Abstract
Thermal issues in microprocessors have become a major design constraint because of their adverse effects on the reliability, performance and cost of the system. This article proposes an improvement in earliest deadline first, a uni-processor scheduling algorithm, without compromising its optimality in order to reduce the thermal peaks and variations. This is done by introducing a factor of fairness to earliest deadline first algorithm, which introduces idle intervals during execution and allows uniform distribution of workload over the time. The technique notably lowers the number of context switches when compare with the previous thermal-aware scheduling algorithm based on the same amount of fairness. Although, the algorithm is proposed for uni-processor environment, it is also applicable to partitioned scheduling in multi-processor environment, which primarily converts the multi-processor scheduling problem to a set of uni-processor scheduling problem and thereafter uses a uni-processor scheduling technique for scheduling. The simulation results show that the proposed approach reduces up to 5% of the temperature peaks and variations in a uni-processor environment while reduces up to 7% and 6% of the temperature spatial gradient and the average temperature in multi-processor environment, respectively.
Highlights
With the innovation in complementary metal oxide semiconductor (CMOS) technology, the size of the chip is constantly decreasing
We address the problem of scheduling for a set of real-time periodic tasks over a single and multi-processor system while minimizing the temperature peaks and variations without missing the deadlines
We propose a modification in earliest deadline first (EDF), the most successful optimal algorithm in uni-processor environment to address the thermal issues without disturbing the optimality of the algorithm
Summary
With the innovation in complementary metal oxide semiconductor (CMOS) technology, the size of the chip is constantly decreasing. Bashir et al.[13] present a thermal-aware technique using the principal of load balancing that addresses the thermal emergencies while reducing the switching time between the cores This is done by estimating the temperature patterns based on the recorded thermal history of similar task sets. Iranfar et al.[20] propose a scheduling technique to avoid thermal emergencies in multi-core systems In this approach, core consolidation and deconsolidation is performed by considering power and peak temperature. In the extension of their work, Ahmed et al.[22] derive the sufficient and necessary condition for thermal feasibility on a single-core system and extended some results on a multi-core system They proposed that if the computational and thermal utilization is less than or equal to 1, a schedule is possible where all the tasks meet their deadlines without avoiding temperature thresholds using a global positioning system (GPS)-inspired fluidscheduling algorithm. P//htlÀ=e10mXa(xSim, l)umis value of Us is 1 i.e. Us ł total executed time units
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