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CPU Ray Tracing of Tree-Based Adaptive Mesh Refinement Data.
Wang, Feng; Marshak, Nathan; Usher, Will; Burstedde, Carsten; Knoll, Aaron; Heister, Timo; Johnson, Chris R.
Afiliação
  • Wang F; SCI Institute, University of Utah.
  • Marshak N; SCI Institute, University of Utah.
  • Usher W; SCI Institute, University of Utah.
  • Burstedde C; Intel Corp.
  • Knoll A; Institute for Numerical Simulation, University of Bonn.
  • Heister T; Intel Corp.
  • Johnson CR; School of Mathematical and Statistical Sciences, Clemson University.
Comput Graph Forum ; 39(3): 1-12, 2020 Jun.
Article em En | MEDLINE | ID: mdl-34671172
ABSTRACT
Adaptive mesh refinement (AMR) techniques allow for representing a simulation's computation domain in an adaptive fashion. Although these techniques have found widespread adoption in high-performance computing simulations, visualizing their data output interactively and without cracks or artifacts remains challenging. In this paper, we present an efficient solution for direct volume rendering and hybrid implicit isosurface ray tracing of tree-based AMR (TB-AMR) data. We propose a novel reconstruction strategy, Generalized Trilinear Interpolation (GTI), to interpolate across AMR level boundaries without cracks or discontinuities in the surface normal. We employ a general sparse octree structure supporting a wide range of AMR data, and use it to accelerate volume rendering, hybrid implicit isosurface rendering and value queries. We demonstrate that our approach achieves artifact-free isosurface and volume rendering and provides higher quality output images compared to existing methods at interactive rendering rates.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Comput Graph Forum Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Comput Graph Forum Ano de publicação: 2020 Tipo de documento: Article