abstract.tex
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\begin{abstract}
Battery lifetime continues to be a top complaint about smartphones. Dynamic
voltage and frequency scaling (DVFS) has existed for mobile device CPUs for
some time, and can be used to dynamically trade off energy for performance.
To make more energy-performance tradeoffs possible, DVFS is beginning to be
applied to memory as well.
We present the first characterization of the behavior and optimal frequency
settings of workloads running both under \textit{energy constraints} and on
systems with \textit{both} CPU and memory DVFS, an environment representative
of next-generation mobile devices. Our results show that continuously using
the optimal frequency settings results in a large number of frequency
transitions which end up hurting performance. However, by permitting a small
loss in performance, transition overhead can be reduced and end-to-end
performance and energy consumption improved. We introduce the idea of
\textit{inefficiency} as a way of constraining task energy consumption
relative to the most energy-efficient settings, and characterize the
performance of multiple workloads running under different inefficiency
settings. Overall our results have multiple implications for next-generation
mobile devices exposing multiple energy-performance tradeoffs.
\end{abstract}