By Suet-Fei Li, Roy Sutton, Jan Rabaey (auth.), Luca Benini, Mahmut Kandemir, J. Ramanujam (eds.)
Compilers and working platforms for Low Power specializes in either application-level compiler directed strength optimization and low-power working platforms. Chapters were written completely for this quantity via numerous of the best researchers and alertness builders energetic within the box. the 1st six chapters concentrate on low power working platforms, or extra regularly, energy-aware middleware providers. the subsequent 5 chapters are founded on compilation and code optimization. ultimately, the final bankruptcy takes a extra common standpoint on cellular computing. the fabric demonstrates the cutting-edge paintings and proves that to procure the easiest energy/performance features, compilers, procedure software program, and structure needs to interact. the connection among energy-aware middleware and instant microsensors, cellular computing and different instant purposes are covered.
This paintings might be of curiosity to researchers within the parts of low-power computing, embedded structures, compiler optimizations, and working platforms.
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4), the total consumption energy is improved by our algorithm. This difference in energy is due to the use of the idle time to reduce the processor speed in different instants during the hyper-period. To test our algorithm, we have also performed several experiments using 100 different synthetic task sets for each experiment. All tasks sets are formed by 10 schedulable periodic tasks, and for each task, we vary from 10% to 100% of the WCET consumption. In all the experiments, we check how harmonicity could affect the results, using harmonic task set and nonharmonic task set, and we also check how workload could change the results varying both the workload of the system, and the tasks workload.
Each box represent five time units (although our minimal calculation unit corresponds to 1 time unit), and each line corresponds to task T I, T2 and T3 respectively. The shaded circle s represent idle time in the system. , the tasks use all available time. 1. 3, we have represented the behavior of LPFPS. The LPFPS algorithm is driven by pre-emptive fixed-priority scheduling. This algor ithm 25 A Modified Dual-Priority Scheduling Algorithm consists of executing tasks as slow as possible while satisfying time constraints.
7. Comparison of both algorithms in the task set proposed by Shin and Choi  4. Experimental Results In order to evaluate the capabilities of the PLMDP approach, we have simulated several task sets (synthetic and real) and compared the total energy results per hyper-period obtained with those of the Low-Power A Modified Dual-Priority Scheduling Algorithm 29 Fixed-Priority Scheduling (LPFPS) proposed by Shin and Choi . 7. In the experiment we vary the percentage of consumption of the worst case execution time (WCET) of tasks to better analyze the performance in different situations.
Compilers and Operating Systems for Low Power by Suet-Fei Li, Roy Sutton, Jan Rabaey (auth.), Luca Benini, Mahmut Kandemir, J. Ramanujam (eds.)