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A methodology for exploiting concurrency among independent tasks in partitionable parallel processing systems

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dc.contributor.authorSiegel, Howard J., author
dc.contributor.authorMaciejewski, Anthony A., author
dc.contributor.authorNation, Wayne G., author
dc.contributor.authorAcademic Press, publisher
dc.date.accessioned2007-01-03T08:09:30Z
dc.date.available2007-01-03T08:09:30Z
dc.date.issued1993
dc.description.abstractOne benefit of partitionable parallel processing systems is their ability to execute multiple, independent tasks simultaneously. Previous work has identified conditions such that, when there are tasks to be processed, partitioning the system so that all k tasks are processed simultaneously results in a minimum overall execution time. An alternate condition is developed that provides additional insight into the effects of parallelism on execution time. This result and previous results, however, assume that execution times are data independent. It is shown that data-dependent tasks do not necessarily execute faster when processed simultaneously even if the condition is met. A model is developed that provides for the possible variability of a task's execution time and is used in a new framework to study the problem of finding an optimal mapping for identical, independent data-dependent execution time tasks onto partitionable systems. Executing one, some, or all of the k tasks simultaneously is considered. Because this new framework is general, it can also serve as a new method for the study of data-independent tasks. Extension of this framework to situations where the k tasks are nonidentical is discussed.
dc.format.mediumborn digital
dc.format.mediumarticles
dc.identifier.bibliographicCitationNation, Wayne G., Anthony A. Maciejewski, and Howard Jay Siegel, A Methodology for Exploiting Concurrency Among Independent Tasks in Partitionable Parallel Processing Systems, Journal of Parallel and Distributed Computing 19, 3 (November 1993): 271-278.
dc.identifier.urihttp://hdl.handle.net/10217/67343
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©1993 Academic Press.
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectconcurrent tasks
dc.subjectallocating tasks
dc.subjectexecution time
dc.subjectparallelism
dc.titleA methodology for exploiting concurrency among independent tasks in partitionable parallel processing systems
dc.typeText

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