Modeling, Predicting, And Optimizing Parallel Performance Of Grid Stuctured Problems

dc.contributor.advisorJeffrey S. Scroggs, Committee Memberen_US
dc.contributor.advisorEdward W. Davis, Committee Memberen_US
dc.contributor.advisorRex A. Dwyer, Committee Memberen_US
dc.contributor.advisorRobert E. Funderlic, Committee Chairen_US
dc.contributor.advisorCarla D. Savage, Committee Memberen_US
dc.contributor.authorSmith, Frank Andersonen_US
dc.date.accessioned2010-04-02T18:28:08Z
dc.date.available2010-04-02T18:28:08Z
dc.date.issued2004-06-04en_US
dc.degree.disciplineComputer Scienceen_US
dc.degree.leveldissertationen_US
dc.degree.namePhDen_US
dc.description.abstractThe performance of parallel computers can be greatly affected by a user's choices of data distribution and logical processor configuration. Selecting optimal choices for such user specifiable parameters may be easier if the performance of the target machine can be predicted by a performance model. Models for parallel performance on the IBM SP for grid structured problems are considered. Such problems are ubiquitous in scientific computing and frequently are characterized by a nearest neighbor communication pattern. Bounds are derived for the size of the solution space of data distributions and logical processor configurations for problems with nearest neighbor communication. Proofs are derived that exclude a substantial number of non-optimal choices of data distribution and logical processor configuration. Algorithms are given that are intended to predict parallel performance for a model application and allow the user to select optimal choices for parameters that can be specified. Experimental evidence is presented that suggests that performance on the SP is characterized fairly accurately by a specific model. Experimental evidence also suggests that an algorithm exists to optimize a user's choices of data distribution and logical processor configuration for grid structured problems on the SP.en_US
dc.identifier.otheretd-05172004-003720en_US
dc.identifier.urihttp://www.lib.ncsu.edu/resolver/1840.16/3229
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectparallel performanceen_US
dc.subjectperformance modelingen_US
dc.subjectnearest neighbor communicationen_US
dc.subjectoptimizationen_US
dc.titleModeling, Predicting, And Optimizing Parallel Performance Of Grid Stuctured Problemsen_US

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
etd.pdf
Size:
1.1 MB
Format:
Adobe Portable Document Format

Collections