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Job Scheduling Strategies for Parallel Processing
Details
This book constitutes the refereed proceedings of the 27th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2024, held in San Francisco, CA, USA, on May 31, 2024.
The 10 full papers included in this book were carefully reviewed and selected from 15 submissions. The JSSPP 2024 covers several interesting problems within the resource management and scheduling domains.
Inhalt
.- Technical papers.
.- Real-life HPC Workload Trace Featuring Refined Job Runtime Estimates.
.- An Empirical Study of Machine Learning-based Synthetic Job Trace Generation Methods.
.- Clustering Based Job Runtime Prediction for Backfilling Using Classification.
.- Launchpad: Learning to Schedule Using Offline and Online RL Methods.
.- Radical-Cylon: A Heterogeneous Data Pipeline for Scientific Computing.
.- Evaluation of Heuristic Task-to-Thread Mapping Using Static and Dynamic Approaches.
.- Challenges in parallel matrix chain multiplication.
.- A node selection method for on-demand job execution with considering deadline constraints.
.- Maximizing Energy Budget Utilization Using Dynamic Power Cap Control.
.- Run your HPC jobs in Eco-Mode: revealing the potential of user-assisted power capping in supercomputing systems.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783031744297
- Genre Information Technology
- Editor Dalibor Klusáek, Julita Corbalán, Gonzalo P. Rodrigo
- Lesemotiv Verstehen
- Anzahl Seiten 197
- Größe H235mm x B155mm
- Jahr 2024
- EAN 9783031744297
- Format Kartonierter Einband
- ISBN 978-3-031-74429-7
- Veröffentlichung 21.12.2024
- Titel Job Scheduling Strategies for Parallel Processing
- Untertitel 27th International Workshop, JSSPP 2024, San Francisco, CA, USA, May 31, 2024, Revised Selected Papers
- Herausgeber Springer Nature Switzerland
- Sprache Englisch