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Fair Scheduling in High Performance Computing Environments

  • Art Sedighi
  • Milton Smith

Table of contents

  1. Front Matter
    Pages i-xi
  2. Art Sedighi, Milton Smith
    Pages 1-5
  3. Art Sedighi, Milton Smith
    Pages 7-15
  4. Art Sedighi, Milton Smith
    Pages 17-22
  5. Art Sedighi, Milton Smith
    Pages 23-28
  6. Art Sedighi, Milton Smith
    Pages 29-37
  7. Art Sedighi, Milton Smith
    Pages 39-46
  8. Art Sedighi, Milton Smith
    Pages 47-50
  9. Art Sedighi, Milton Smith
    Pages 51-62
  10. Art Sedighi, Milton Smith
    Pages 63-70
  11. Art Sedighi, Milton Smith
    Pages 71-84
  12. Art Sedighi, Milton Smith
    Pages 85-99
  13. Art Sedighi, Milton Smith
    Pages 101-109
  14. Art Sedighi, Milton Smith
    Pages 111-122
  15. Art Sedighi, Milton Smith
    Pages 123-124
  16. Back Matter
    Pages 125-132

About this book

Introduction

This book introduces a new scheduler to fairly and efficiently distribute system resources to many users of varying usage patterns compete for them in large shared computing environments.  The Rawlsian Fair scheduler developed for this effort is shown to boost performance while reducing delay in high performance computing workloads of certain types including the following four types examined in this book:

i.        Class A – similar but complementary workloads

ii.      Class B – similar but steady vs intermittent workloads

iii.    Class C – Large vs small workloads

iv.    Class D – Large vs noise-like workloads

This new scheduler achieves short-term fairness for small timescale demanding rapid response to varying workloads and usage profiles.  Rawlsian Fair scheduler is shown to consistently benefit workload Classes C and D while it only benefits Classes A and B workloads where they become disproportionate as the number of users increases.

A simulation framework, dSim, simulates the new Rawlsian Fair scheduling mechanism. The dSim helps achieve instantaneous fairness in High Performance Computing environments, effective utilization of computing resources, and user satisfaction through the Rawlsian Fair scheduler.

Keywords

Scheduling HPC grid computing Cloud fairness game theory resource management resource allocation allocation schemes

Authors and affiliations

  • Art Sedighi
    • 1
  • Milton Smith
    • 2
  1. 1.Industrial, Manufacturing & Systems EngineeringTexas Tech UniversityLubbockUSA
  2. 2.Industrial, Manufacturing & Systems EngineeringTexas Tech UniversityLubbockUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-030-14568-2
  • Copyright Information Springer Nature Switzerland AG 2019
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-030-14567-5
  • Online ISBN 978-3-030-14568-2
  • Buy this book on publisher's site
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