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General applicability of genetic and simulated annealing algorithms for data mapping

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dc.contributor.author Mansour, Nashat
dc.contributor.author Kawash, Jalal
dc.contributor.author Diab, Hassan
dc.date.accessioned 2018-06-04T09:24:11Z
dc.date.available 2018-06-04T09:24:11Z
dc.date.copyright 1995 en_US
dc.date.issued 2018-06-04
dc.identifier.uri http://hdl.handle.net/10725/7976
dc.description.abstract We experimentally analyze the general applicability of genetic algorithms (GA) and simulated annealing algorithms (SA) for mapping data to multicomputers. The results show that the GA and SA are insensitive to user parameters in wide ranges, completely fault tolerant, and unbiased towards particular multicomputer topologies. These properties of flexibility and general applicability, which are lacking in other heuristic algorithms, make the GA and SA attractive for automatic parallelization systems. en_US
dc.language.iso en en_US
dc.title General applicability of genetic and simulated annealing algorithms for data mapping en_US
dc.type Conference Paper / Proceeding en_US
dc.author.school SAS en_US
dc.author.idnumber 198629170 en_US
dc.author.department Computer Science and Mathematics en_US
dc.description.embargo N/A en_US
dc.keywords Automatic parallelization en_US
dc.keywords Data mapping en_US
dc.keywords Load partitioning and balancing en_US
dc.identifier.ctation Kawash, J., Mansour, N., & Diab, H. B. (1995). General Applicability of Genetic and Simulated Annealing Algorithms for Data Mapping. In Parallel and Distributed Computing and Systems (pp. 225-228). en_US
dc.author.email nmansour@lau.edu.lb en_US
dc.conference.date October 19-21, 1995 en_US
dc.conference.place Washington, D.C., USA en_US
dc.conference.title Proceedings of the Seventh IASTED/ISMM International Conference on Parallel and Distributed Computing and Systems en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url https://www.researchgate.net/profile/Hassan_Diab2/publication/220800620_General_Applicability_of_Genetic_and_Simulated_Annealing_Algorithms_for_Data_Mapping/links/0046352009a7781929000000.pdf en_US
dc.orcid.id https://orcid.org/0000-0002-3603-8284 en_US
dc.publication.date 1995 en_US
dc.author.affiliation Lebanese American University en_US


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