DocumentCode :
2673357
Title :
Energy-efficient scheduling algorithm of task dependent graph on DVS-Unable cluster system
Author :
Ma, Yan ; Gong, Bin ; Zou, Lida
Author_Institution :
Sch. of Comput. Sci. & Technol., Shandong Univ., Jinan, China
fYear :
2009
fDate :
13-15 Oct. 2009
Firstpage :
217
Lastpage :
224
Abstract :
At present, energy-efficient scheduling algorithm in High-Performance Computing (HPC) environment is becoming a research hotspot owning to its high operation cost and low reliability. In this paper, we investigate energy-efficient scheduling algorithm of data dependent tasks in DVS-Unable cluster system. The proposed ESTD algorithm efficiently integrates task clustering with task duplication technologies to reduce data transmission time and communication energy consumption. In order to decrease the static power of processing elements, it also uses one of the power-saving techniques in system level - Dynamic Power Management on the premise that application execution is non-preemptive and predictive. ESTD algorithm not only optimizes the makespan of task dependent graph, but also confines its energy consumption into a certain extent. Compared with EAD algorithm and PEBD algorithm, experimental results and case studies demonstrate that ESTD algorithm can reduce more energy consumption while not affecting scheduling performance of applications.
Keywords :
graph theory; power aware computing; scheduling; workstation clusters; DVS-Unable cluster system; application execution; communication energy consumption; data dependent tasks; data transmission time; dynamic power management; energy-efficient scheduling; high-performance computing environment; power saving techniques; task clustering; task dependent graph; task duplication; Clustering algorithms; Costs; Data communication; Energy consumption; Energy efficiency; Energy management; Power system management; Power system reliability; Prediction algorithms; Scheduling algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Grid Computing, 2009 10th IEEE/ACM International Conference on
Conference_Location :
Banff, AB
Print_ISBN :
978-1-4244-5148-7
Electronic_ISBN :
978-1-4244-5149-4
Type :
conf
DOI :
10.1109/GRID.2009.5353056
Filename :
5353056
Link To Document :
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