Job Scheduling Strategies for Parallel Processing

16th International Workshop, JSSPP 2012, Shanghai, China, May 25, 2012. Revised Selected Papers

ISBN: 978-3-642-35866-1 (Print) 978-3-642-35867-8 (Online)

Table of contents (14 chapters)

  1. Front Matter

    Pages -

  2. No Access

    Book Chapter

    Pages 1-15

    Web-Scale Job Scheduling

  3. No Access

    Book Chapter

    Pages 16-35

    DEMB: Cache-Aware Scheduling for Distributed Query Processing

  4. No Access

    Book Chapter

    Pages 36-55

    Employing Checkpoint to Improve Job Scheduling in Large-Scale Systems

  5. No Access

    Book Chapter

    Pages 56-75

    Multi-objective Processor-Set Selection for Computational Cluster-Systems

  6. No Access

    Book Chapter

    Pages 76-95

    On Workflow Scheduling for End-to-End Performance Optimization in Distributed Network Environments

  7. No Access

    Book Chapter

    Pages 96-113

    Dynamic Kernel/Device Mapping Strategies for GPU-Assisted HPC Systems

  8. No Access

    Book Chapter

    Pages 114-133

    Optimal Co-Scheduling to Minimize Makespan on Chip Multiprocessors

  9. No Access

    Book Chapter

    Pages 134-156

    Evaluating Scalability and Efficiency of the Resource and Job Management System on Large HPC Clusters

  10. No Access

    Book Chapter

    Pages 157-177

    Partitioned Parallel Job Scheduling for Extreme Scale Computing

  11. No Access

    Book Chapter

    Pages 178-195

    High-Resolution Analysis of Parallel Job Workloads

  12. No Access

    Book Chapter

    Pages 196-215

    Identifying Quick Starters: Towards an Integrated Framework for Efficient Predictions of Queue Waiting Times of Batch Parallel Jobs

  13. No Access

    Book Chapter

    Pages 216-234

    On Identifying User Session Boundaries in Parallel Workload Logs

  14. No Access

    Book Chapter

    Pages 235-252

    Performance and Fairness for Users in Parallel Job Scheduling

  15. No Access

    Book Chapter

    Pages 253-271

    Comprehensive Workload Analysis and Modeling of a Petascale Supercomputer

  16. Back Matter

    Pages -