Title :
Energy saving task scheduling for heterogeneous CMP system based on multi-objective fuzzy genetic algorithm
Author :
Miao, Lei ; Qi, Yong ; Hou, Di ; Wu, Chang-Li ; Dai, Yue-Hua
Author_Institution :
Sch. of Electron. & Inf. Eng., Xi´´an Jiaotong Univ., Xi´´an, China
Abstract :
With the chip multi-processor (CMP) being more and more widespread used in the laptop, desktop and data center area, the power-performance scheduling issues are becoming challenges to the researchers. In this paper, we propose a multi-objective fuzzy genetic algorithm to optimize the energy saving scheduling tasks on heterogeneous CMP system. According to the characteristic of heterogeneous CMP system, we present a novel encoding and decoding scheme of genetic algorithm, improve the crossover operator and the mutation operator. Based on that, we improve the genetic algorithm architecture by using the relative fuzzy membership grade fitness and the elitist strategy. Simulation results demonstrate that using our algorithm can save both the execution time and system energy cost at the same time.
Keywords :
fuzzy set theory; genetic algorithms; microprocessor chips; power aware computing; processor scheduling; crossover operator; energy saving task scheduling; fuzzy membership grade fitness; heterogeneous chip multiprocessor system; multiobjective fuzzy genetic algorithm; mutation operator; power-performance scheduling; Cybernetics; Dynamic voltage scaling; Energy consumption; Fuzzy systems; Genetic algorithms; Genetic mutations; Multiprocessing systems; Scheduling algorithm; System-on-a-chip; USA Councils; heterogeneous chip multi-processor; multi-objective optimal; task scheduling;
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
DOI :
10.1109/ICSMC.2009.5346656