Enhancing Solar Convection Analysis With Multi‐Core Processors and GPUs
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| Veröffentlicht in: | Engineering Reports vol. 7, no. 1 (Jan 1, 2025) |
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John Wiley & Sons, Inc.
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| 001 | 3161574921 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2577-8196 | ||
| 024 | 7 | |a 10.1002/eng2.13050 |2 doi | |
| 035 | |a 3161574921 | ||
| 045 | 0 | |b d20250101 | |
| 100 | 1 | |a Heidari, Arash |u Department of Computer Engineering, Faculty of Engineering and Natural Science, İstanbul Atlas University, Istanbul, Turkey | |
| 245 | 1 | |a Enhancing Solar Convection Analysis With Multi‐Core Processors and GPUs | |
| 260 | |b John Wiley & Sons, Inc. |c Jan 1, 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Parallel processing | ||
| 653 | |a Data analysis | ||
| 653 | |a Simulation | ||
| 653 | |a Computers | ||
| 653 | |a Astrophysics | ||
| 653 | |a Astronomy | ||
| 653 | |a Cutting speed | ||
| 653 | |a Adaptability | ||
| 653 | |a C plus plus | ||
| 653 | |a Graphics processing units | ||
| 653 | |a Solar energy | ||
| 653 | |a Optimization | ||
| 653 | |a Stars & galaxies | ||
| 653 | |a Solar convection (astronomy) | ||
| 653 | |a Demand analysis | ||
| 653 | |a Numerical analysis | ||
| 653 | |a Algorithms | ||
| 653 | |a Sun | ||
| 653 | |a High performance computing | ||
| 653 | |a Efficiency | ||
| 700 | 1 | |a Amiri, Zahra |u Ivy College of Business, lowa State University, Ames, USA | |
| 700 | 1 | |a Jamali, Mohammad Ali Jabraeil |u Department of Computer Engineering, Shabestar Branch, Islamic Azad University, Shabestar, Iran | |
| 700 | 1 | |a Navimipour, Nima Jafari |u Department of Computer Engineering, Kadir Has Universitesi, Istanbul, Turkey | |
| 773 | 0 | |t Engineering Reports |g vol. 7, no. 1 (Jan 1, 2025) | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3161574921/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3161574921/fulltext/embedded/H09TXR3UUZB2ISDL?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3161574921/fulltextPDF/embedded/H09TXR3UUZB2ISDL?source=fedsrch |