proportional systems that consume power proportional to its usage. However, these systems are only theoretical. In order to achieve system-level energy proportionality, effective energy management algorithms are needed that can tune each individual component of the system dynamically in response to usage. We define the ability of a system to detect, select and transition to efficient power settings dynamically during the execution of applications as Power-Agility. However, there are no metrics available that can measure how well the device is achieving Power-Agility, guide designers on how to make better system components and management algorithms. We present two metrics, Selection Power Agility and Transition Power Agility that measure the ability of the systems to select the efficient power settings and transition to the selected settings respectively. We study the Power-Agility of various representative algorithms and modeled devices for SPEC2006 benchmarks. Our results show that the Power-Agility of systems across algorithms varies with applications. We also show that both the discrete power settings and the transition latencies of the devices have an impact on system's Power-Agility.