Toward convergence in job schedulers for parallel supercomputers

Dror G. Feitelson, Larry Rudolph

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

114 Scopus citations

Abstract

The space of job schedulers for parallel supercomputers is rather fragmented, because different researchers tend to make different assumptions about the goals of the scheduler, the information that is available about the workload, and the operations that the scheduler may perform. We argue that by identifying these assumptions explicitly, it is possible to reach a level of convergence. For example, it is possible to unite most of the different assumptions into a common framework by associating a suitable cost function with the execution of each job. The cost function reflects knowledge about the job and the degree to which it fits the goals of the system. Given such cost functions, scheduling is done to maximize the system's profit.

Original languageAmerican English
Title of host publicationJob Scheduling Strategies for Parallel Processing - IPPS 1996 Workshop, Proceedings
EditorsDror G. Feitelson, Larry Rudolph
PublisherSpringer Verlag
Pages1-26
Number of pages26
ISBN (Print)3540618643, 9783540618645
DOIs
StatePublished - 1996
Event2nd Workshop on Job Scheduling Strategies for Parallel Processing, IPPS 1996 - Honolulu, United States
Duration: 16 Apr 199616 Apr 1996

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1162
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd Workshop on Job Scheduling Strategies for Parallel Processing, IPPS 1996
Country/TerritoryUnited States
CityHonolulu
Period16/04/9616/04/96

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 1996.

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