IEEE Transactions on Emerging Topics in Computing · 2020 · 22 citations · 32 references
EngineeringComputer EngineeringComputer ScienceEmbedded SystemsFault ToleranceFault-tolerant ComputingEmbedded Systems DesignPower ManagementPower-aware DesignReal-time SchedulingReliable System DesignSoft Real-time SystemsMulticore ArchitecturesMulticore Embedded SystemsMulticore SystemsPower ConsumptionPower-aware SchedulingScheduling With Reliability ConstraintsSoft Real-time SchedulingTransient Faults
Increasing power densities in future technology nodes is a crucial issue in multicore platforms. As the number of cores increases in them, power budget constraints may prevent powering all cores simultaneously at full performance level. Therefore, chip manufacturers introduce a power budget constraint as Thermal Design Power (TDP) for chips. Meanwhile, multicore platforms are suitable for the implementation of fault-tolerance techniques to achieve high reliability. Task Replication is a well-known technique to tolerate transient faults. However, careless task replication may lead to significant peak power consumption. In this article, we consider the problem of achieving a given reliability target while keeping the total power consumption under the chip TDP for a set of periodic soft real-time tasks. For this purpose, we propose a method for mapping and scheduling periodic soft real-time tasks in multicore embedded systems. The proposed method consists of three parts: ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> ) Reliability-Aware Lowest Utilization Mapping, ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii</i> ) Maximum-Power-Aware EDF Scheduling, and ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">iii</i> ) Reliability-and-Peak-Power-Aware Dynamic-Voltage-Frequency-Scaling. Our experiments show that our proposed method provides up to 38.4 percent (on average by 25 percent) peak power reduction compared to state-of-the-art methods.
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