Energy Efficient Scheduling of Real-Time Tasks on Multicore Processors

Multicore processors deliver a higher throughput at lower power consumption than unicore processors. In the near future, they will thus be widely used in mobile real-time systems. There have been many research on energy-efficient scheduling of real-time tasks using DVS. These approaches must be modi...

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Veröffentlicht in:	IEEE transactions on parallel and distributed systems Jg. 19; H. 11; S. 1540 - 1552
Hauptverfasser:	Seo, Euiseong, Jeong, Jinkyu, Park, Seonyeong, Lee, Joonwon
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.11.2008 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Dynamics Energy consumption Energy efficiency Energy-aware systems Heuristic algorithms Loads (forces) Microprocessors Multi-core/single-chip multiprocessors Multicore processing Multiprocessing systems Partitioning Partitioning algorithms Power consumption Processor scheduling Processors Real time Real time systems Real-time systems and embedded systems Scheduling and task partitioning Studies Tasks Throughput Voltage control Scheduling and task partitioning Multi-core/single-chip multiprocessors Real-time systems and embedded systems Energy-aware systems
ISSN:	1045-9219, 1558-2183
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Abstract	Multicore processors deliver a higher throughput at lower power consumption than unicore processors. In the near future, they will thus be widely used in mobile real-time systems. There have been many research on energy-efficient scheduling of real-time tasks using DVS. These approaches must be modified for multicore processors, however, since normally all the cores in a chip must run at the same performance level. Thus, blindly adopting existing DVS algorithms that do not consider the restriction will result in a waste of energy. This article suggests Dynamic Repartitioning algorithm based on existing partitioning approaches of multiprocessor systems. The algorithm dynamically balances the task loads of multiple cores to optimize power consumption during execution. We also suggest Dynamic Core Scaling algorithm, which adjusts the number of active cores to reduce leakage power consumption under low load conditions. Simulation results show that Dynamic Repartitioning can produce energy savings of about 8 percent even with the best energy-efficient partitioning algorithm. The results also show that Dynamic Core Scaling can reduce energy consumption by about 26 percent under low load conditions.
AbstractList	Multicore processors deliver a higher throughput at lower power consumption than unicore pro- cessors. In the near future, they will thus be widely used in mobile real-time systems. There have been many research on energy-efficient scheduling of real-time tasks using DVS. These approaches must be modified for multicore processors, however, since normally all the cores in a chip must run at the same performance level. Thus blindly adopting existing DVS algorithms which do not consider the restriction will result in a waste of energy. This article suggests Dynamic Repartitioning algorithm based on existing partitioning approaches of multiprocessor systems. The algorithm dynamically balances the task loads of multiple cores to optimize power consumption during execution. We also suggest Dynamic Core Scaling algorithm which adjusts the number of active cores to reduce leakage power consumption under low load conditions. Simulation results show that Dynamic Repartitioning can produce energy savings of about 8% even with the best energy-efficient partitioning algorithm. The results also show that Dynamic Core Scaling can reduce energy consumption by about 26% under low load conditions. Multicore processors deliver a higher throughput at lower power consumption than unicore processors. In the near future, they will thus be widely used in mobile real-time systems. There have been many research on energy-efficient scheduling of real-time tasks using DVS. These approaches must be modified for multicore processors, however, since normally all the cores in a chip must run at the same performance level. Thus, blindly adopting existing DVS algorithms that do not consider the restriction will result in a waste of energy. This article suggests Dynamic Repartitioning algorithm based on existing partitioning approaches of multiprocessor systems. The algorithm dynamically balances the task loads of multiple cores to optimize power consumption during execution. We also suggest Dynamic Core Scaling algorithm, which adjusts the number of active cores to reduce leakage power consumption under low load conditions. Simulation results show that Dynamic Repartitioning can produce energy savings of about 8 percent even with the best energy-efficient partitioning algorithm. The results also show that Dynamic Core Scaling can reduce energy consumption by about 26 percent under low load conditions. Multicore processors deliver a higher throughput at lower power consumption than unicore pro- cessors. In the near future, they will thus be widely used in mobile real-time systems. There have been many research on energy-efficient scheduling [abstract truncated by publisher]. [...] blindly adopting existing DVS algorithms which do not consider the restriction will result in a waste of energy.
Author	Joonwon Lee Seonyeong Park Jinkyu Jeong Euiseong Seo
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SubjectTerms	Algorithms Dynamics Energy consumption Energy efficiency Energy-aware systems Heuristic algorithms Loads (forces) Microprocessors Multi-core/single-chip multiprocessors Multicore processing Multiprocessing systems Partitioning Partitioning algorithms Power consumption Processor scheduling Processors Real time Real time systems Real-time systems and embedded systems Scheduling and task partitioning Studies Tasks Throughput Voltage control
Title	Energy Efficient Scheduling of Real-Time Tasks on Multicore Processors
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