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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Vydané v:IEEE transactions on parallel and distributed systems Ročník 19; číslo 11; s. 1540 - 1552
Hlavní autori: Seo, Euiseong, Jeong, Jinkyu, Park, Seonyeong, Lee, Joonwon
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.11.2008
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
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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Shrnutí: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.
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ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2008.104