Probabilistic Backfilling
Backfilling is a scheduling optimization that requires information about job runtimes to be known. Such information can come from either of two sources: estimates provided by users when the jobs are submitted, or predictions made by the system based on hi
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Editorial Board David Hutchison Lancaster University, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M. Kleinberg Cornell University, Ithaca, NY, USA Alfred Kobsa University of California, Irvine, CA, USA Friedemann Mattern ETH Zurich, Switzerland John C. Mitchell Stanford University, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel Oscar Nierstrasz University of Bern, Switzerland C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen University of Dortmund, Germany Madhu Sudan Massachusetts Institute of Technology, MA, USA Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Gerhard Weikum Max-Planck Institute of Computer Science, Saarbruecken, Germany
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Eitan Frachtenberg Uwe Schwiegelshohn (Eds.)
Job Scheduling Strategies for Parallel Processing 13th International Workshop, JSSPP 2007 Seattle, WA, USA, June 17, 2007 Revised Papers
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Volume Editors Eitan Frachtenberg Powerset, Inc. 475 Brannan St., San Francisco, CA 94107, USA E-mail: [email protected] Uwe Schwiegelshohn Technische Universität Dortmund, Institut für Roboterforschung Otto-Hahn-Str. 8, 44227 Dortmund, Germany E-mail: [email protected]
Library of Congress Control Number: 2008924626 CR Subject Classification (1998): D.4, D.1.3, F.2.2, C.1.4, B.2.1, B.6, F.1.2 LNCS Sublibrary: SL 1 – Theoretical Computer Science and General Issues ISSN ISBN-10 ISBN-13
0302-9743 3-540-78698-8 Springer Berlin Heidelberg New York 978-3-540-78698-6 Springer Berlin Heidelberg New York
This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springer.com © Springer-Verlag Berlin Heidelberg 2008 Printed in Germany Typesetting: Camera-ready by author, data conversion by Scientific Publishing Services, Chennai, India Printed on acid-free paper SPIN: 12243488 06/3180 543210
Preface
This volume contains the papers presented at the 13th workshop on Job Scheduling Strategies for Parallel Processing. The workshop was held in Seattle, WA, USA, on June 17, 2007, in conjunction with ICS 2007. All submitted papers went through a complete review process, with the full version being read and evaluated by an average of five reviewers. We would like to thank the Program Committee members and additional referees for their willingness to participate in this effort and their excellent, detailed reviews: Nazareno Andrad
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