Job Scheduling Strategies for Parallel Processing: 24th International Workshop, JSSPP 2021, Virtual Event, May 21, 2021, Revised Selected Papers - Info and Reading Options

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Intro -- Preface -- Organization -- Contents -- Keynote -- Resampling with Feedback: A New Paradigm of Using Workload Data for Performance Evaluation -- 1 Introduction -- 2 Background -- 3 Using Workload Logs and Models to Drive Simulations -- 3.1 Workload Modeling -- 3.2 Problems with Models -- 3.3 Using Logs Directly -- 3.4 Drawbacks of Using Logs -- 4 Resampling and Feedback -- 4.1 Before Resampling: Input Shaking and User-Based Modeling -- 4.2 Resampling from a Log -- 4.3 Adding Feedback -- 4.4 Applications and Benefits -- 5 Conclusions -- References -- Open Scheduling Problems and Proposals -- Collection of Job Scheduling Prediction Methods -- 1 Introduction -- 2 Background -- 3 Predictions -- 3.1 Job Workloads and Metadata -- 3.2 Metrics -- 3.3 Repository -- 4 Conclusion and Outlook -- References -- Modular Workload Format: Extending SWF for Modular Systems -- 1 Introduction and Motivation -- 2 Standard Workload Format -- 3 Heterogeneous Systems Requirements -- 4 Modular Workload Format (MWF) Proposal -- 4.1 Modular Workload Format Fields -- 4.2 Headers -- 5 From SWF to MWF -- 6 MWF Experiences -- 7 Conclusions -- References -- Technical Papers -- Measurement and Modeling of Performance of HPC Applications Towards Overcommitting Scheduling Systems -- 1 Introduction -- 2 Background -- 2.1 Evaluation Metrics for Scheduling -- 2.2 Features of Interactive Jobs -- 3 Overcommitting on Supercomputer Systems -- 3.1 Node-Level Overcommitting -- 3.2 Processor Core-Level Overcommitting -- 3.3 Overcommitting Scheduling System -- 4 Methodology for Evaluation Under Overcommitting -- 4.1 Target Workload -- 4.2 Experiment Environment for Overcommitting -- 4.3 Definition of Performance Degradation Ratio -- 5 Performance Evaluation Under Overcommitting -- 5.1 Two Batch Jobs -- 5.2 A Batch Job and an Interactive Job

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