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)
1. Verfasser: Heidari, Arash
Weitere Verfasser: Amiri, Zahra, Jamali, Mohammad Ali Jabraeil, Navimipour, Nima Jafari
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John Wiley & Sons, Inc.
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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