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Título: | High performance computing simulations of self-gravity in astronomical agglomerates |
Autor: | Rocchetti, Néstor Nesmachnow, Sergio Tancredi Machado, Gonzalo José |
Tipo: | Preprint |
Palabras clave: | Simulation, High-performance computing, Self-gravity, Astronomical agglomerates |
Fecha de publicación: | 2021 |
Resumen: | This article describes the advances on the design, implementation, and evaluation of efficient algorithms for self-gravity simulations in astronomical agglomerates. Three algorithms are presented and evaluated: the occupied cells method, and two variations of the Barnes & Hut method using an octal and a binary tree. Two scenarios are considered in the evaluation: two agglomerates orbiting each other and a collapsing cube. Results show that the proposed octal tree Barnes & Hut method allows improving the performance of the self-gravity calculation up to 100 with respect to the occupied cell method, while having a correct numerical accuracy. The proposed algorithms are efficient and accurate methods for self-gravity simulations in astronomical agglomerates. |
Descripción: | Versión permitida: preprint |
Financiadores: | ANII: FCE_1_2019_1_156451 |
Citación: | Rocchetti, N, Nesmachnow, S y Tancredi Machado, G. "High performance computing simulations of self-gravity in astronomical agglomerates" [preprint]. Publicado en: Simulation, 2021. 20 h. DOI: 10.1177/2F0037549721998766. |
Aparece en las colecciones: | Publicaciones académicas y científicas - Facultad de Ciencias |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | ||
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10.11770037549721998766.pdf | 1,39 MB | Adobe PDF | Visualizar/Abrir |
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