System-Level Techniques for Temperature-Aware Energy Optimization
Licentiate Thesis No. 1459, Dept. of Computer and Information Science, Linköping University, December 2010 (Opponent: Junior Professor Jian-Jia Chen, Karlsruhe Institute of Technology, Germany)
Junior Professor Jian-Jia Chen, Karlsruhe Institute of Technology, Germany
Energy consumption has become one of the main design constraints in today’s integrated circuits. Techniques for energy optimization, from circuit-level up to system-level, have been intensively researched.
The advent of large-scale integration with deep sub-micron technologies has led to both high power densities and high chip working temperatures. At the same time, leakage power is becoming the dominant power consumption source of circuits, due to continuously lowered threshold voltages, as technology scales. In this context, temperature is an important parameter. One aspect, of particular interest for this thesis, is the strong inter-dependency between leakage and temperature. Apart from leakage power, temperature also has an important impact on circuit delay and, implicitly, on the frequency, mainly through its influence on carrier mobility and threshold voltage. For power-aware design techniques, temperature has become a major factor to be considered. In this thesis, we address the issue of system-level energy optimization for real-time embedded systems taking temperature aspects into consideration.
We have investigated two problems in this thesis: (1) Energy optimization via temperature-aware dynamic voltage/frequency scaling (DVFS). (2) Energy optimization through temperature-aware idle time (or slack) distribution (ITD). For the above two problems, we have proposed off-line techniques where only static slack is considered. To further improve energy efficiency, we have also proposed online techniques, which make use of both static and dynamic slack. Experimental results have demonstrated that considerable improvement of the energy efficiency can be achieved by applying our temperature-aware optimization techniques. Another contribution of this thesis is an analytical temperature analysis approach which is both accurate and sufficiently fast to be used inside an energy optimization loop.
[B10] Min Bao, "System-Level Techniques for Temperature-Aware Energy Optimization", Licentiate Thesis No. 1459, Dept. of Computer and Information Science, Linköping University, December 2010 (Opponent: Junior Professor Jian-Jia Chen, Karlsruhe Institute of Technology, Germany)