Schedule length minimization of parallel applications with energy consumption constraints using heuristics on heterogeneous distributed systems

2016 ◽  
Vol 29 (16) ◽  
pp. e4024 ◽  
Author(s):  
Guoqi Xie ◽  
Xiongren Xiao ◽  
Renfa Li ◽  
Keqin Li
Keyword(s):  
Energy Consumption ◽  
Distributed Systems ◽  
Parallel Applications ◽  
Schedule Length ◽  
Heterogeneous Distributed Systems ◽  
Consumption Constraints

Enhanced Parallel Application Scheduling Algorithm with Energy Consumption Constraint in Heterogeneous Distributed Systems

2019 ◽  
Vol 28 (11) ◽  
pp. 1950190 ◽  
Author(s):  
Jinghong Li ◽  
Guoqi Xie ◽  
Keqin Li ◽  
Zhuo Tang
Keyword(s):  
Energy Consumption ◽  
Distributed Systems ◽  
Gaussian Elimination ◽  
Scheduling Algorithm ◽  
Parallel Applications ◽  
Parallel Application ◽  
Heterogeneous Distributed Systems ◽  
Dynamic Voltage ◽  
Cluster Computer Systems ◽  
Consumption Constraints

Energy consumption has always been one of the main design problems in heterogeneous distributed systems, whether for large cluster computer systems or small handheld terminal devices. And as energy consumption explodes for complex performance, many efforts and work are focused on minimizing the schedule length of parallel applications that meet the energy consumption constraints currently. In prior studies, a pre-allocation method based on dynamic voltage and frequency scaling (DVFS) technology allocates unassigned tasks with minimal energy consumption. However, this approach does not necessarily result in minimal scheduling length. In this paper, we propose an enhanced scheduling algorithm, which allocates the same energy consumption for each task by selecting a relatively intermediate value among the unequal allocations. Based on the two real-world applications (Fast Fourier transform and Gaussian elimination) and the randomly generated parallel application, experiments show that the proposed algorithm not only achieves better scheduling length while meeting the energy consumption constraints, but also has better performance than the existing parallel algorithms.

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

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2077
Author(s):  
Kai Huang ◽  
Ming Jing ◽  
Xiaowen Jiang ◽  
Siheng Chen ◽  
Xiaobo Li ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Schedule Algorithm ◽  
Parallel Applications ◽  
Core System ◽  
Parallel Application ◽  
Average Value ◽  
Schedule Length ◽  
Energy Constrained ◽  
Execution Frequency ◽  
Consumption Constraints

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.

Energy-Efficient Scheduling Optimization for Parallel Applications on Heterogeneous Distributed Systems

2020 ◽  
Vol 29 (13) ◽  
pp. 2050203
Author(s):  
Nan Gao ◽  
Cheng Xu ◽  
Xin Peng ◽  
Haibo Luo ◽  
Wufei Wu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Distributed Systems ◽  
Energy Efficient ◽  
Gaussian Elimination ◽  
Task Assignment ◽  
Computation Time ◽  
Parallel Applications ◽  
Heterogeneous Distributed Systems ◽  
Static Energy ◽  
Energy Efficient Scheduling

Designing energy-efficient scheduling algorithms on heterogeneous distributed systems is increasingly becoming the focus of research. State-of-the-art works have studied scheduling by combining dynamic voltage and frequency scaling (DVFS) technology and turning off the appropriate processors to reduce dynamic and static energy consumptions. However, the methods for turning off processors are ineffective. In this study, we propose a novel method to assign priorities to processors for facilitating effective selection of turned-on processors to decrease static energy consumption. An energy-efficient scheduling algorithm based on bisection (ESAB) is proposed on this basis, and this algorithm directly turns on the most energy-efficient processors depending on the idea of bisection to reduce static energy consumption while dynamic energy consumption is decreased by using DVFS technology. Experiments are performed on fast Fourier transform, Gaussian elimination, and randomly generated parallel applications. Results show that our ESAB algorithm makes a better trade-off between reducing energy consumption and low computation time of task assignment (CTTA) than existing algorithms under different scale conditions, deadline constraints, and degrees of parallelism and heterogeneity.

Maximizing reliability of energy constrained parallel applications on heterogeneous distributed systems

2018 ◽  
Vol 26 ◽  
pp. 344-353 ◽  
Author(s):  
Xiongren Xiao ◽  
Guoqi Xie ◽  
Cheng Xu ◽  
Chunnian Fan ◽  
Renfa Li ◽  
...  
Keyword(s):  
Distributed Systems ◽  
Parallel Applications ◽  
Heterogeneous Distributed Systems ◽  
Energy Constrained
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