Job Scheduling Strategies for Parallel Processing : 12th International Workshop, JSSPP 2006, Saint-Malo, France, June 26, 2006, Revised Selected Papers

Uwe Schwiegelshohn

ISBN 10: 3540710345 / ISBN 13: 9783540710349

Editore: Springer Berlin Heidelberg, 2007

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Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the thoroughly refereed post-proceedings of the 12th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2006, held in Saint-Malo, France in June 2006 in conjunction with the Joint International Conference on Measurement and Modeling of Computer Systems SIGMETRICS/Performance 2006. The 12 revised full research papers cover all current issues of job scheduling strategies for parallel processing.

Codice articolo 9783540710349

Dati bibliografici

• Titolo: Job Scheduling Strategies for Parallel Processing : 12th International Workshop, JSSPP 2006, Saint-Malo, France, June 26, 2006, Revised Selected Papers
• Editore: Springer Berlin Heidelberg
• Data di pubblicazione: 2007
• Lingua: Inglese
• ISBN 10: 3540710345
• ISBN 13: 9783540710349
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 15 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 15 millimetri di profondità
• Peso: 417 grammi

Descrizione articolo

Riassunto

This book constitutes the thoroughly refereed post-proceedings of the 12th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2006, held in Saint-Malo, France in June 2006 in conjunction with the Joint International Conference on Measurement and Modeling of Computer Systems SIGMETRICS/Performance 2006. The 12 revised full research papers cover all current issues of job scheduling strategies for parallel processing.

Contenuti

Provably Efficient Two-Level Adaptive Scheduling.- Scheduling Dynamically Spawned Processes in MPI-2.- Advance Reservation Policies for Workflows.- On Advantages of Scheduling Using Genetic Fuzzy Systems.- Moldable Parallel Job Scheduling Using Job Efficiency: An Iterative Approach.- Adaptive Job Scheduling Via Predictive Job Resource Allocation.- A Data Locality Aware Online Scheduling Approach for I/O-Intensive Jobs with File Sharing.- Volunteer Computing on Clusters.- Load Balancing: Toward the Infinite Network and Beyond.- Symbiotic Space-Sharing on SDSC’s DataStar System.- Modeling Job Arrivals in a Data-Intensive Grid.- On Grid Performance Evaluation Using Synthetic Workloads.