Dynamic power management approaches based on neural network
Data(s) |
2007
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Resumo |
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. 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. zhangdi于2010-03-09批量导入 Made available in DSpace on 2010-03-09T02:11:59Z (GMT). No. of bitstreams: 0 Previous issue date: 2007 作者关键词: power management; BPPM; RBFPM [Lu, Huaxiang; Lu, Yan; Tang, Zhifang; Wang, Shoujue] Chinese Acad Sci, Inst Semicond, Neural Network Lab, Beijing 100083, Peoples R China 作者关键词: power management; BPPM; RBFPM |
Identificador | |
Idioma(s) |
英语 |
Publicador |
WATAM PRESS C/O DCDIS JOURNAL, 317 KAREN PLACE, WATERLOO, ONTARIO N2L 6K8, CANADA |
Fonte |
Lu, HX ; Lu, Y ; Tang, ZF ; Wang, SJ .Dynamic power management approaches based on neural network .见:WATAM PRESS .DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS ,C/O DCDIS JOURNAL, 317 KAREN PLACE, WATERLOO, ONTARIO N2L 6K8, CANADA ,2007,14: 334-340 Part 1 Suppl |
Palavras-Chave | #人工智能 #SYSTEM |
Tipo |
会议论文 |