Dynamic power management using machine learning

IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD

Volumn , Issue , 2006, Pages 747-754

  Dhiman, Gaurav ^a   Rosing, Tajana Simunic ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Dynamic power management; Machine learning

Indexed keywords

(R ,S ,S) POLICY; COMPUTER-AIDED DESIGN; CONVERGENCE (MATHEMATICS); DYNAMIC POWER MANAGEMENT (DPM); HARD DISK DRIVE (HDD); INTERNATIONAL CONFERENCES; LOW POWER STATES; MACHINE LEARNING ALGORITHMS; MACHINE-LEARNING; OVERALL PERFORMANCE; STATE OF THE ARTS; WORKLOAD CHARACTERISTICS;

ARTIFICIAL INTELLIGENCE; BOOLEAN FUNCTIONS; DESIGN; ELECTRIC POWER MEASUREMENT; EMBEDDED SYSTEMS; ENERGY MANAGEMENT; HARD DISK STORAGE; LEARNING SYSTEMS; LOCAL AREA NETWORKS; PHASE MEASUREMENT; ROBOT LEARNING; SET THEORY; WIRELESS LOCAL AREA NETWORKS (WLAN);

LEARNING ALGORITHMS;

EID: 46149096949     PISSN: 10923152     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCAD.2006.320115     Document Type: Conference Paper

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