Committee:

Dr. Bonnie Ferri, ECE, Chair , Advisor

Dr. Abhijit Chatterjee, ECE

Dr. Sudhakar Yalamanchili, ECE

Dr. Linda Wills, ECE

Dr. Aldo Ferri, ME

Abstract:

This research describes a system for proactive management of power and performance trade-offs through greater cooperation between applications and hardware. To enable such a management system, a software framework for application-guided power-aware control systems was developed. This system allows an application to guide the underlying computing hardware through a reusable and modular software abstraction. The abstraction layer enables an application to avoid hardware-specific details while still requesting resources from the computing hardware using a generic quality-of-service (QoS) interface. The computing system, in turn, monitors its power and performance state and notifies the application to adjust its computational load by changing its algorithms. This two-way communication between application and computing platform allows both application and system designers to create proactive strategies for managing power and performance states. The work as a whole describes mechanisms for system state estimation, prediction and management; introduces speculative threads for transient management in switched systems; and develops in detail two methods for power and performance management: a situational-aware governor and a Q-Learner-based quality-of-service manager.