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dc.contributor.advisorAndrews, Gregory R.en_US
dc.contributor.authorRoback, Joseph Anthony
dc.creatorRoback, Joseph Anthonyen_US
dc.date.accessioned2011-12-05T22:35:23Z
dc.date.available2011-12-05T22:35:23Z
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/10150/194468
dc.description.abstractThe key to performance improvements in the multicore era is for software toutilize the newly available concurrency. Consequently, programmers will have tolearn new programming techniques, and software systems will have to be able tomanage the parallelism effectively. The challenge is to do so simply, portably,and efficiently.This dissertation presents a lightweight programming framework called Gossamerthat is easy to use, enables the solution of a broad range of parallelprogramming problems, and produces efficient code. Gossamer supports task andrecursive parallelism, iterative parallelism, domain decomposition, pipelinedcomputations, and MapReduce computations. Gossamer contains (1) a set ofhigh-level annotations that one adds to a sequential program to specifyconcurrency and synchronization, (2) a source-to-source translator that producesan optimized program, and (3) a run-time system that provides efficient threadsand synchronization. The annotation-based programming model simplifies writingparallel programs by allowing the programmer to concentrate on the applicationand not the extensive bookkeeping involved with concurrency and synchronization;moreover, the annotations never reference any particulars of the underlyinghardware.
dc.language.isoenen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectannotationsen_US
dc.subjectCen_US
dc.subjectcompileren_US
dc.subjectgossameren_US
dc.subjectparallelen_US
dc.subjectprogramming languagesen_US
dc.titleGossamer: A Lightweight Approach to Using Multicore Machinesen_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.identifier.oclc752261012en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberLowenthal, David K.en_US
dc.contributor.committeememberDebray, Saumya K.en_US
dc.contributor.committeememberHartman, John H.en_US
dc.identifier.proquest11158en_US
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.namePh.D.en_US
refterms.dateFOA2018-06-14T23:04:31Z
html.description.abstractThe key to performance improvements in the multicore era is for software toutilize the newly available concurrency. Consequently, programmers will have tolearn new programming techniques, and software systems will have to be able tomanage the parallelism effectively. The challenge is to do so simply, portably,and efficiently.This dissertation presents a lightweight programming framework called Gossamerthat is easy to use, enables the solution of a broad range of parallelprogramming problems, and produces efficient code. Gossamer supports task andrecursive parallelism, iterative parallelism, domain decomposition, pipelinedcomputations, and MapReduce computations. Gossamer contains (1) a set ofhigh-level annotations that one adds to a sequential program to specifyconcurrency and synchronization, (2) a source-to-source translator that producesan optimized program, and (3) a run-time system that provides efficient threadsand synchronization. The annotation-based programming model simplifies writingparallel programs by allowing the programmer to concentrate on the applicationand not the extensive bookkeeping involved with concurrency and synchronization;moreover, the annotations never reference any particulars of the underlyinghardware.


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