Job Scheduling Strategies for Parallel Processing
Job Scheduling Strategies for Parallel Processing
27th International Workshop, JSSPP 2024, San Francisco, CA, USA, May 31, 2024, Revised Selected Papers
Corbalan, Julita; Rodrigo, Gonzalo P.; Klusacek, Dalibor
Springer International Publishing AG
01/2025
203
Mole
9783031744297
Pré-lançamento - envio 15 a 20 dias após a sua edição
.- 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.
.- 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.