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Job Scheduling Strategies for Parallel Processing

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Cover of 'Job Scheduling Strategies for Parallel Processing'

Table of Contents

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    Book Overview
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    Chapter 1 Parallel Job Scheduling — A Status Report
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    Chapter 2 Scheduling on the Top 50 Machines
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    Chapter 3 Parallel Computer Workload Modeling with Markov Chains
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    Chapter 4 Enhancements to the Decision Process of the Self-Tuning dynP Scheduler
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    Chapter 5 Reconfigurable Gang Scheduling Algorithm
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    Chapter 6 Time-Critical Scheduling on a Well Utilised HPC System at ECMWF Using Loadleveler with Resource Reservation
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    Chapter 7 Inferring the Topology and Traffic Load of Parallel Programs Running in a Virtual Machine Environment
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    Chapter 8 Multi-toroidal Interconnects: Using Additional Communication Links to Improve Utilization of Parallel Computers
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    Chapter 9 Costs and Benefits of Load Sharing in the Computational Grid
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    Chapter 10 Workload Characteristics of a Multi-cluster Supercomputer
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    Chapter 11 A Dynamic Co-allocation Service in Multicluster Systems
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    Chapter 12 Exploiting Replication and Data Reuse to Efficiently Schedule Data-Intensive Applications on Grids
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    Chapter 13 Performance Implications of Failures in Large-Scale Cluster Scheduling
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    Chapter 14 Are User Runtime Estimates Inherently Inaccurate?
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    Chapter 15 Improving Speedup and Response Times by Replicating Parallel Programs on a SNOW
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    Chapter 16 LOMARC — Lookahead Matchmaking for Multi-resource Coscheduling
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Title
Job Scheduling Strategies for Parallel Processing
Published by
Springer, Berlin, Heidelberg, January 2004
DOI 10.1007/b107134
ISBNs
978-3-54-025330-3, 978-3-54-031795-1
Editors

Dror G. Feitelson, Larry Rudolph, Uwe Schwiegelshohn

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 4%
United Kingdom 1 2%
Mexico 1 2%
China 1 2%
Hong Kong 1 2%
Pakistan 1 2%
Greece 1 2%
Unknown 44 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 42%
Student > Master 11 21%
Researcher 9 17%
Student > Doctoral Student 4 8%
Professor > Associate Professor 3 6%
Other 3 6%
Readers by discipline Count As %
Computer Science 40 77%
Engineering 9 17%
Arts and Humanities 1 2%
Social Sciences 1 2%
Physics and Astronomy 1 2%
Other 0 0%