dc.contributor.author | Rabbani, Amir H. | en_US |
dc.contributor.author | Khiat, Soufiane | en_US |
dc.contributor.editor | Holden, Daniel | en_US |
dc.date.accessioned | 2020-10-04T14:46:49Z | |
dc.date.available | 2020-10-04T14:46:49Z | |
dc.date.issued | 2020 | |
dc.identifier.isbn | 978-3-03868-129-8 | |
dc.identifier.issn | 1727-5288 | |
dc.identifier.uri | https://doi.org/10.2312/sca.20201221 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/sca20201221 | |
dc.description.abstract | We present separable Poisson filters to accelerate the projection step in Eulerian fluid simulation. These filters are analytically computed offline and are easy to integrate into any fluid algorithm with a Poisson pressure computation step. We take advantage of the recursive structure of the Jacobi method to construct and then reduce a kernel that is used to solve the Poisson pressure entirely on GPU. Our method demonstrates promising speedups that scale well with both the grid resolution and the target Jacobi iteration. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.subject | Computing methodologies | |
dc.subject | Physical simulation | |
dc.title | Fast Eulerian Fluid Simulation In Games Using Poisson Filters | en_US |
dc.description.seriesinformation | Eurographics/ ACM SIGGRAPH Symposium on Computer Animation - Showcases | |
dc.description.sectionheaders | Showcases | |
dc.identifier.doi | 10.2312/sca.20201221 | |
dc.identifier.pages | 11-13 | |