D.1 PROGRAMMING TECHNIQUES (E)
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Institute
Electrical energy is the single most important operating resource to computer systems. Although the energy demand of computers is an invisible system property by itself, the impact of energy demand is omnipresent and obvious in manifold forms of appearance. Sudden system failures (i.e., system breakdowns) and recurrent standard system operations (i.e., system charging) serve as practical examples. Energy demand of hardware components is a physical property of integrated transistor circuits that build our computers today. However, dynamic energy demand at the hardware level is caused by system activities (i.e., processes) at the software level. The analysis and improvement of system software is in focus due to the causal relationship: system software yields challenges and opportunities in equal measure in order to reduce the energy demand of the system at the hardware level. In particular, fine-tuning of system components offers distinct measures to improve the energy efficiency of computer systems. Improvements concern the coherent design of application and system software under consideration of hardware aspects.
This thesis presents, implements, and evaluates unique concepts for proactive energy-aware computing on energy-efficient systems-on-a-chip. In particular, it contributes a development method for energy-aware programming that originates in static and dynamic program analysis to support programmers at the design of energy-aware programs. To assist programmers in reducing the energy demand of their programs, the thesis proposes a software-hardware tooling infrastructure that combines energy-aware programming techniques with automatised energy demand analysis at system level. To further reduce the energy demand of computer systems, the thesis implements a process executive at the operating-system level that exploits a priori information at run time to reduce the energy demand of processes. The corresponding cross-layer approach enables the transfer of programmers’ knowledge to the operating system to reduce the energy demand at run time.
The thesis is first to combine dynamic program analysis techniques and the automatic creation of program variants to support energy-aware programming at the operating-system level. The distinct combination of application knowledge to identify and set important adjusting screws for the energy efficient operation of a computing system bound to an operating system is claimed to be novel.