Parallelization of Stochastic Evolution
The complexity involved in VLSI design and its sub-problems has always made them ideal application areas for non-eterministic iterative heuristics. However, the major drawback has been the large runtime involved in reaching acceptable solutions especially in the case of multi-objective optimization...
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| مؤلفون آخرون: | |
| التنسيق: | masterThesis |
| منشور في: |
2006
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://eprints.kfupm.edu.sa/id/eprint/262/1/Final-thesis.pdf |
| الوسوم: |
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| _version_ | 1864513379811459072 |
|---|---|
| author | Khan, Khawar |
| author2 | unknown |
| author2_role | author |
| author_facet | Khan, Khawar unknown |
| author_role | author |
| dc.creator.none.fl_str_mv | Khan, Khawar unknown |
| dc.date.none.fl_str_mv | 2006-05-28 2020 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/262/1/Final-thesis.pdf (2006) Parallelization of Stochastic Evolution. Masters thesis, King Fahd University of Petroleun and Minerals. |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/262/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Computer |
| dc.title.none.fl_str_mv | Parallelization of Stochastic Evolution |
| dc.type.none.fl_str_mv | Thesis NonPeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/masterThesis |
| description | The complexity involved in VLSI design and its sub-problems has always made them ideal application areas for non-eterministic iterative heuristics. However, the major drawback has been the large runtime involved in reaching acceptable solutions especially in the case of multi-objective optimization problems. Among the acceleration techniques proposed, parallelization of iterative heuristics is a promising one. The motivation for Parallel CAD include faster runtimes, handling of larger problem sizes, and exploration of larger search space. In this work, the development of parallel algorithms for Stochastic Evolution, applied on multi-objective VLSI cell-placement problem is presented. In VLSI circuit design, placement is the process of arranging circuit blocks on a layout. In standard cell design, placement consists of determining optimum positions of all blocks on the layout to satisfy the constraint and improve a number of objectives. The placement objectives in our work are to reduce power dissipation and wire-length while improving performance (timing). The parallelization is achieved on a cluster of workstations interconnected by a low-latency network, by using MPI communication libraries. Circuits from ISCAS-89 are used as benchmarks. Results for parallel Stochastic Evolution are compared with its sequential counterpart as well as with the results achieved by parallel versions of Simulated Annealing as a reference point for both, the quality of solution as well as the execution time. After parallelization, linear and super linear speed-ups were obtained, with no degradation in quality of the solution. |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| id | KFUPM_8b7f7b3d939ba761d701d36f85d8ce68 |
| identifier_str_mv | (2006) Parallelization of Stochastic Evolution. Masters thesis, King Fahd University of Petroleun and Minerals. |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::262 |
| publishDate | 2006 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Parallelization of Stochastic EvolutionKhan, KhawarunknownComputerThe complexity involved in VLSI design and its sub-problems has always made them ideal application areas for non-eterministic iterative heuristics. However, the major drawback has been the large runtime involved in reaching acceptable solutions especially in the case of multi-objective optimization problems. Among the acceleration techniques proposed, parallelization of iterative heuristics is a promising one. The motivation for Parallel CAD include faster runtimes, handling of larger problem sizes, and exploration of larger search space. In this work, the development of parallel algorithms for Stochastic Evolution, applied on multi-objective VLSI cell-placement problem is presented. In VLSI circuit design, placement is the process of arranging circuit blocks on a layout. In standard cell design, placement consists of determining optimum positions of all blocks on the layout to satisfy the constraint and improve a number of objectives. The placement objectives in our work are to reduce power dissipation and wire-length while improving performance (timing). The parallelization is achieved on a cluster of workstations interconnected by a low-latency network, by using MPI communication libraries. Circuits from ISCAS-89 are used as benchmarks. Results for parallel Stochastic Evolution are compared with its sequential counterpart as well as with the results achieved by parallel versions of Simulated Annealing as a reference point for both, the quality of solution as well as the execution time. After parallelization, linear and super linear speed-ups were obtained, with no degradation in quality of the solution.2006-05-282020ThesisNonPeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/262/1/Final-thesis.pdf (2006) Parallelization of Stochastic Evolution. Masters thesis, King Fahd University of Petroleun and Minerals. enhttps://eprints.kfupm.edu.sa/id/eprint/262/info:eu-repo/semantics/openAccessoai::2622019-11-01T13:23:17Z |
| spellingShingle | Parallelization of Stochastic Evolution Khan, Khawar Computer |
| status_str | publishedVersion |
| title | Parallelization of Stochastic Evolution |
| title_full | Parallelization of Stochastic Evolution |
| title_fullStr | Parallelization of Stochastic Evolution |
| title_full_unstemmed | Parallelization of Stochastic Evolution |
| title_short | Parallelization of Stochastic Evolution |
| title_sort | Parallelization of Stochastic Evolution |
| topic | Computer |
| url | https://eprints.kfupm.edu.sa/id/eprint/262/1/Final-thesis.pdf |