Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994)

Includes bibliographical references.

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Kawash, Jalal Y. (author)
التنسيق: masterThesis
منشور في: 1994
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/10725/195
https://doi.org/10.26756/th.1994.4
الوسوم: إضافة وسم
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author Kawash, Jalal Y.
author_facet Kawash, Jalal Y.
author_role author
dc.creator.none.fl_str_mv Kawash, Jalal Y.
dc.date.none.fl_str_mv 1994
1994-12
2011-01-07T10:18:51Z
2011-01-07T10:18:51Z
2011-01-07
dc.identifier.none.fl_str_mv http://hdl.handle.net/10725/195
https://doi.org/10.26756/th.1994.4
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Lebanese American University
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Algorithms
Computer graphics
Parallel processing (Electronic computers)
Combinatorial optimization
Parallel computers
dc.title.none.fl_str_mv Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994)
dc.type.none.fl_str_mv Thesis
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/masterThesis
description Includes bibliographical references.
eu_rights_str_mv openAccess
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id LAURepo_ce5b37409878b0bf6b7a457325f3dbba
language_invalid_str_mv en
network_acronym_str LAURepo
network_name_str Lebanese American University repository
oai_identifier_str oai:laur.lau.edu.lb:10725/195
publishDate 1994
publisher.none.fl_str_mv Lebanese American University
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994)Kawash, Jalal Y.AlgorithmsComputer graphicsParallel processing (Electronic computers)Combinatorial optimizationParallel computersIncludes bibliographical references.We analyze the sensitivity to parameters and the general applicability of genetic algorithms and simulated annealing algorithms for mapping data to distributed-memory multicomputers, using the loosely synchronous computation model. The analysis includes sensitivity to user parameters, fault tolerance capability, and applicability to different multicomputer topologies. The user parameters are either objective function dependent or algorithm dependent. The fault tolerance capability is demonstrated by using the mapping algorithms for mapping data to a multicomputer that has some failed processors. We assume a hypercube multicomputer architecture in most experiments. However, comparative results for mesh, array, ring, tree, star graph, and fully connected topologies are presented. The mapping algorithms used are sequential hybrid genetic algorithm, versions of a distributed genetic algorithm, sequential simulated annealing algorithm, and a simulated parallel simulated annealing algorithm. The experimental results verifY that these algorithms are insensitive to user parameters in wide ranges, completely fault tolerant, and unbiased towards particular multicomputer topologies. These results support the conjecture that physical optimization algorithms are flexible and have general applicability, where these properties are necessary for the automation of the mapping process.1 bound copy: 1 v. (various pagings); ill., tables available at RNL.Lebanese American University2011-01-07T10:18:51Z2011-01-07T10:18:51Z19942011-01-071994-12Thesisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/10725/195https://doi.org/10.26756/th.1994.4eninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/1952021-03-19T09:58:57Z
spellingShingle Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994)
Kawash, Jalal Y.
Algorithms
Computer graphics
Parallel processing (Electronic computers)
Combinatorial optimization
Parallel computers
status_str publishedVersion
title Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994)
title_full Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994)
title_fullStr Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994)
title_full_unstemmed Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994)
title_short Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994)
title_sort Sensitivity to parameters and general applicability of genetic algorithms and simulated annealing algorithms for mapping data to multicomputers. (c1994)
topic Algorithms
Computer graphics
Parallel processing (Electronic computers)
Combinatorial optimization
Parallel computers
url http://hdl.handle.net/10725/195
https://doi.org/10.26756/th.1994.4