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

Chapter 9 Conclusions and Future Work
9.1 Conclusions
The widespread application of dynamic power management has provided the opportunity
for computing systems to attain high performance and energy efficiency across a wide
range of workloads. Practically, systems do not operate optimally due to the lack of
effective, power management, control schemes. This is largely due to a lack of run-time
power accounting and the use of reactive power management on workloads with widely
varying performance and power characteristics. The objective of this dissertation is to
improve the effectiveness of dynamic power management by addressing these
limitations. This is achieved in the following contributions:
1) Fine-Grain Accounting of Complete System Power Consumption
Using a small set of widely available performance events including IPC, cache misses
and interrupts, power models are developed by measuring power consumption on actual
systems. These linear and polynomial models are created using regression techniques
that iteratively adjust coefficients to minimize model error. This novel approach
improves upon existing research by finding that complex structures such as processors
and chipsets can be accurately represented by tracking their dominant performance
events. Unlike existing research that primarily relies on retired instruction or
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