By Suet-Fei Li, Roy Sutton, Jan Rabaey (auth.), Luca Benini, Mahmut Kandemir, J. Ramanujam (eds.)
Compilers and working structures for Low Power specializes in either application-level compiler directed strength optimization and low-power working structures. Chapters were written completely for this quantity by way of a number of of the top researchers and alertness builders energetic within the box. the 1st six chapters specialise in low strength working platforms, or extra more often than not, energy-aware middleware companies. the following 5 chapters are established on compilation and code optimization. eventually, the final bankruptcy takes a extra common standpoint on cellular computing. the fabric demonstrates the cutting-edge paintings and proves that to procure the simplest energy/performance features, compilers, method software program, and structure needs to interact. the connection among energy-aware middleware and instant microsensors, cellular computing and different instant functions are covered.
This paintings may be of curiosity to researchers within the parts of low-power computing, embedded structures, compiler optimizations, and working structures.
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26] when tasks consumption is 50% of their WCET. These differences in energy consumption between both algorithms are practically constant when varying the workload of the system. 9. System workload variation when all tasks consume the 100% ofWCET. t! 10. 11, note that the normalized energy consumption is represented on a logarithmic scale, so we can compare the improvement of energy consumption of our algorithm (PLMDP) with that of LPFPS, when all tasks consume 50% of the WeET, in two different situations: (i) when the task periods are harmonic (LPFPS-h, PLMDP-h), and (ii) when the task periods are non-harmonic.
20 COMPILERS AND OPERATING SYSTEMS FOR LOW POWER The system is organized as a set of concurrent tasks managed by a preemptive priority-based scheduler whose details are described below . The computation times for context switching and for the scheduler are assumed to be negligible; this enables us to perform the analysis in a straightforward manner without the danger of loss of generality. The extent to which these assumptions are realistic is discussed in the analysis of the algorithm given in , and it turns out to be practical if the context switching time is subsumed by the worst case execution times of the different tasks .
This amount d can be obtained through a variety of scheduling disciplines, such as EDF, RMS, and CBS (based on task utilization), as well as fair-share and other resource allocation techniques that guarantee a certain CPU usage for each task (called resource protection or resource isolation). We will refer to the quantity d as the task deadline. In this initial work, we consider the sequential form of program execution, where a program can be divided into n segments of equal length , to determine an optimal number of PMPs.