High performance computing simulations of self-gravity in astronomical agglomerates

 

Autor(es):

Rocchetti, Néstor ; Nesmachnow, Sergio ; Tancredi Machado, Gonzalo José

Tipo:

Preprint

Versión:

Enviado

Financiadores:

ANII: FCE_1_2019_1_156451

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.

Año:

2021

Idioma:

Inglés

Temas:

Simulation
High-performance computing
Self-gravity
Astronomical agglomerates

Institución:

Universidad de la República

Repositorio:

COLIBRI

Enlace(s):

https://hdl.handle.net/20.500.12008/35263

Nivel de acceso:

Acceso abierto