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Job Scheduling Strategies for Parallel Processing: 24th International Workshop, JSSPP 2021, Virtual Event, May 21, 2021, Revised Selected Papers 1st ed. 2021 [Minkštas viršelis]

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  • Formatas: Paperback / softback, 231 pages, aukštis x plotis: 235x155 mm, weight: 379 g, 93 Illustrations, color; 10 Illustrations, black and white; XII, 231 p. 103 illus., 93 illus. in color., 1 Paperback / softback
  • Serija: Lecture Notes in Computer Science 12985
  • Išleidimo metai: 06-Oct-2021
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030882233
  • ISBN-13: 9783030882235
  • Formatas: Paperback / softback, 231 pages, aukštis x plotis: 235x155 mm, weight: 379 g, 93 Illustrations, color; 10 Illustrations, black and white; XII, 231 p. 103 illus., 93 illus. in color., 1 Paperback / softback
  • Serija: Lecture Notes in Computer Science 12985
  • Išleidimo metai: 06-Oct-2021
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030882233
  • ISBN-13: 9783030882235
This book constitutes the thoroughly refereed post-conference proceedings of the 24th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2021, held as a virtual event in May 2021 (due to the Covid-19 pandemic).

The 10 revised full papers presented were carefully reviewed and selected from 17 submissions. In addition to this, one keynote paper was included in the workshop. The volume contains two sections: Open Scheduling Problems and Proposals and Technical Papers. The papers cover such topics as parallel computing, distributed systems, workload modeling, performance optimization, and others.

Keynote.- Resampling with Feedback: A New Paradigm of Using Workload
Data for Performance Evaluation.- Open Scheduling Problems and
Proposals.- Collection of Job Scheduling Prediction Methods.- Modular
Workload Format: extending SWF for modular systems.- Technical
Papers.- Measurement and Modeling of Performance of HPC Applications towards
Overcommitting Scheduling Systems.- Scheduling Microservice Containers on
Large Core Machines through Placement and Coalescing.- Learning-based
Approaches to Estimate Job Wait Time in HTC Datacenters.- A HPC Co-Scheduler
with Reinforcement Learning.- Performance-Cost Optimization of Moldable
Scientific Workflows.- Temperature-Aware Energy-Optimal Scheduling of
Moldable Streaming Tasks onto 2D-Mesh-Based Many-Core CPUs with
DVFS.- Scheduling Challenges for Variable Capacity Resources.- GLUME: A
Strategy for Reducing Workflow Execution Times on Batch-Scheduled Platforms.