CPU volume rendering of adaptive mesh refinement data

Adaptive Mesh Refinement (AMR) methods are widespread in scientific computing, and visualizing the resulting data with efficient and accurate rendering methods can be vital for enabling interactive data exploration. In this work, we detail a comprehensive solution for directly volume rendering block-structured (Berger-Colella) AMR data in the OSPRay interactive CPU ray tracing framework. In particular, we contribute a general method for representing and traversing AMR data using a kd-tree structure, and four different reconstruction options, one of which in particular (the basis function approach) is novel compared to existing methods. We demonstrate our system on two types of block-structured AMR data and compressed scalar field data, and show how it can be easily used in existing production-ready applications through a prototypical integration in the widely used visualization program ParaView.

[1]  Kwan-Liu Ma,et al.  A scalable parallel cell-projection volume rendering algorithm for three-dimensional unstructured data , 1997, Proceedings IEEE Symposium on Parallel Rendering (PRS'97).

[2]  David Ellsworth,et al.  Visualization of AMR Data With Multi-Level Dual-Mesh Interpolation , 2011, IEEE Transactions on Visualization and Computer Graphics.

[3]  Markus Wagner,et al.  Interactive Rendering with Coherent Ray Tracing , 2001, Comput. Graph. Forum.

[4]  Chandrajit L. Bajaj,et al.  Case study: Interactive rendering of adaptive mesh refinement data , 2002, IEEE Visualization, 2002. VIS 2002..

[5]  Kwan-Liu Ma,et al.  Efficient parallel volume rendering of large-scale adaptive mesh refinement data , 2013, 2013 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV).

[6]  Hans-Christian Hege,et al.  Texture-based volume rendering of adaptive mesh refinement data , 2002, The Visual Computer.

[7]  Mark F. Adams,et al.  Chombo Software Package for AMR Applications Design Document , 2014 .

[8]  Aaron Knoll,et al.  OSPRay - A CPU Ray Tracing Framework for Scientific Visualization , 2017, IEEE Transactions on Visualization and Computer Graphics.

[9]  Hans-Peter Seidel,et al.  Faster isosurface ray tracing using implicit KD-trees , 2005, IEEE Transactions on Visualization and Computer Graphics.

[10]  P. Colella,et al.  Local adaptive mesh refinement for shock hydrodynamics , 1989 .

[11]  Guillaume Colin de Verdière,et al.  High-Quality, Semi-Analytical Volume Rendering for AMR Data , 2009, IEEE Transactions on Visualization and Computer Graphics.

[12]  Hans-Christian Hege,et al.  GPU-Assisted Raycasting for Cosmological Adaptive Mesh Refinement Simulations , 2006, VG@SIGGRAPH.

[13]  Anders Ynnerman,et al.  Multiresolution Interblock Interpolation in Direct Volume Rendering , 2006, EuroVis.

[14]  D. Trebotich,et al.  An adaptive finite volume method for the incompressible Navier–Stokes equations in complex geometries , 2015 .

[15]  Nelson L. Max,et al.  Sorting for Polyhedron Compositing , 1991, Focus on Scientific Visualization.

[16]  Kenneth I. Joy,et al.  Query-Driven Visualization of Time-Varying Adaptive Mesh Refinement Data , 2008, IEEE Transactions on Visualization and Computer Graphics.

[17]  Kellogg S. Booth,et al.  Report from the chair , 1986 .

[18]  Ralf Kähler,et al.  Single-pass GPU-raycasting for structured adaptive mesh refinement data , 2012, Electronic Imaging.

[19]  Hal Finkel,et al.  GRChombo: Numerical relativity with adaptive mesh refinement , 2015, 1503.03436.

[20]  John Shalf,et al.  Extraction of Crack-free Isosurfaces from Adaptive Mesh Refinement Data , 2001, VisSym.

[21]  Gunther H. Weber,et al.  Efficient parallel extraction of crack-free isosurfaces from adaptive mesh refinement (AMR) data , 2012, IEEE Symposium on Large Data Analysis and Visualization (LDAV).

[22]  G. Bryan,et al.  Introducing Enzo, an AMR Cosmology Application , 2004, astro-ph/0403044.

[23]  Kwan-Liu Ma,et al.  Parallel rendering of 3D AMR data on the SGI/Cray T3E , 1999, Proceedings. Frontiers '99. Seventh Symposium on the Frontiers of Massively Parallel Computation.

[24]  Markus Hadwiger,et al.  Smooth Mixed-Resolution GPU Volume Rendering , 2008, VG/PBG@SIGGRAPH.

[25]  M. Berger,et al.  Adaptive mesh refinement for hyperbolic partial differential equations , 1982 .

[26]  Richard Franke,et al.  Smooth interpolation of large sets of scattered data , 1980 .

[27]  Myoungkyu Lee,et al.  Petascale direct numerical simulation of turbulent channel flow on up to 786K cores , 2013, 2013 SC - International Conference for High Performance Computing, Networking, Storage and Analysis (SC).