A SIMILARITY-BASED ANALYSIS TOOL FOR SCIENTIFIC APPLICATION PORTING

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dc.contributor.advisorChapman, Barbara M.
dc.contributor.committeeMemberGabriel, Edgar
dc.contributor.committeeMemberGarbey, Marc
dc.contributor.committeeMemberDeng, Zhigang
dc.contributor.committeeMemberBassler, Kevin E.
dc.creatorDing, Wei 1981-
dc.date.accessioned2014-02-13T15:12:23Z
dc.date.available2014-02-13T15:12:23Z
dc.date.createdDecember 2013
dc.date.issued2013-12
dc.date.updated2014-02-13T15:12:28Z
dc.description.abstractPorting applications to a new system is a nontrivial job in the HPC field. It is a very time-consuming, labor-intensive process, and the quality of the results will depend critically on the experience of the experts involved. In order to ease the porting process, we propose a methodology to address an important aspect of software porting that receives little attention, namely planning support. When a scientific application consisting of many subroutines is to be ported, the selection of key subroutines greatly impacts the productivity and overall porting strategy, because these subroutines may represent a significant feature of the code in terms of functionality, code structure, or performance. They may also serve as indicators of the difficulty and amount of effort involved in porting a code to a new platform. The proposed methodology is based on the idea that a set of similar subroutines can be ported with similar strategies and result in a similar-quality porting. By viewing subroutines as data and operator sequences, analogous to DNA sequences, we are able to use various bio-informatics techniques to conduct the similarity analysis of subroutines while avoiding NP-complete complexities of other approaches. To further improve accuracy for porting, we also merged some other code metrics and cost-model metrics for similarity analysis to capture the internal code characteristics. In this dissertation, we describe our methodology, which includes presentation of a tool called Klonos. To evaluate the effectiveness of Klonos, we used it to conduct experiments to find strategies for porting of several scientific benchmarks and a large scientific application. Our experiment shows Klonos is very effective for providing a systematic porting plan to guide the users during their porting process of reusing similar porting strategies for similar code regions.
dc.description.departmentComputer Science, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10657/518
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectKlonos
dc.subjectCompiler Tool
dc.subjectSoftware Porting
dc.subjectSimilarity analysis
dc.subjectFamily distance tree
dc.subjectPorting plan
dc.titleA SIMILARITY-BASED ANALYSIS TOOL FOR SCIENTIFIC APPLICATION PORTING
dc.type.dcmiText
dc.type.genreThesis
thesis.degree.collegeCollege of Natural Sciences and Mathematics
thesis.degree.departmentComputer Science, Department of
thesis.degree.disciplineComputer Science
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.majorCompiler and High Performance Computing
thesis.degree.nameDoctor of Philosophy

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