Properties of simulated annealing and genetic algorithms for mapping data to multicomputers

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dc.contributor.author Mansour, Nashat
dc.contributor.author Kawash, Jalal
dc.contributor.author Diab, Hassan
dc.date.accessioned 2016-01-26T13:32:02Z
dc.date.available 2016-01-26T13:32:02Z
dc.date.copyright 1997
dc.date.issued 2016-01-26
dc.identifier.issn 1063-7192 en_US
dc.identifier.uri http://hdl.handle.net/10725/2962
dc.description.abstract We experimentally analyze some properties of simulated annealing algorithms (SA) and genetic algorithms (GA) for mapping data to multicomputers. These properties include sensitiviiy to user parameters, fault tolerance capability, and applicability to different multicomputer topologies. Some user parameters are included in the objective function and are architecture- or problem-dependent parameters. The others are used in the GA and SA algorithms. The fault tolerance capability is demonstrated by mapping data to a multicomputer with some faulty processors. We assume a hypercube multicomputer architecture in most experiments. However, mapping to mesh, array, ring, tree, and star graph topologies is also demonstrated. The experimental 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 Properties of simulated annealing and genetic algorithms for mapping data to multicomputers en_US
dc.type Article en_US
dc.description.version Published en_US
dc.author.school SAS en_US
dc.author.idnumber 198629170 en_US
dc.author.woa N/A en_US
dc.author.department Computer Science and Mathematics en_US
dc.description.embargo N/A en_US
dc.relation.journal Parallel Algorithms and Applications en_US
dc.journal.volume 12 en_US
dc.journal.issue 4 en_US
dc.article.pages 249-296 en_US
dc.keywords Automatic parallelization en_US
dc.keywords Data mapping en_US
dc.keywords Load partitioning and balancing en_US
dc.keywords Scheduling en_US
dc.keywords Parallelizing compilers en_US
dc.identifier.doi http://dx.doi.org/10.1080/01495739708941426 en_US
dc.identifier.ctation Mansour, N., Kawash, J., & Diab, H. (1997). Properties of simulated annealing and genetic algorithms for mapping data to multicomputers. Parallel Algorithms and Applications, 12(4), 279-296. en_US
dc.author.email nmansour@lau.edu.lb
dc.identifier.url http://www.tandfonline.com/doi/abs/10.1080/01495739708941426

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