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Job Scheduling Strategies for Parallel Processing de Walfredo Cirne

Job Scheduling Strategies for Parallel Processing: Lecture Notes in Computer Science, cartea 8828

Editat de Walfredo Cirne, Narayan Desai
en Limba Engleză Paperback – 16 mar 2015
This book constitutes the thoroughly refereed post-conference proceedings of the 18th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2014, held in Phoenix, AZ, USA, in May 2014. The 9 revised full papers presented were carefully reviewed and selected from 24 submissions. The papers cover the following topics: single-core parallelism; moving to distributed-memory, larger-scale systems, scheduling fairness; and parallel job scheduling.
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Specificații

ISBN-13: 9783319157887
ISBN-10: 3319157884
Pagini: 180
Ilustrații: X, 169 p. 60 illus.
Dimensiuni: 155 x 235 x 11 mm
Greutate: 0.28 kg
Ediția:2015
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

Bubble Task: A Dynamic Execution Throttling Method for Multi-core Resource Management.- Real-World Clustering for Task Graphs on Shared Memory Systems.- Experimental Analysis of the Tardiness of Parallel Tasks in Soft Real-time Systems.- Multi-Resource Aware Fairsharing for Heterogeneous Systems.- Priority Operators for Fairshare Scheduling.- User-Aware Metrics for Measuring Quality of Parallel Job Schedules.- Prediction of Queue Waiting Times for Metascheduling on Parallel Batch Systems.- Dynamically Scheduling a Component-Based Framework in Clusters.- How to Design a Job Scheduling Algorithm.

Textul de pe ultima copertă

This book constitutes the thoroughly refereed post-conference proceedings of the 18th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2014, held in Phoenix, AZ, USA, in May 2014. The 9 revised full papers presented were carefully reviewed and selected from 24 submissions. The papers cover the following topics: single-core parallelism; moving to distributed-memory, larger-scale systems, scheduling fairness; and parallel job scheduling.