Performance Analysis and Grid Computing

Selected Articles from the Workshop on Performance Analysis and Distributed Computing August 19–23, 2002, Dagstuhl, Germany

  • Vladimir Getov
  • Michael Gerndt
  • Adolfy Hoisie
  • Allen Malony
  • Barton Miller

Table of contents

  1. Front Matter
    Pages i-xv
  2. Performance Modeling and Analysis

    1. Front Matter
      Pages 1-1
    2. Tomàs Margalef, Josep Jorba, Oleg Morajko, Anna Morajko, Emilio Luque
      Pages 3-19
    3. Darren J. Kerbyson, Adolfy Hoisie, Shawn D. Pautz
      Pages 21-39
    4. Matthias Korch, Thomas Rauber, Gudula Rünger
      Pages 41-56
    5. Achal Prabhakar, Vladimir Getov
      Pages 57-76
    6. Matthias Kühnemann, Thomas Rauber, Gudula Rünger
      Pages 77-91
    7. Salvador Coll, José Duato, Francisco J. Mora, Fabrizio Petrini, Adolfy Hoisie
      Pages 93-107
  3. Performance Tools and Systems

    1. Front Matter
      Pages 109-109
    2. Ken Mayes, Graham D. Riley, Rupert W. Ford, Mikel Luján, Len Freeman, Cliff Addison
      Pages 111-127
    3. Allen D. Malony, Sameer Shende, Robert Bell, Kai Li, Li Li, Nick Trebon
      Pages 129-144
    4. Kukjin Lee, Diane T. Rover
      Pages 145-159
    5. Marian Bubak, Włodzimierz Funika, Roland Wismüller
      Pages 161-173
    6. Kwok Yeung, Paul H. J. Kelly, Sarah Bennett
      Pages 175-187
    7. Thomas Fahringer, Clovis Seragiotto Jr.
      Pages 189-208
  4. Grid Performance and Applications

    1. Front Matter
      Pages 209-209
    2. Catherine Crawford, Daniel Dias, Arun Iyengar, Marcos Novaes, Li Zhang
      Pages 211-229
    3. Nikos Chrisochoides, Craig Lee, Bruce Lowekamp
      Pages 231-250
    4. Beniamino Di Martino, Omer F. Rana
      Pages 251-263
    5. Bartosz Baliś, Marian Bubak, Włodzimierz Funika, Tomasz Szepieniec, Roland Wismüller
      Pages 265-273
    6. Sven Haubold, Hartmut Mix, Wolfgang E. Nagel, Mathilde Romberg
      Pages 275-288
  5. Back Matter
    Pages 289-290

About this book


Past and current research in computer performance analysis has focused primarily on dedicated parallel machines. However, future applications in the area of high-performance computing will not only use individual parallel systems but a large set of networked resources. This scenario of computational and data Grids is attracting a great deal of attention from both computer and computational scientists. In addition to the inherent complexity of parallel machines, the sharing and transparency of the available resources introduces new challenges on performance analysis, techniques, and systems. In order to meet those challenges, a multi-disciplinary approach to the multi-faceted problems of performance is required. New degrees of freedom will come into play with a direct impact on the performance of Grid computing, including wide-area network performance, quality-of-service (QoS), heterogeneity, and middleware systems, to mention only a few.


Automat Java Middleware agents complexity modeling monitor optimization

Editors and affiliations

  • Vladimir Getov
    • 1
  • Michael Gerndt
    • 2
  • Adolfy Hoisie
    • 3
  • Allen Malony
    • 4
  • Barton Miller
    • 5
  1. 1.University of WestminsterUK
  2. 2.Technical University MunichGermany
  3. 3.Los Alamos National LaboratoryUSA
  4. 4.University of Oregon-EugeneUSA
  5. 5.University of Wisconsin-MadisonUSA

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