Parallel physical optimization algorithms for allocating data to multicomputer nodes
Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. They are based on simulated annealing, neural networks and genetic algorithms. All three algorithms deviate from the sequential versions in order to achieve acceptable speedups. The pa...
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| مؤلفون آخرون: | |
| التنسيق: | article |
| منشور في: |
1994
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/2950 http://dx.doi.org/10.1007/BF01666908 http://link.springer.com/article/10.1007/BF01666908 |
| الوسوم: |
إضافة وسم
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| _version_ | 1864513459494846464 |
|---|---|
| author | Mansour, Nashat |
| author2 | Fox, Geoffrey C. |
| author2_role | author |
| author_facet | Mansour, Nashat Fox, Geoffrey C. |
| author_role | author |
| dc.creator.none.fl_str_mv | Mansour, Nashat Fox, Geoffrey C. |
| dc.date.none.fl_str_mv | 1994 2016-01-25T14:05:19Z 2016-01-25T14:05:19Z 2016-01-25 |
| dc.identifier.none.fl_str_mv | 0920-8542 http://hdl.handle.net/10725/2950 http://dx.doi.org/10.1007/BF01666908 Mansour, N., & Fox, G. C. (1994). Parallel physical optimization algorithms for allocating data to multicomputer nodes. The Journal of Supercomputing, 8(1), 53-80. http://link.springer.com/article/10.1007/BF01666908 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | The Journal of Supercomputing |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | Parallel physical optimization algorithms for allocating data to multicomputer nodes |
| dc.type.none.fl_str_mv | Article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. They are based on simulated annealing, neural networks and genetic algorithms. All three algorithms deviate from the sequential versions in order to achieve acceptable speedups. The parallel simulated annealing (PSA) and neural network (PNN) algorithms include communication schemes that are adapted to the properties of the allocation problem and of the algorithms themselves for maintaining both good solutions and reasonable execution times. The parallel genetic algorithm (PGA) is based on a natural model of evolution. The performances of these algorithms are evaluated and compared. The three parallel algorithms maintain the good solution qualities of their sequential counterparts. Their comparison shows their suitability for different applications. For example, PGA yields the best solutions, but it is the slowest of the three. PNN is the fastest, but it yields lower quality solutions. PSA's performance lies in the middle. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | LAURepo_3307223562d43b8c8a535a9dcdc253b4 |
| identifier_str_mv | 0920-8542 Mansour, N., & Fox, G. C. (1994). Parallel physical optimization algorithms for allocating data to multicomputer nodes. The Journal of Supercomputing, 8(1), 53-80. |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/2950 |
| publishDate | 1994 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Parallel physical optimization algorithms for allocating data to multicomputer nodesMansour, NashatFox, Geoffrey C.Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. They are based on simulated annealing, neural networks and genetic algorithms. All three algorithms deviate from the sequential versions in order to achieve acceptable speedups. The parallel simulated annealing (PSA) and neural network (PNN) algorithms include communication schemes that are adapted to the properties of the allocation problem and of the algorithms themselves for maintaining both good solutions and reasonable execution times. The parallel genetic algorithm (PGA) is based on a natural model of evolution. The performances of these algorithms are evaluated and compared. The three parallel algorithms maintain the good solution qualities of their sequential counterparts. Their comparison shows their suitability for different applications. For example, PGA yields the best solutions, but it is the slowest of the three. PNN is the fastest, but it yields lower quality solutions. PSA's performance lies in the middle.PublishedN/A2016-01-25T14:05:19Z2016-01-25T14:05:19Z19942016-01-25Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article0920-8542http://hdl.handle.net/10725/2950http://dx.doi.org/10.1007/BF01666908Mansour, N., & Fox, G. C. (1994). Parallel physical optimization algorithms for allocating data to multicomputer nodes. The Journal of Supercomputing, 8(1), 53-80.http://link.springer.com/article/10.1007/BF01666908enThe Journal of Supercomputinginfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/29502017-04-10T11:03:00Z |
| spellingShingle | Parallel physical optimization algorithms for allocating data to multicomputer nodes Mansour, Nashat |
| status_str | publishedVersion |
| title | Parallel physical optimization algorithms for allocating data to multicomputer nodes |
| title_full | Parallel physical optimization algorithms for allocating data to multicomputer nodes |
| title_fullStr | Parallel physical optimization algorithms for allocating data to multicomputer nodes |
| title_full_unstemmed | Parallel physical optimization algorithms for allocating data to multicomputer nodes |
| title_short | Parallel physical optimization algorithms for allocating data to multicomputer nodes |
| title_sort | Parallel physical optimization algorithms for allocating data to multicomputer nodes |
| url | http://hdl.handle.net/10725/2950 http://dx.doi.org/10.1007/BF01666908 http://link.springer.com/article/10.1007/BF01666908 |