Enhancing Solar Convection Analysis With Multi‐Core Processors and GPUs
ABSTRACT In the realm of astrophysical numerical calculations, the demand for enhanced computing power is imperative. The time‐consuming nature of calculations, particularly in the domain of solar convection, poses a significant challenge for Astrophysicists seeking to analyze new data efficiently....
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Engineering Reports |
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| Online Access: | https://doi.org/10.1002/eng2.13050 |
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| author | Arash Heidari Zahra Amiri Mohammad Ali Jabraeil Jamali Nima Jafari Navimipour |
| author_facet | Arash Heidari Zahra Amiri Mohammad Ali Jabraeil Jamali Nima Jafari Navimipour |
| author_sort | Arash Heidari |
| collection | DOAJ |
| description | ABSTRACT In the realm of astrophysical numerical calculations, the demand for enhanced computing power is imperative. The time‐consuming nature of calculations, particularly in the domain of solar convection, poses a significant challenge for Astrophysicists seeking to analyze new data efficiently. Because they let different kinds of data be worked on separately, parallel algorithms are a good way to speed up this kind of work. A lot of this study is about how to use both multi‐core computers and GPUs to do math work about solar energy at the same time. Cutting down on the time it takes to work with data is the main goal. This way, new data can be looked at more quickly and without having to practice for a long time. It works well when you do things in parallel, especially when you use GPUs for 3D tasks, which speeds up the work a lot. This is proof of how important it is to adjust the parallelization methods based on the size of the numbers. But for 2D math, computers with more than one core work better. The results not only fix bugs in models of solar convection, but they also show that speed changes a little based on the gear and how it is processed. |
| format | Article |
| id | doaj-art-b2a32769d3ad461ba78d632ccf151c96 |
| institution | Kabale University |
| issn | 2577-8196 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Engineering Reports |
| spelling | doaj-art-b2a32769d3ad461ba78d632ccf151c962025-01-31T00:22:48ZengWileyEngineering Reports2577-81962025-01-0171n/an/a10.1002/eng2.13050Enhancing Solar Convection Analysis With Multi‐Core Processors and GPUsArash Heidari0Zahra Amiri1Mohammad Ali Jabraeil Jamali2Nima Jafari Navimipour3Department of Computer Engineering, Faculty of Engineering and Natural Science İstanbul Atlas University Istanbul TurkeyIvy College of Business lowa State University Ames USADepartment of Computer Engineering, Shabestar Branch Islamic Azad University Shabestar IranDepartment of Computer Engineering Kadir Has Universitesi Istanbul TurkeyABSTRACT In the realm of astrophysical numerical calculations, the demand for enhanced computing power is imperative. The time‐consuming nature of calculations, particularly in the domain of solar convection, poses a significant challenge for Astrophysicists seeking to analyze new data efficiently. Because they let different kinds of data be worked on separately, parallel algorithms are a good way to speed up this kind of work. A lot of this study is about how to use both multi‐core computers and GPUs to do math work about solar energy at the same time. Cutting down on the time it takes to work with data is the main goal. This way, new data can be looked at more quickly and without having to practice for a long time. It works well when you do things in parallel, especially when you use GPUs for 3D tasks, which speeds up the work a lot. This is proof of how important it is to adjust the parallelization methods based on the size of the numbers. But for 2D math, computers with more than one core work better. The results not only fix bugs in models of solar convection, but they also show that speed changes a little based on the gear and how it is processed.https://doi.org/10.1002/eng2.13050graphic processormulti‐core processorparallel algorithmsolar convection |
| spellingShingle | Arash Heidari Zahra Amiri Mohammad Ali Jabraeil Jamali Nima Jafari Navimipour Enhancing Solar Convection Analysis With Multi‐Core Processors and GPUs Engineering Reports graphic processor multi‐core processor parallel algorithm solar convection |
| title | Enhancing Solar Convection Analysis With Multi‐Core Processors and GPUs |
| title_full | Enhancing Solar Convection Analysis With Multi‐Core Processors and GPUs |
| title_fullStr | Enhancing Solar Convection Analysis With Multi‐Core Processors and GPUs |
| title_full_unstemmed | Enhancing Solar Convection Analysis With Multi‐Core Processors and GPUs |
| title_short | Enhancing Solar Convection Analysis With Multi‐Core Processors and GPUs |
| title_sort | enhancing solar convection analysis with multi core processors and gpus |
| topic | graphic processor multi‐core processor parallel algorithm solar convection |
| url | https://doi.org/10.1002/eng2.13050 |
| work_keys_str_mv | AT arashheidari enhancingsolarconvectionanalysiswithmulticoreprocessorsandgpus AT zahraamiri enhancingsolarconvectionanalysiswithmulticoreprocessorsandgpus AT mohammadalijabraeiljamali enhancingsolarconvectionanalysiswithmulticoreprocessorsandgpus AT nimajafarinavimipour enhancingsolarconvectionanalysiswithmulticoreprocessorsandgpus |