dc.contributor.author | Dravecky, Peter | en_US |
dc.contributor.author | Stephenson, Ian | en_US |
dc.contributor.editor | Vangorp, Peter | en_US |
dc.contributor.editor | Hunter, David | en_US |
dc.date.accessioned | 2023-09-12T05:44:50Z | |
dc.date.available | 2023-09-12T05:44:50Z | |
dc.date.issued | 2023 | |
dc.identifier.isbn | 978-3-03868-231-8 | |
dc.identifier.uri | https://doi.org/10.2312/cgvc.20231197 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/cgvc20231197 | |
dc.description.abstract | Particle systems in CG often encounter performance issues when all the particles rely on mutual influence, producing an O(N2) performance. The Barnes-Hut approximation is used in the field of astrophysics to provide sufficiently accurate results in O(Nlog(N)) time. Here we explore a hardware accelerated implementation of this algorithm, implemented within SideFX Houdini - the commercial tool typically used for particle work in film. We are able to demonstrate a workflow with integrates into the existing artist friendly environment, with performance improved by orders of magnitudes for typically large simulations, and negligible visual change in results. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.rights | Attribution 4.0 International License | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.subject | CCS Concepts: Computing methodologies -> Scientific visualization; Massively parallel and high-performance simulations; Massively parallel algorithms; Applied computing -> Media arts | |
dc.subject | Computing methodologies | |
dc.subject | Scientific visualization | |
dc.subject | Massively parallel and high | |
dc.subject | performance simulations | |
dc.subject | Massively parallel algorithms | |
dc.subject | Applied computing | |
dc.subject | Media arts | |
dc.title | Using The Barnes-Hut Approximation for Fast N-Body Simulations in Computer Graphics | en_US |
dc.description.seriesinformation | Computer Graphics and Visual Computing (CGVC) | |
dc.description.sectionheaders | Posters | |
dc.identifier.doi | 10.2312/cgvc.20231197 | |
dc.identifier.pages | 77-80 | |
dc.identifier.pages | 4 pages | |