Fair Scheduling in High Performance Computing Environments

Nonfiction, Computers, General Computing, Programming, Internet
Cover of the book Fair Scheduling in High Performance Computing Environments by Art Sedighi, Milton Smith, Springer International Publishing
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Author: Art Sedighi, Milton Smith ISBN: 9783030145682
Publisher: Springer International Publishing Publication: April 17, 2019
Imprint: Springer Language: English
Author: Art Sedighi, Milton Smith
ISBN: 9783030145682
Publisher: Springer International Publishing
Publication: April 17, 2019
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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