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

proportional to the amount of frequency change (seconds/MHz). Other architecture-
specific adaptations may have variable costs per transition. For example, powering down
a cache requires modified contents to be flushed to the next higher level of memory. This
reduces performance and may increase power consumption due to the additional bus
traffic. When a predictive component is powered down it no longer records program
behavior. For example, if a branch predictor is powered down during a phase in which
poor predictability is expected, then branch behavior is not recorded. If the phase
actually contains predictable behavior, then performance may be lost and efficiency may
be lost. If a unit is powered on and off in excess of the actual program demand, then
power and performance may be significantly affected by the flush and warm-up cycles of
the components. In this study the focus is on fixed cost per transition effects such as
those required for voltage and frequency changes.
6.1.2 Workload Phase and Policy Costs
In the ideal case the transition costs described above do not impact performance and save
maximum power. The reality is that performance of dynamic adaption is greatly affected
by the nature of workload phases and the power manager’s policies. Adaptations provide
power savings by setting performance to the minimum level required by the workload. If
the performance demand of a workload were known in advance, then setting performance
levels would be trivial. Since they are not known, the policy manager must estimate
future demand based on the past. Existing power managers, such as those used in this
study (Windows Vista [Vi07] and SLES Linux [PaSt06]), act in a reactive mode. They
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