Preprint
High performance computing simulations of self-gravity in astronomical agglomerates
Fecha
2021Registro en:
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.
Autor
Rocchetti, Néstor
Nesmachnow, Sergio
Tancredi Machado, Gonzalo José
Institución
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.