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

Contributor(s): Frachtenberg, Eitan [editor.] | Schwiegelshohn, Uwe [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Computer Science: 4376Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.Description: VIII, 264 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540710356.Subject(s): Computer science | Logic design | Microprocessors | Architecture, Computer | Computer programming | Operating systems (Computers) | Algorithms | Computer Science | Computer System Implementation | Operating Systems | Programming Techniques | Algorithm Analysis and Problem Complexity | Processor Architectures | Logic DesignOnline resources: Click here to access online
Contents:
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.
In: Springer eBooks
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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 Arrivals in a Data-Intensive Grid -- On Grid Performance Evaluation Using Synthetic Workloads.

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