Job Scheduling Strategies for Parallel Processing - Frachtenberg, Eitan (Volume ed.) / Schwiegelshohn, Uwe
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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…mehr

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Produktbeschreibung
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.
Autorenporträt
Eitan Frachtenberg, Los Alamos National Laboratory, NM, USA / Uwe Schwiegelshohn, University of Dortmund, Germany