Document Type
Dissertation
Degree
Doctor of Philosophy (PhD)
Major/Program
Electrical Engineering
First Advisor's Name
Gang Quan
First Advisor's Committee Title
Committee Chair
Second Advisor's Name
Nezih Pala
Third Advisor's Name
Jean H. Andrian
Fourth Advisor's Name
Cheng-Xian Lin
Fifth Advisor's Name
Raju Rangaswami
Keywords
Real-Time Scheduling, Power aware scheduling, thermal aware scheduling, embedded Systems, operating Systems, Scheduling
Date of Defense
3-26-2013
Abstract
Catering to society’s demand for high performance computing, billions of transistors are now integrated on IC chips to deliver unprecedented performances. With increasing transistor density, the power consumption/density is growing exponentially. The increasing power consumption directly translates to the high chip temperature, which not only raises the packaging/cooling costs, but also degrades the performance/reliability and life span of the computing systems. Moreover, high chip temperature also greatly increases the leakage power consumption, which is becoming more and more significant with the continuous scaling of the transistor size. As the semiconductor industry continues to evolve, power and thermal challenges have become the most critical challenges in the design of new generations of computing systems.
In this dissertation, we addressed the power/thermal issues from the system-level perspective. Specifically, we sought to employ real-time scheduling methods to optimize the power/thermal efficiency of the real-time computing systems, with leakage/ temperature dependency taken into consideration. In our research, we first explored the fundamental principles on how to employ dynamic voltage scaling (DVS) techniques to reduce the peak operating temperature when running a real-time application on a single core platform. We further proposed a novel real-time scheduling method, “M-Oscillations” to reduce the peak temperature when scheduling a hard real-time periodic task set. We also developed three checking methods to guarantee the feasibility of a periodic real-time schedule under peak temperature constraint. We further extended our research from single core platform to multi-core platform. We investigated the energy estimation problem on the multi-core platforms and developed a light weight and accurate method to calculate the energy consumption for a given voltage schedule on a multi-core platform. Finally, we concluded the dissertation with elaborated discussions of future extensions of our research.
Identifier
FI13042337
Recommended Citation
Chaturvedi, Vivek, "Leakage Temperature Dependency Aware Real-Time Scheduling for Power and Thermal Optimization" (2013). FIU Electronic Theses and Dissertations. 870.
https://digitalcommons.fiu.edu/etd/870
Latex Source files of the Dissertation
Rights Statement
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/
This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).