Affiliation:
1. University of California
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.
Funder
Sandia National Laboratories
DARPA AFRL
National Science Foundation
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Graphics and Computer-Aided Design
Cited by
9 articles.
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1. IMESH: A DSL for Mesh Processing;ACM Transactions on Graphics;2024-06-25
2. Fast and robust parallel simplification algorithm for triangular mesh;Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023);2023-11-14
3. Surface Simplification using Intrinsic Error Metrics;ACM Transactions on Graphics;2023-07-26
4. Integrating GPU-Accelerated Tetrahedral Mesh Editing and Simulation;Lecture Notes in Networks and Systems;2023
5. MeshTaichi;ACM Transactions on Graphics;2022-11-30