Treffer: Speed Scaling on Parallel Processors

Title:
Speed Scaling on Parallel Processors
Authors:
ALBERS, Susanne, MÜLLER, Fabian, SCHMELZER, Swen
Source:
Algorithmica. 68(2):404-425
Publisher Information:
Heidelberg: Springer, 2014.
Publication Year:
2014
Physical Description:
print, 30 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Logiciel, Software, Traitement des langages et microprogrammation, Language processing and microprogramming, Systèmes informatiques et systèmes répartis. Interface utilisateur, Computer systems and distributed systems. User interface, Algorithme approximation, Approximation algorithm, Algoritmo aproximación, Algorithme en ligne, Online algorithm, Algoritmo en línea, Complexité calcul, Computational complexity, Complejidad computación, Consommation énergie, Energy consumption, Consumo energía, Date limite, Deadline, Fechas últimas, Economies d'énergie, Energy savings, Ahorros energía, Gestion énergie, Energy management, Gestión energía, Machine unique, Single machine, Máquina única, Microprocesseur, Microprocessor, Microprocesador, Multiprocesseur, Multiprocessor, Multiprocesador, Ordonnancement, Scheduling, Reglamento, Problème NP difficile, NP hard problem, Problema NP duro, Système exploitation, Operating system, Sistema operativo, Temps polynomial, Polynomial time, Tiempo polinomial, Vitesse variable, Varying speed, Velocidad variable, Algorithme compétitif, Competitive algorithms, Algoritmo Competitivo, Dynamic speed scaling, Energy efficiency, NP-hardness
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Computer Science, Humboldt Universität zu Berlin, 10099 Berlin, Germany
Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 79, 79110 Freiburg, Germany
ISSN:
0178-4617
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=28568817
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.28568817
Database:
PASCAL Archive

Weitere Informationen

In this paper we investigate dynamic speed scaling, a technique to reduce energy consumption in variable-speed microprocessors. While prior research has focused mostly on single processor environments, in this paper we investigate multiprocessor settings. We study the basic problem of scheduling a set of jobs, each specified by a release date, a deadline and a processing volume, on variable-speed processors so as to minimize the total energy consumption. We first settle the problem complexity if unit size jobs have to be scheduled. More specifically, we devise a polynomial time algorithm for jobs with agreeable deadlines and prove NP-hardness results if jobs have arbitrary deadlines. For the latter setting we also develop a polynomial time algorithm achieving a constant factor approximation guarantee. Additionally, we study problem settings where jobs have arbitrary processing requirements and, again, develop constant factor approximation algorithms. We finally transform our offline algorithms into constant competitive online strategies.