GPU-based parallel programming for FEM analysis in the optimization of steel frames
Optimization of large-scale frame structures consumes a vast amount of time since the analysis of such complex systems contains several iterative processes. Mitigating computational burden and reducing this time to a reasonable level is possible by running GPU (Graphical Processing Unit) processors,...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-05-01
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| Series: | Journal of Asian Architecture and Building Engineering |
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| Online Access: | http://dx.doi.org/10.1080/13467581.2024.2345310 |
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| author | Tevfik Oğuz Örmecioğlu İbrahim Aydoğdu Hilal Tuğba Örmecioğlu |
| author_facet | Tevfik Oğuz Örmecioğlu İbrahim Aydoğdu Hilal Tuğba Örmecioğlu |
| author_sort | Tevfik Oğuz Örmecioğlu |
| collection | DOAJ |
| description | Optimization of large-scale frame structures consumes a vast amount of time since the analysis of such complex systems contains several iterative processes. Mitigating computational burden and reducing this time to a reasonable level is possible by running GPU (Graphical Processing Unit) processors, which can be found on standard computers. This study presents an algorithm for the acceleration of size optimization of steel frames by using the BBO (Biogeography-Based Optimization) method that is suitable for GPU architecture. The GPU-based parallel algorithm, designed for FEM (Finite Element Method) analysis, is applied to three hypothetical steel-frame case structures with different numbers of members and nodes; and processed on four different computers which are available on the market. The presented case studies revealed that the proposed solution’s efficiency increases as the number of members increases and confirmed the ability of the acceleration algorithm for optimization of large-scale frame structures and provided time efficiency. |
| format | Article |
| id | doaj-art-9164c4d69a994db7a2a1ded37f7fccd1 |
| institution | DOAJ |
| issn | 1347-2852 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Asian Architecture and Building Engineering |
| spelling | doaj-art-9164c4d69a994db7a2a1ded37f7fccd12025-08-20T02:58:41ZengTaylor & Francis GroupJournal of Asian Architecture and Building Engineering1347-28522025-05-012431404142510.1080/13467581.2024.23453102345310GPU-based parallel programming for FEM analysis in the optimization of steel framesTevfik Oğuz Örmecioğlu0İbrahim Aydoğdu1Hilal Tuğba Örmecioğlu2Akdeniz UniversityAkdeniz UniversityAkdeniz UniversityOptimization of large-scale frame structures consumes a vast amount of time since the analysis of such complex systems contains several iterative processes. Mitigating computational burden and reducing this time to a reasonable level is possible by running GPU (Graphical Processing Unit) processors, which can be found on standard computers. This study presents an algorithm for the acceleration of size optimization of steel frames by using the BBO (Biogeography-Based Optimization) method that is suitable for GPU architecture. The GPU-based parallel algorithm, designed for FEM (Finite Element Method) analysis, is applied to three hypothetical steel-frame case structures with different numbers of members and nodes; and processed on four different computers which are available on the market. The presented case studies revealed that the proposed solution’s efficiency increases as the number of members increases and confirmed the ability of the acceleration algorithm for optimization of large-scale frame structures and provided time efficiency.http://dx.doi.org/10.1080/13467581.2024.2345310parallel processinggpu-based algorithmbiogeography-based optimizationaccelerationfem |
| spellingShingle | Tevfik Oğuz Örmecioğlu İbrahim Aydoğdu Hilal Tuğba Örmecioğlu GPU-based parallel programming for FEM analysis in the optimization of steel frames Journal of Asian Architecture and Building Engineering parallel processing gpu-based algorithm biogeography-based optimization acceleration fem |
| title | GPU-based parallel programming for FEM analysis in the optimization of steel frames |
| title_full | GPU-based parallel programming for FEM analysis in the optimization of steel frames |
| title_fullStr | GPU-based parallel programming for FEM analysis in the optimization of steel frames |
| title_full_unstemmed | GPU-based parallel programming for FEM analysis in the optimization of steel frames |
| title_short | GPU-based parallel programming for FEM analysis in the optimization of steel frames |
| title_sort | gpu based parallel programming for fem analysis in the optimization of steel frames |
| topic | parallel processing gpu-based algorithm biogeography-based optimization acceleration fem |
| url | http://dx.doi.org/10.1080/13467581.2024.2345310 |
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