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

prediction scheme in this dissertation makes use of table-based prediction structures and
the repetitive nature of power phases to predict performance demand and/or power
consumption. Further, the validation of the predictor is performed using realistic,
representative workloads. These workloads contain complex power management events
that are not present in the simple workloads used in the contemporary research. These
events are critical to a practical power management schemed since they induce power and
performance effects larger than those seen in simple workloads.
Outside the predictive adaptation realm, there are numerous proposals for increasing
energy efficiency and staying within operating limits. To increase energy efficiency
studies have applied adaptation at the processor level [LiMa06] [LiBr05] [WuJu05]
[Vi07] [PaSt06] [KoGh05] [KoDe04] and system level [MeGo09] [RaLe03] [BoEl02].
To stay within defined operating limits studies have applied adaptation at the processor
level [HaKe07] [RaHa06] [ChJa09] [IsBu06] [McPo06] and complete system level
[LeWa07] [RaLe06] [ChDa05] [ChAn01] [Po10] [FaWe07] [WaCh08] [MiFr02].
8.4 Deadline and User-Driven Power Adaptation
In the embedded and real-time computing domains power management is performed
under a different set of requirements. Rather than focusing on reduction of average or
peak power, computation deadlines are more critical. These systems contain various
components and processes with critical deadlines for computation. For example, network
devices implement buffers to allow the network interface to queue transactions. This
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