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dc.contributor.advisorSrikant, Y N
dc.contributor.authorShenoy, U Nagaraj
dc.date.accessioned2005-12-07T05:58:25Z
dc.date.accessioned2018-07-31T04:39:26Z
dc.date.available2005-12-07T05:58:25Z
dc.date.available2018-07-31T04:39:26Z
dc.date.issued2005-12-07T05:58:25Z
dc.date.submitted1996-09
dc.identifier.urihttp://etd.iisc.ac.in/handle/2005/172
dc.identifier.srnonull
dc.description.abstractThe introduction of languages like High Performance Fortran (HPF) which allow the programmer to indicate how the arrays used in the program have to be distributed across the local memories of a multi-computer has not completely unburdened the parallel programmer from the intricacies of these architectures. In order to tap the full potential of these architectures, the compiler has to perform this crucial task of data partitioning automatically. This would not only unburden the programmer but would make the programs more efficient since the compiler can be made more intelligent to take care of the architectural nuances. The topic of this thesis namely the automatic data partitioning deals with finding the best data partition for the various arrays used in the entire program in such a way that the cost of execution of the entire program is minimized. The compiler could resort to runtime redistribution of the arrays at various points in the program if found profitable. Several aspects of this problem have been proven to be NP-complete. Other researchers have suggested heuristic solutions to solve this problem. In this thesis we propose a genetic algorithm namely the Hierarchical Genetic Search algorithm to solve this problem.en
dc.description.sponsorshipCDACen
dc.format.extent1091751 bytes
dc.format.mimetypeapplication/postscript
dc.language.isoen
dc.publisherIndian Institute of Scienceen
dc.rightsI grant Indian Institute of Science the right to archive and to make available my thesis or dissertation in whole or in part in all forms of media, now hereafter known. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation.en
dc.subject.classificationComputer and Information Scienceen
dc.subject.keywordGenetic Searchen
dc.subject.keywordAutomatic Data Partitioningen
dc.subject.keywordParallelizing Compileren
dc.subject.keywordMultiprogrammingen
dc.subject.keywordParallel Processingen
dc.subject.keywordDistributed Memory Multi-Computersen
dc.subject.keywordDistributed Memory Machinesen
dc.subject.keywordGenetic Algorithmsen
dc.subject.keywordHierarchical Genetic Search (HGS)en
dc.titleAutomatic Data Partitioning By Hierarchical Genetic Searchen
dc.typeElectronic Thesis and Dissertationen
dc.degree.namePhDen
dc.degree.levelDoctoralen
dc.degree.grantorIndian Institute of Scienceen
dc.degree.disciplineFaculty of Engineeringen


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