Job Scheduling Strategies for Parallel Processing 21st International Workshop, JSSPP 2017, Orlando, FL, USA, June 2, 2017, Revised Selected Papers için kapak resmi
Job Scheduling Strategies for Parallel Processing 21st International Workshop, JSSPP 2017, Orlando, FL, USA, June 2, 2017, Revised Selected Papers
Başlık:
Job Scheduling Strategies for Parallel Processing 21st International Workshop, JSSPP 2017, Orlando, FL, USA, June 2, 2017, Revised Selected Papers
Yazar:
Klusáček, Dalibor. editor.
ISBN:
9783319773988
Edisyon:
1st ed. 2018.
Fiziksel Niteleme:
IX, 189 p. 91 illus. online resource.
Seri:
Theoretical Computer Science and General Issues ; 10773
İçindekiler:
Experience and Practice of Batch Scheduling on Leadership Supercomputers at Argonne -- Analysis of Mixed Workloads from Shared Cloud Infrastructure -- Tuning EASY-Backfilling Queues -- Don't Hurry be Happy: a Deadline-based Backfilling Approach -- Supporting Real-Time Jobs on the IBM Blue Gene/Q: Simulation-Based Study -- Towards Efficient Resource Allocation for Distributed Workflows Under Demand Uncertainties -- Programmable In Situ System for Iterative -- A Data Structure for Planning Based Workload Management of Heterogeneous HPC Systems Workflows -- ScSF: A Scheduling Simulation Framework -- DJSB: Dynamic Job Scheduling Benchmark.
Özet:
This book constitutes the thoroughly refereed post-conference proceedings of the 21st International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2017, held in Orlando, FL, USA, in June 2017. The 10 revised full papers presented in this book were carefully reviewed and selected from 20 submissions. The papers cover topics in the fields of design and evaluation of new scheduling approaches; performance evaluation of scheduling approaches; workloads; consideration of additional constraints in scheduling systems; scaling and composition of very large scheduling systems; cloud provider issues; interaction between schedulers on different levels; interaction between applications/workloads; experience reports from production systems or large scale compute campaigns. .