1 option
Job Scheduling Strategies for Parallel Processing : 28th International Workshop, JSSPP 2025, Milan, Italy, June 3–4, 2025, Revised Selected Papers / edited by Dalibor Klusáček, Julita Corbalán, Gonzalo P. Rodrigo.
Springer Nature - Springer Computer Science eBooks 2026 English International Available online
View online- Format:
- Book
- Author/Creator:
- Klusáĉek, Dalibor.
- Series:
- Lecture Notes in Computer Science, 1611-3349 ; 16210
- Language:
- English
- Subjects (All):
- Software engineering.
- Artificial intelligence.
- Coding theory.
- Information theory.
- Microprogramming.
- Computer input-output equipment.
- Logic design.
- Software Engineering.
- Artificial Intelligence.
- Coding and Information Theory.
- Control Structures and Microprogramming.
- Input/Output and Data Communications.
- Logic Design.
- Local Subjects:
- Software Engineering.
- Artificial Intelligence.
- Coding and Information Theory.
- Control Structures and Microprogramming.
- Input/Output and Data Communications.
- Logic Design.
- Physical Description:
- 1 online resource (466 pages)
- Edition:
- 1st ed. 2026.
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2026.
- Summary:
- This book constitutes the refereed proceedings of the 28th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2025, held in Milan, Italy, during June 3-4, 2025. The 17 full papers and 1 keynote paper presented in this book were carefully reviewed and selected from 25 submissions. These papers covered interesting topics within the resource management and scheduling domains.
- Contents:
- How to make the ultimate goal of energy-efficient data centers a reality.
- Power-Aware Scheduling for Multi-Center HPC Electricity Cost Optimization.
- Job Grouping Based Intelligent Resource Prediction Framework.
- Kubernetes Scheduling with Checkpoint/Restore: Challenges and Open Problems.
- Adaptive Carbon-Aware scheduling policies for HPC systems.
- Resource elasticity for scientific platforms on HPC infrastructure.
- More for Less: Integrating Capability-Predominant and Capacity-Predominant Computing.
- Workflow Batch Job Scheduling with Considering Task Dependencies.
- Quality-Aware Energy-Efficient Scheduling of Moldable-Parallel Streaming Computations on Heterogeneous Multicore CPUs with DVFS.
- Optimizing Energy Efficiency in Heterogeneous Computing via Multi-Objective Scheduling with Reinforcement Learning.
- Static powercap vs. EAR hard-powercap: Performance evaluation.
- Deep RC: A Scalable Data Engineering and Deep Learning Pipeline.
- Fedsort: An Optimized Federated Scheduling Strategy for Cloud Workloads with Inter-task Dependencies.
- Evaluating the Impact of Algorithmic Components on Task Graph Scheduling.
- Communication-balanced Job Allocation using SLURM.
- Performance Models to support HPC Co-Scheduling.
- ELiSE: A tool to support algorithmic design for HPC co-scheduling.
- Deadline Miss Minimization Scheduling for License-Constrained CAE Jobs in Hybrid Cloud Infrastructure.
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 3-032-10507-2
- 9783032105073
- OCLC:
- 1568058268
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.