Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/69314
Title: An energy-aware gradient-based scheduling heuristic for heterogeneous multiprocessor embedded systems
Authors: Gob, L.K.
Veeravalli, B. 
Viswanathan, S.
Keywords: Dynamic voltage scaling
Embedded systems
Energy-aware scheduling
Heterogeneous multiprocessor
Power management
Issue Date: 2007
Source: Gob, L.K.,Veeravalli, B.,Viswanathan, S. (2007). An energy-aware gradient-based scheduling heuristic for heterogeneous multiprocessor embedded systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4873 LNCS : 331-341. ScholarBank@NUS Repository.
Abstract: In this paper, we propose a heuristic static energy-aware scheduling algorithm for scheduling tasks with precedence constraints on a heterogeneous multiprocessor embedded system consisting of processing elements equipped with dynamic voltage scaling capabilities. While most energy-aware scheduling algorithms in the literature assume that the mapping of the tasks to the processors is known and consider only task ordering and voltage scaling, our algorithm takes into considerar tion all three factors using the concept of energy gradient. Higher values of energy gradient result in larger reduction in the energy consumption together with smaller increase in the makespan of the schedules. We compare our algorithm to a genetic algorithm in the literature and show that although our algorithm does not consider intrartask voltage scaling, it still provides an average energy savings of about 4% while reducing the optimization time by more than 93%. These energy savings are more significant for larger task graphs. © Springer-Verlag Berlin Heidelberg 2007.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/69314
ISBN: 9783540772194
ISSN: 03029743
Appears in Collections:Staff Publications

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