Job Scheduling Strategies for Parallel Processing - 23rd International Workshop, JSSPP 2020, New Orleans, LA, USA, May 22, 2020, Revised Selected Papers

This book constitutes the thoroughly refereed post-conference proceedings of the 23rd International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2020, held in New Orleans, LA, USA, in May 2020.*The 6 revised full papers presented were carefully reviewed and selected from 8 submissions. In addition to this, one invited paper and one keynote pare were included in the workshop. The papers cover topics within the fields of resource management and scheduling. They focus on several interesting problems such as resource contention and workload interference, new scheduling policy, scheduling ultrasound simulation workflows, and walltime prediction.
* The conference was held virtually due to the COVID-19 pandemic.

List of contents

Towards Interference-aware Dynamic Scheduling in Virtualized Environments.- Towards Hybrid Isolation for Shared Multicore Systems.- Improving Resource Isolation of Critical Tasks in a Workload.- Optimizing Biomedical Ultrasound Workflow Scheduling Using Cluster Simulations.- Evaluating Controlled Memory Request Injection to Counter PREM Memory Underutilization.- Accelerating 3-way Epistasis Detection with CPU+GPU processing.- Walltime Prediction and its Impact on Job Scheduling Performance and Predictability.- PDAWL: Profile-based Iterative Dynamic Adaptive WorkLoad Balance on Heterogeneous Architectures.

Product details

• Assisted by: Walfred Cirne (Editor), Walfredo Cirne (Editor), Narayan Desai (Editor), Dalibor Klusá¿ek (Editor), Dalibor Klusácek (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 18.01.2021
• EAN: 9783030631703
• ISBN: 978-3-0-3063170-3
• No. of pages: 163
• Dimensions: 156 mm x 11 mm x 236 mm
• Illustrations: IX, 163 p. 77 illus., 45 illus. in color.
• Series: Lecture Notes in Computer Science; Theoretical Computer Science and General Issues
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > IT