Performance Analysis and Grid Computing

1. Front Matter

   Pages i-xv

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2. Performance Modeling and Analysis

   1. Front Matter

      Pages 1-1

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   2. Different Approaches to Automatic Performance Analysis of Distributed Applications

      • Tomàs Margalef, Josep Jorba, Oleg Morajko, Anna Morajko, Emilio Luque

      Pages 3-19

   3. Performance Modeling of Deterministic Transport Computations

      • Darren J. Kerbyson, Adolfy Hoisie, Shawn D. Pautz

      Pages 21-39

   4. Performance Optimization of RK Methods Using Block-Based Pipelining

      • Matthias Korch, Thomas Rauber, Gudula Rünger

      Pages 41-56

   5. Performance Evaluation of Hybrid Parallel Programming Paradigms

      • Achal Prabhakar, Vladimir Getov

      Pages 57-76

   6. Performance Modelling for Task-Parallel Programs

      • Matthias Kühnemann, Thomas Rauber, Gudula Rünger

      Pages 77-91

   7. Collective Communication Patterns on the Quadrics Network

      • 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

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   2. The Design of a Performance Steering System for Component-Based Grid Applications

      • Ken Mayes, Graham D. Riley, Rupert W. Ford, Mikel Luján, Len Freeman, Cliff Addison

      Pages 111-127

   3. Advances in the Tau Performance System

      • Allen D. Malony, Sameer Shende, Robert Bell, Kai Li, Li Li, Nick Trebon

      Pages 129-144

   4. Uniform Resource Visualization: Software and Services

      • Kukjin Lee, Diane T. Rover

      Pages 145-159

   5. A Performance Analysis Tool for Interactive Grid Applications

      • Marian Bubak, Włodzimierz Funika, Roland Wismüller

      Pages 161-173

   6. Dynamic Instrumentation for Java Using a Virtual JVM

      • Kwok Yeung, Paul H. J. Kelly, Sarah Bennett

      Pages 175-187

   7. Aksum: A Performance Analysis Tool for Parallel and Distributed Applications

      • Thomas Fahringer, Clovis Seragiotto Jr.

      Pages 189-208

4. Grid Performance and Applications

   1. Front Matter

      Pages 209-209

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   2. Commercial Applications of Grid Computing

      • Catherine Crawford, Daniel Dias, Arun Iyengar, Marcos Novaes, Li Zhang

      Pages 211-229

   3. Mesh Generation and Optimistic Computation on the Grid

      • Nikos Chrisochoides, Craig Lee, Bruce Lowekamp

      Pages 231-250

   4. Grid Performance and Resource Management Using Mobile Agents

      • Beniamino Di Martino, Omer F. Rana

      Pages 251-263

   5. Monitoring of Interactive Grid Applications

      • Bartosz Baliś, Marian Bubak, Włodzimierz Funika, Tomasz Szepieniec, Roland Wismüller

      Pages 265-273

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

• University of Westminster, UK

  Vladimir Getov

• Technical University Munich, Germany

  Michael Gerndt

• Los Alamos National Laboratory, USA

  Adolfy Hoisie

• University of Oregon-Eugene, USA

  Allen Malony

• University of Wisconsin-Madison, USA

  Barton Miller

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