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Scheduling on AP/Linux for Fine and Coarse Grain Parallel Processes

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Cover of 'Scheduling on AP/Linux for Fine and Coarse Grain Parallel Processes'

Table of Contents

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    Book Overview
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    Chapter 1 Scheduling for Parallel Supercomputing: A Historical Perspective of Achievable Utilization
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    Chapter 2 On the Design and Evaluation of Job Scheduling Algorithms
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    Chapter 3 Comparing Logs and Models of Parallel Workloads Using the Co-plot Method
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    Chapter 4 Benchmarks and Standards for the Evaluation of Parallel Job Schedulers
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    Chapter 5 The Effect of Correlating Quantum Allocation and Job Size for Gang Scheduling
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    Chapter 6 Scheduling on AP/Linux for Fine and Coarse Grain Parallel Processes
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    Chapter 7 Job Re-packing for Enhancing the Performance of Gang Scheduling
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    Chapter 8 Process Tracking for Parallel Job Control
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    Chapter 9 The Legion Resource Management System
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    Chapter 10 Scheduling a Metacomputer with Uncooperative Sub-schedulers
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    Chapter 11 Using Run-Time Predictions to Estimate Queue Wait Times and Improve Scheduler Performance
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    Chapter 12 Deterministic Batch Scheduling without Static Partitioning
Attention for Chapter 2: On the Design and Evaluation of Job Scheduling Algorithms
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Citations

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14 Mendeley
Summary Dimensions citations
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Chapter title
On the Design and Evaluation of Job Scheduling Algorithms
Chapter number 2
Book title
Job Scheduling Strategies for Parallel Processing
Published by
Springer, Berlin, Heidelberg, April 1999
DOI 10.1007/3-540-47954-6_2
Book ISBNs
978-3-54-066676-9, 978-3-54-047954-3
Authors

Jochen Krallmann, Uwe Schwiegelshohn, Ramin Yahyapour, Krallmann, Jochen, Schwiegelshohn, Uwe, Yahyapour, Ramin

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 14%
United States 1 7%
Spain 1 7%
Unknown 10 71%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 21%
Student > Ph. D. Student 3 21%
Professor > Associate Professor 2 14%
Student > Bachelor 1 7%
Student > Doctoral Student 1 7%
Other 2 14%
Unknown 2 14%
Readers by discipline Count As %
Computer Science 10 71%
Engineering 2 14%
Unknown 2 14%

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