TY - GEN
T1 - Energy-efficient scheduling of real-time tasks on cluster-based multicores
AU - Kong, Fanxin
AU - Yi, Wang
AU - Deng, Qingxu
PY - 2011
Y1 - 2011
N2 - While much work has addressed the energy-efficient scheduling problem for uniprocessor or multiprocessor systems, little has been done for multicore systems. We study the multicore architecture with a fixed number of cores partitioned into clusters (or islands), on each of which all cores operate at a common frequency. We develop algorithms to determine a schedule for real-time tasks to minimize the energy consumption under the timing and operating frequency constraints. As technical contributions, we first show that the optimal frequencies resulting in the minimum energy consumption for each island is not dependent on the workload mapped but the number of cores and leakage power on the island, when not considering the timing constraint. Then for systems with timing constraints, we present a polynomial algorithm which derives the minimum energy consumption for a given task partition. Finally, we develop an efficient algorithm to determine the number of active islands, task partition and frequency assignment. Our simulation result shows that our approach significantly outperforms the related approaches in terms of energy saving.
AB - While much work has addressed the energy-efficient scheduling problem for uniprocessor or multiprocessor systems, little has been done for multicore systems. We study the multicore architecture with a fixed number of cores partitioned into clusters (or islands), on each of which all cores operate at a common frequency. We develop algorithms to determine a schedule for real-time tasks to minimize the energy consumption under the timing and operating frequency constraints. As technical contributions, we first show that the optimal frequencies resulting in the minimum energy consumption for each island is not dependent on the workload mapped but the number of cores and leakage power on the island, when not considering the timing constraint. Then for systems with timing constraints, we present a polynomial algorithm which derives the minimum energy consumption for a given task partition. Finally, we develop an efficient algorithm to determine the number of active islands, task partition and frequency assignment. Our simulation result shows that our approach significantly outperforms the related approaches in terms of energy saving.
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M3 - Conference contribution
AN - SCOPUS:79957537193
SN - 9783981080179
T3 - Proceedings -Design, Automation and Test in Europe, DATE
SP - 1135
EP - 1140
BT - Proceedings - Design, Automation and Test in Europe Conference and Exhibition, DATE 2011
T2 - 14th Design, Automation and Test in Europe Conference and Exhibition, DATE 2011
Y2 - 14 March 2011 through 18 March 2011
ER -