Application-level Prediction of Program Power Dissipation
UCSB Technical Report #2002-10
Rich Wolski, Chandra Krintz, and Ye Wen
Abstract
In this paper, we investigate the degree to which power dissipation
induced by program execution can be measured and predicted by
application-level software tools. Application control of the power
it uses while executing on a processor is critical to both the next
generation of super-dense machine architectures (e.g. IBM Blue Gene)
and battery-powered mobile devices that are an integral to any
realization of ubiquitous computing.
Our work investigates the use of instruction-level power dissipation
measurements to make whole-program power-consumption estimates and
statistical techniques that predict battery death strictly from
observed dissipation history. We demonstrate the prediction accuracy
associated with each approach. As such, this work establishes an
initial set of bounds on the accuracy with which software power management
tools can expect to predict application power dissipation.