Copyright by William Lloyd Bircher 2010 - The Laboratory for ...

performance loss and power consumption can be minimized through careful selection of
hardware adaptation and software control parameters. In the case of Microsoft Windows
Vista running desktop workloads, performance loss using a naïve operating system
configuration is less than 8 percent on average for all workloads while saving an average
of 45 percent power. Using an optimized operating system configuration, performance
loss drops to less than 2 percent with power savings of 30 percent.
While the results attained through optimizing a reactive operating system power
adaptation are promising, further improvement can be achieved through new approaches.
The existing adaptations algorithms have several limitations including poor response to
phase changes and a lack of process awareness and frequency-sensitivity. The ability to
increase the responsiveness of the reactive algorithm is limited since excessive
adaptations reduce performance and increase energy consumption. To attain higher
performance and efficiency, a predictive adaptation is required. Predictive adaptation
effectively provides the responsiveness of a maximally reactive scheme without the
overhead of excessive adaptation.
Another limitation is the lack of frequency-sensitivity awareness in current algorithms.
To make best use of dynamic processor voltage and frequency scaling, the sensitivity of a
workload to frequency should be accounted. By knowing the frequency sensitivity,
workloads which do not benefit from high frequency could achieve much lower power.
Similarly, workloads that scale well with frequency can attain higher performance by
avoiding the use of excessively low frequencies.
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