Energy efficient online scheduling of aperiodic real time task on large multi-threaded multiprocessor systems
Manojit Ghose, Aryabartta Sahu, Sushanta Karmakar · 2016
In recent time, reduction of energy consumption has become an important issue as compared to minimizing execution time, specially in large multi-threaded multiprocessor systems where compute capability is sufficiently high. In such large systems, energy aware scheduling using only low level power constructs like DVFS technique may not be suitable and thus designing energy efficient scheduling techniques becomes essential which use power constructs at a higher granularity. In this paper, we have derived a simple power model designed at a higher granularity for such large systems having multi-threaded processors. We have proposed an online task scheduling policy namely, smart allocation policy for scheduling aperiodic real time tasks onto large multi-threaded multiprocessor systems to reduce overall energy consumption of the system without missing deadline of any task. We have analyzed the instantaneous power consumption and the overall energy consumption of the proposed task allocation policy along with other five baseline policies for a wide variety of synthetic data sets and real trace data. Experimental results show that our proposed policy achieves an average energy reduction of 60% (maximum up to 92%) for synthetic data set and 30% (maximum up to 45%) for real data sets as compared to baseline policies.