Dynamic power management approaches based on neural network

SEMI OpenIR > 中国科学院半导体研究所（2009年前）

	Dynamic power management approaches based on neural network
	Lu, HX; Lu, Y; Tang, ZF; Wang, SJ; Lu, HX, Chinese Acad Sci, Inst Semicond, Neural Network Lab, Beijing 100083, Peoples R China.
	2007
会议名称	1st International Conference Bio-Inspired Computing -Theory and Applications
会议录名称	DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS
页码	14: 334-340 Part 1 Suppl
会议日期	SEP 18-22, 2006
会议地点	Wuhan, PEOPLES R CHINA
出版地	C/O DCDIS JOURNAL, 317 KAREN PLACE, WATERLOO, ONTARIO N2L 6K8, CANADA
出版者	WATAM PRESS
ISSN	1492-8760
部门归属	[lu, huaxiang; lu, yan; tang, zhifang; wang, shoujue] chinese acad sci, inst semicond, neural network lab, beijing 100083, peoples r china
摘要	Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system. by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level policies. We proposed two PAY policies-Back propagation Power Management (BPPM) and Radial Basis Function Power management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79,145,1.18-competitive separately for traditional timeout PM, adaptive predictive PM and stochastic PM.
关键词	System
学科领域	人工智能
主办者	作者关键词: power management; BPPM; RBFPM
收录类别	CPCI-S
语种	英语
文献类型	会议论文
条目标识符	http://ir.semi.ac.cn/handle/172111/7878
专题	中国科学院半导体研究所（2009年前）
通讯作者	Lu, HX, Chinese Acad Sci, Inst Semicond, Neural Network Lab, Beijing 100083, Peoples R China.
推荐引用方式 GB/T 7714	Lu, HX,Lu, Y,Tang, ZF,et al. Dynamic power management approaches based on neural network[C]. C/O DCDIS JOURNAL, 317 KAREN PLACE, WATERLOO, ONTARIO N2L 6K8, CANADA:WATAM PRESS,2007:14: 334-340 Part 1 Suppl.