Department of Information Technology
Uppsala Architecture Research Team

Power-Sleuth: A Tool for Investigating your Program's Power Behavior

Modern processors support aggressive power saving techniques to reduce energy consumption. However, traditional profiling techniques have mainly focused on performance, which does not accurately reflect the power behavior of applications. For example, the longest running function is not always the most energy-hungry function. Thus software developers cannot always take full advantage of these power-saving features.

We present \powersleuth, a power/performance estimation tool which is able to provide a full description of an application's behavior for any frequency from a single profiling run. The tool combines three techniques: a power and a performance estimation model with a program phase detection technique to deliver accurate, per-phase, per-frequency analysis.

Our evaluation (against real power measurements) shows that we can accurately predict power and performance across different frequencies with average errors of 3.5% and 3.9% respectively.

Predicted and measured power consumption for maximum and minimum frequency based on data from a maximum frequency run.
Predicted and measured power consumption for maximum and minimum frequency based on data from a maximum frequency run. Poster

Updated  2013-07-22 11:48:02 by David Black-Schaffer.