Abstract

This dissertation addresses challenges in balancing performance and power/energy consumption in computing systems. Systems are often underutilized, meaning applications do not require all of a system's resources in order to achieve desired behavior, eg, an application performance goal or reasonable system energy consumption. Modern systems expose knobs for tuning resources, like processor frequency or core allocation, which have a quantifiable impact on application performance and system power consumption. The result is a tradeoff space that can be navigated by resource schedulers to achieve desired behavior, sacrificing one dimension in favor of another, eg, increased performance at the cost of increased power or energy consumption. The optimal knob settings required to achieve desired behavior depend on both the application and system, even changing during the course of execution as …

Date

2018

Authors

Connor Kelly Imes

Institution

The University of Chicago