A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments
Abstract This paper applies a simulated evolution (SE) approach to the problem of matching and scheduling dependent tasks in a heterogeneous suite of computers interconnected via a high-speed network. The various steps of the SE approach are discussed in details. Goodness functions required by SE ar...
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| Other Authors: | , , |
| Format: | article |
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2020
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| Online Access: | https://eprints.kfupm.edu.sa/id/eprint/268/1/J_Barada_EAAI_September2002.pdf |
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| _version_ | 1864513379816701952 |
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| author | Barada, Hassan |
| author2 | Sait, Sadiq M. Baig, N. unknown |
| author2_role | author author author |
| author_facet | Barada, Hassan Sait, Sadiq M. Baig, N. unknown |
| author_role | author |
| dc.creator.none.fl_str_mv | Barada, Hassan Sait, Sadiq M. Baig, N. unknown |
| dc.date.*.fl_str_mv | 2020 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/268/1/J_Barada_EAAI_September2002.pdf A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 15 (5): 491-500 SEP 2002. |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/268/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Computer |
| dc.title.none.fl_str_mv | A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments |
| dc.type.none.fl_str_mv | Article PeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | Abstract This paper applies a simulated evolution (SE) approach to the problem of matching and scheduling dependent tasks in a heterogeneous suite of computers interconnected via a high-speed network. The various steps of the SE approach are discussed in details. Goodness functions required by SE are designed and explained. Experimental results applied on various types of workloads are analyzed. Workloads are characterized according to the connectivity, heterogeneity, and communication-to-cost ratio of the task graphs representing the application tasks. The performance of SE is compared with a genetic algorithm approach for the same problem with respect to the quality of solutions generated, and timing requirements of the algorithms. r 2003 Elsevier Science Ltd. All rights reserved. Keywords: Scheduling; Optimization; Heuristics; Heterogeneous systems |
| eu_rights_str_mv | openAccess |
| format | article |
| id | KFUPM_a54f205f4fdaaa20259c08a4468fb0f9 |
| identifier_str_mv | A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 15 (5): 491-500 SEP 2002. |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::268 |
| publishDate | 2020 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | A simulated evolution approach to task-matching and scheduling in heterogeneous computing environmentsBarada, HassanSait, Sadiq M.Baig, N.unknownComputerAbstract This paper applies a simulated evolution (SE) approach to the problem of matching and scheduling dependent tasks in a heterogeneous suite of computers interconnected via a high-speed network. The various steps of the SE approach are discussed in details. Goodness functions required by SE are designed and explained. Experimental results applied on various types of workloads are analyzed. Workloads are characterized according to the connectivity, heterogeneity, and communication-to-cost ratio of the task graphs representing the application tasks. The performance of SE is compared with a genetic algorithm approach for the same problem with respect to the quality of solutions generated, and timing requirements of the algorithms. r 2003 Elsevier Science Ltd. All rights reserved. Keywords: Scheduling; Optimization; Heuristics; Heterogeneous systemsArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/268/1/J_Barada_EAAI_September2002.pdf A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 15 (5): 491-500 SEP 2002. enhttps://eprints.kfupm.edu.sa/id/eprint/268/2020info:eu-repo/semantics/openAccessoai::2682019-11-01T13:23:20Z |
| spellingShingle | A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments Barada, Hassan Computer |
| status_str | publishedVersion |
| title | A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments |
| title_full | A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments |
| title_fullStr | A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments |
| title_full_unstemmed | A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments |
| title_short | A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments |
| title_sort | A simulated evolution approach to task-matching and scheduling in heterogeneous computing environments |
| topic | Computer |
| url | https://eprints.kfupm.edu.sa/id/eprint/268/1/J_Barada_EAAI_September2002.pdf |