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Task-Level Aware Scheduling of Energy-Constrained Applications on Heterogeneous Multi-Core System

1
Institute of VLSI Design, Zhejiang University, Hangzhou 310027, China
2
Digital Grid Research Institute, Artificial Intelligence and Chip Application Research Department, CSG, Guangzhou 510623, China
3
Electric Power Research Institute, China Southern Power Grid (CSG), Guangzhou 510623, China
4
Hangzhou Sec-Chip Technology Co., Ltd., Hangzhou 310027, China
*
Author to whom correspondence should be addressed.
Electronics 2020, 9(12), 2077; https://doi.org/10.3390/electronics9122077
Received: 10 November 2020 / Revised: 1 December 2020 / Accepted: 3 December 2020 / Published: 5 December 2020
(This article belongs to the Section Computer Science & Engineering)
Minimizing the schedule length of parallel applications, which run on a heterogeneous multi-core system and are subject to energy consumption constraints, has recently attracted much attention. The key point of this problem is the strategy to pre-allocate the energy consumption of unscheduled tasks. Previous articles used the minimum value, average value or a power consumption weight value as the pre-allocation energy consumption of tasks. However, they all ignored the different levels of tasks. The tasks in different task levels have different impact on the overall schedule length when they are allocated the same energy consumption. Considering the task levels, we designed a novel task energy consumption pre-allocation strategy that is conducive to minimizing the scheduling time and developed a novel task schedule algorithm based on it. After getting the preliminary scheduling results, we also proposed a task execution frequency re-adjustment mechanism that can re-adjust the execution frequency of tasks, to further reduce the overall schedule length. We carried out a considerable number of experiments with practical parallel application models. The results of the experiments show that our method can reach better performance compared with the existing algorithms. View Full-Text
Keywords: heterogeneous multi-core system; energy consumption; task schedule length; task level; frequency re-adjustment heterogeneous multi-core system; energy consumption; task schedule length; task level; frequency re-adjustment
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MDPI and ACS Style

Huang, K.; Jing, M.; Jiang, X.; Chen, S.; Li, X.; Tao, W.; Xiong, D.; Liu, Z. Task-Level Aware Scheduling of Energy-Constrained Applications on Heterogeneous Multi-Core System. Electronics 2020, 9, 2077. https://doi.org/10.3390/electronics9122077

AMA Style

Huang K, Jing M, Jiang X, Chen S, Li X, Tao W, Xiong D, Liu Z. Task-Level Aware Scheduling of Energy-Constrained Applications on Heterogeneous Multi-Core System. Electronics. 2020; 9(12):2077. https://doi.org/10.3390/electronics9122077

Chicago/Turabian Style

Huang, Kai; Jing, Ming; Jiang, Xiaowen; Chen, Siheng; Li, Xiaobo; Tao, Wei; Xiong, Dongliang; Liu, Zhili. 2020. "Task-Level Aware Scheduling of Energy-Constrained Applications on Heterogeneous Multi-Core System" Electronics 9, no. 12: 2077. https://doi.org/10.3390/electronics9122077

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