Memory management techniques for gang scheduling

William Leinberger, George Karypis, Vipin Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


The addition of time-slicing to space-shared gang scheduling improves the average response time of the jobs in a typical job stream. Recent research has shown that time-slicing is most effective when the jobs admitted for execution fit entirely into physical memory. The question is, how to select and map jobs to make the best use of the available physical memory. Specifically, the achievable degree of multi-programming is limited by the memory requirements, or physical memory pressure, of the admitted jobs. We investigate two techniques for improving the performance of gang scheduling in the presence of memory pressure: 1) a novel backfill approach which improves memory utilization, and 2) an adaptive multi-programming level which balances processor/memory utilization with job response time performance. Our simulations show that these techniques reduce the average wait time and slow-down performance metrics over naive first-come-first-serve methods on a distributed memory parallel system.

Original languageEnglish (US)
Title of host publicationEuro-Par 2000 Parallel Processing - 6th International Euro-Par Conference, Proceedings
EditorsArndt Bode, Thomas Ludwig, Wolfgang Karl, Roland Wismüller
PublisherSpringer Verlag
Number of pages10
ISBN (Electronic)9783540679561
StatePublished - Jan 1 2000
Event6th International European Conference on Parallel Computing, Euro-Par 2000 - Munich, Germany
Duration: Aug 29 2000Sep 1 2000

Publication series

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


Other6th International European Conference on Parallel Computing, Euro-Par 2000

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