Job Scheduling Strategies for Parallel Processing

29th International Workshop, JSSPP 2026, New Orleans, LA, USA, May 26, 2026, Revised Selected Papers
Erscheinungsjahr 2026
ISBN: 978-3-032-41877-7
Verlag: Springer

Buch, Englisch, 251 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Computer Science

This book constitutes the refereed proceedings of the 29th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2025, held in New Orleans, LA, USA, during May 26, 2026.

The 13 full papers presented in this book were carefully reviewed and selected from 19 submissions. The workshop was organized into four sessions with thirteen
technical papers that covered several interesting problems within the resource management and scheduling domains.

Zielgruppe

Research

Autoren/Hrsg.

Klusácek, Dalibor

Corbalán, Julita

Rodrigo, Gonzalo P.

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
• Mathematik | Informatik EDV | Informatik Informatik Rechnerarchitektur
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Technische Informatik

Inhaltsverzeichnis

.- Duration-Aware Bandwidth Reservation over Two Node-Disjoint Paths in High-Performance Networks.
.- Pareto Frontier Optimization for NLP-based Cluster Allocation Directives.
.- MARS-HPC: A Multi-Objective Adaptive RL-Scheduler for Energy-Aware HPC Resource Management.
.- Patience vs Restraint as Self-adaptive Scheduling Strategies for Parallel Systems with Barriers.
.- GOA: Memory-Safe Oversubscription for Deep Learning Training Workloads.
.- Prediction-Augmented Scheduling for Minimizing GPU Fragmentation.
.- SafeWall: A Risk-Aware Job Walltime Recommendation for HPC Scheduling.
.- Workload Traces from the Frontier Exascale Supercomputer.
.- Opportunistic Resource Reclamation in Kubernetes: From Aggressive Resizing to Flash Jobs.
.- A Granularity Characterization of Task Scheduling Effectiveness.
.- Fusing System Data to Navigate Power-Saving Opportunities.
.- Sustainable On-Demand HPC through Managed Oversubscription.
.- From Petascale to Exascale: Evolving User Behavior on the Polaris and Aurora Systems.