english Icono del idioma   español Icono del idioma  

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12008/35263 How to cite
Title: High performance computing simulations of self-gravity in astronomical agglomerates
Authors: Rocchetti, Néstor
Nesmachnow, Sergio
Tancredi Machado, Gonzalo José
Type: Preprint
Keywords: Simulation, High-performance computing, Self-gravity, Astronomical agglomerates
Issue Date: 2021
Abstract: 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.
Description: Versión permitida: preprint
Sponsors: ANII: FCE_1_2019_1_156451
Citation: 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.
License: Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Appears in Collections:Publicaciones académicas y científicas - Facultad de Ciencias

Files in This Item:
File Description SizeFormat  
10.11770037549721998766.pdf1,39 MBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons