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RXMesh

Authors :
Serban D. Porumbescu
John D. Owens
Ahmed H. Mahmoud
Source :
ACM Transactions on Graphics. 40:1-16
Publication Year :
2021
Publisher :
Association for Computing Machinery (ACM), 2021.

Abstract

We propose a new static high-performance mesh data structure for triangle surface meshes on the GPU. Our data structure is carefully designed for parallel execution while capturing mesh locality and confining data access, as much as possible, within the GPU's fast "shared memory." We achieve this by subdividing the mesh into patches and representing these patches compactly using a matrix-based representation. Our patching technique is decorated with ribbons , thin mesh strips around patches that eliminate the need to communicate between different computation thread blocks, resulting in consistent high throughput. We call our data structure RXMesh : Ribbon-matriX Mesh. We hide the complexity of our data structure behind a flexible but powerful programming model that helps deliver high performance by inducing load balance even in highly irregular input meshes. We show the efficacy of our programming model on common geometry processing applications---mesh smoothing and filtering, geodesic distance, and vertex normal computation. For evaluation, we benchmark our data structure against well-optimized GPU and (single and multi-core) CPU data structures and show significant speedups.

Details

ISSN :
15577368 and 07300301
Volume :
40
Database :
OpenAIRE
Journal :
ACM Transactions on Graphics
Accession number :
edsair.doi.dedup.....4a6ec747f8a35e4b20f8efa8d70ec6cb
Full Text :
https://doi.org/10.1145/3450626.3459748