DocumentCode :
1678732
Title :
PSO Based Instruction Scheduling for Low Power
Author :
Nian, Chen ; Yanxiang, He ; Yong, Chen ; Ximi, Liao ; Qian, Liu
Author_Institution :
Sch. of Comput., Wuhan Univ., Wuhan, China
fYear :
2012
Firstpage :
519
Lastpage :
522
Abstract :
Power consumption has become an important issue in embedded system. Reducing the total number of signal transitions during each bus cycle has great effect on power consumption. In this paper, we proposed an instruction scheduling method which is based on the Particle Swarm Optimization (PSO) Algorithm to reduce the signal transitions. We formulate the low-power instruction scheduling problem to the constrained discrete PSO problem. And then we modify the PSO solution to satisfy the path constrained and find the better instruction schedule with litter signal transitions. For more effectively, we also improve the velocity updating formula to get the better result. The main contribution of our paper is that we use the improved PSO algorithm to find the better instructions sequence for low power quickly.
Keywords :
embedded systems; flow graphs; instruction sets; optimising compilers; particle swarm optimisation; power aware computing; processor scheduling; program control structures; PSO based instruction scheduling; bus cycle; compile optimizatiom; constrained discrete PSO problem; embedded system; instruction sequence; low-power instruction scheduling problem; particle swarm optimization; power consumption; program control flow graph; signal transition; velocity updating formula; Dynamic scheduling; Optimization; Particle swarm optimization; Processor scheduling; Signal processing algorithms; Software; Instruction Scheduling; Low Power; PSO;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2012 International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-1-4673-0458-0
Type :
conf
DOI :
10.1109/CDCIEM.2012.129
Filename :
6178527
Link To Document :
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