abstract

CPU volume rendering of adaptive mesh refinement data

Authors:

Carson Brownlee,

Aaron KnollAuthors Info & Claims

SA '17: SIGGRAPH Asia 2017 Symposium on Visualization

Article No.: 9, Pages 1 - 8

https://doi.org/10.1145/3139295.3139305

Published: 27 November 2017 Publication History

Abstract

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.

References

[1]

Marsha J Berger and Phillip Colella. Local adaptive mesh refinement for shock hydro-dynamics. Journal of computational Physics 82, 1 (1989), 64--84.

Digital Library

[2]

Marsha J Berger and Joseph Oliger. Adaptive mesh refinement for hyperbolic partial differential equations. Journal of computational Physics 53, 3 (1984).

[3]

Johanna Beyer, Markus Hadwiger, Torsten Möller, and Laura Fritz. 2008. Smooth mixed-resolution GPU volume rendering. In Proceedings of the Fifth Eurographics/IEEE VGTC conference on Point-Based Graphics. 163--170.

Digital Library

[4]

Katy Clough, Pau Figueras, Hal Finkel, Markus Kunesch, Eugene A. Lim, and Saran Tunyasuvunakool. Numerical Relativity with Adaptive Mesh Refinement. Classical and Quantum Gravity 32, 24 (2015).

[5]

P Colella, DT Graves, TJ Ligocki, DF Martin, D Modiano, DB Serafini, and B Van Straalen. 2000. Chombo software package for AMR applications-design document. (2000).

[6]

Richard Franke and Greg Nielson. Smooth interpolation of large sets of scattered data. Numerical Methods in Engineering 15 (1980). Issue 11.

[7]

Luke J Gosink, John C Anderson, E Wes Bethel, and Kenneth I Joy. Query-driven visualization of time-varying adaptive mesh refinement data. IEEE transactions on visualization and computer graphics 14, 6 (2008), 1715--1722.

Digital Library

[8]

Ralf Kähler and Tom Abel. 2013. Single-pass GPU-raycasting for structured adaptive mesh refinement data. In IS&T/SPIE Electronic Imaging. 865408--865408.

[9]

Ralf Kähler and Hans-Christian Hege. Texture-based volume rendering of adaptive mesh refinement data. The Visual Computer 18, 8 (2002), 481--492.

[10]

Ralf Kähler, John Wise, Tom Abel, and Hans-Christian Hege. 2006. GPU-assisted raycasting for cosmological adaptive mesh refinement simulations. In Volume Graphics. 103--110.

[11]

Cetin C Kiris, Michael F Barad, Jeffrey A Housman, Emre Sozer, Christoph Brehm, and Shayan Moini-Yekta. The LAVA Computational Fluid Dynamics Solver. 52nd Aerospace Sciences Meeting, AIAA SciTech Forum 70 (2014).

[12]

Nick Leaf, Venkatram Vishwanath, Joseph Insley, Mark Hereld, Michael E Papka, and Kwan-Liu Ma. 2013. Efficient parallel volume rendering of large-scale adaptive mesh refinement data. In 2013 IEEE Symposium on Large-Scale Data Analysis and Visualization. 35--42.

[13]

Myoungkyu Lee, Nicholas Malaya, and Robert D. Moser. 2013. Petascale Direct Numerical Simulation of Turbulent Channel Flow on Up to 786K Cores. In Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis. Article 61.

Digital Library

[14]

Patric Ljung, Claes Lundström, and Anders Ynnerman. Multiresolution interblock interpolation in direct volume rendering. (2006), 259--266.

Digital Library

[15]

Kwan-Liu Ma. 1999. Parallel rendering of 3D AMR data on the SGI/Cray T3E. In The 7th Symposium on the Frontiers of Massively Parallel Computation. 138--145.

Digital Library

[16]

Kwan-Liu Ma and Thomas W Crockett. 1997. A scalable parallel cell-projection volume rendering algorithm for three-dimensional unstructured data. In Proceedings of the IEEE symposium on Parallel rendering.

Digital Library

[17]

Stéphane Marchesin and Guillaume Colin De Verdiere. High-quality, semi-analytical volume rendering for AMR data. IEEE Transactions on Visualization and Computer Graphics 15, 6 (2009).

Digital Library

[18]

Nelson Max. 1993. Sorting for polyhedron composition. In Focus on Scientific Visualization. 259--268.

Digital Library

[19]

Patrick Moran and David Ellsworth. Visualization of AMR data with multi-level dual-mesh interpolation. IEEE transactions on visualization and computer graphics 17, 12 (2011), 1862--1871.

Digital Library

[20]

Brian W O'shea, Greg Bryan, James Bordner, Michael L Norman, Tom Abel, Robert Harkness, and Alexei Kritsuk. 2005. Introducing Enzo, an AMR cosmology application. In Adaptive mesh refinement-theory and applications.

[21]

Sanghun Park, Chandrajit L. Bajaj, and Vinay Siddavanahalli. 2002. Case Study: Interactive Rendering of Adaptive Mesh Refinement Data. In Proceedings of the Conference on Visualization '02 (VIS '02). IEEE Computer Society, Washington, DC, USA, 521--524. http://dl.acm.org/citation.cfm?id=602099.602186

Digital Library

[22]

David Trebotich and Daniel Graves. An adaptive finite volume method for the incompressible Navier-Stokes equations in complex geometries. Communications in Applied Mathematics and Computational Science 10, 1 (2015), 43--82.

[23]

Ingo Wald, Heiko Friedrich, Gerd Marmitt, Philipp Slusallek, and Hans-Peter Seidel. Faster Isosurface Ray Tracing using Implicit KD-Trees. IEEE Transactions on Visualization and Computer Graphics 11, 5 (2005).

Digital Library

[24]

I Wald, GP Johnson, J Amstutz, C Brownlee, A Knoll, J Jeffers, J Günther, and P Navratil. OSPRay-A CPU Ray Tracing Framework for Scientific Visualization. IEEE Transactions on Visualization and Computer Graphics 23, 1 (2017).

Digital Library

[25]

Ingo Wald, Philipp Slusallek, Carsten Benthin, and Markus Wagner. Interactive Rendering with Coherent Ray Tracing. Computer Graphics Forum 20, 3 (2001), 153--164. (Proceedings of Eurographics 2001).

Digital Library

[26]

Gunther H Weber, Hank Childs, and Jeremy S Meredith. 2012. Efficient parallel extraction of crack-free isosurfaces from adaptive mesh refinement (AMR) data. In 2012 IEEE Symposium on Large Data Analysis and Visualization.

[27]

Gunther H Weber, Oliver Kreylos, Terry J Ligocki, John M Shalf, Hans Hagen, Bernd Hamann, and Kenneth I Joy. 2003. Extraction of crack-free isosurfaces from adaptive mesh refinement data. In Hierarchical and Geometrical Methods in Scientific Visualization.

Cited By

Zellmann SWu QSahistan AMa KWald I(2024)Beyond ExaBricks: GPU Volume Path Tracing of AMR DataComputer Graphics Forum10.1111/cgf.1509543:3Online publication date: 10-Jun-2024
https://doi.org/10.1111/cgf.15095
Zellmann SWu QMa KWald I(2023)Memory‐Efficient GPU Volume Path Tracing of AMR Data Using the Dual MeshComputer Graphics Forum10.1111/cgf.1481142:3(51-62)Online publication date: 27-Jun-2023
https://doi.org/10.1111/cgf.14811
Wurster SGuo HShen HPeterka TXu J(2023)Deep Hierarchical Super Resolution for Scientific DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.321442029:12(5483-5495)Online publication date: Dec-2023
https://doi.org/10.1109/TVCG.2022.3214420
Show More Cited By

Index Terms

CPU volume rendering of adaptive mesh refinement data
1. Computing methodologies
  1. Computer graphics
    1. Rendering
      1. Ray tracing
2. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Scientific visualization

Recommendations

Comparison of refinement criteria for structured adaptive mesh refinement

We have investigated and analyzed the grid convergence issues for an adaptive mesh refinement (AMR) code. We have found that the numerical results for the AMR grid may have a larger error than those for the unrefined uniform grid. After a detailed ...
Adaptive mesh refinement for conformal hexahedralmeshes

In a numerical simulation using the finite element method, the mesh has to be fine enough to guarantee the accuracy of the solution. However, a uniformly fine mesh will usually imply a more expensive computation. Mesh adaptation offers an effective ...
Parallel Cell Projection Rendering of Adaptive Mesh Refinement Data
PVG '03: Proceedings of the 2003 IEEE Symposium on Parallel and Large-Data Visualization and Graphics

Adaptive Mesh Refinement (AMR) is a technique used in numerical simulations to automatically refine (or de-refine) certain regions of the physical domain in a finite difference calculation. AMR data consists of nested hierarchies of data grids. As AMR ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SA '17: SIGGRAPH Asia 2017 Symposium on Visualization

November 2017

154 pages

ISBN:9781450354110

DOI:10.1145/3139295

Conference Chairs:
Koji Koyamada
Kyoto University, Japan
,
Puripant Ruchikachorn
Chulalongkorn University, Thailand

Copyright © 2017 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 November 2017

Check for updates

Author Tags

Qualifiers

Abstract

Conference

SA '17

Sponsor:

SIGGRAPH

SA '17: SIGGRAPH Asia 2017

November 27 - 30, 2017

Bangkok, Thailand

Acceptance Rates

Overall Acceptance Rate 178 of 869 submissions, 20%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

11
Total Citations
View Citations
201
Total Downloads

Downloads (Last 12 months)15
Downloads (Last 6 weeks)2

Reflects downloads up to 09 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Zellmann SWu QSahistan AMa KWald I(2024)Beyond ExaBricks: GPU Volume Path Tracing of AMR DataComputer Graphics Forum10.1111/cgf.1509543:3Online publication date: 10-Jun-2024
https://doi.org/10.1111/cgf.15095
Zellmann SWu QMa KWald I(2023)Memory‐Efficient GPU Volume Path Tracing of AMR Data Using the Dual MeshComputer Graphics Forum10.1111/cgf.1481142:3(51-62)Online publication date: 27-Jun-2023
https://doi.org/10.1111/cgf.14811
Wurster SGuo HShen HPeterka TXu J(2023)Deep Hierarchical Super Resolution for Scientific DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.321442029:12(5483-5495)Online publication date: Dec-2023
https://doi.org/10.1109/TVCG.2022.3214420
Vezolainen AErlebacher GVasilyev OYuen D(2022)Volumetric Rendering on Wavelet-Based Adaptive GridFluids10.3390/fluids70702457:7(245)Online publication date: 16-Jul-2022
https://doi.org/10.3390/fluids7070245
Zellmann SSeifried DMorrical NWald IUsher WLaw-Smith JWalch-Gassner SHinkenjann A(2022)Point Containment Queries on Ray-Tracing Cores for AMR Flow VisualizationComputing in Science & Engineering10.1109/MCSE.2022.315367724:2(40-51)Online publication date: 1-Mar-2022
https://doi.org/10.1109/MCSE.2022.3153677
Usher WAmstutz JGünther JKnoll AJohnson GBrownlee CHota ACherniak BRowley TJeffers JPascucci V(2022)Scalable CPU Ray Tracing for In Situ Visualization Using OSPRayIn Situ Visualization for Computational Science10.1007/978-3-030-81627-8_16(353-374)Online publication date: 5-May-2022
https://doi.org/10.1007/978-3-030-81627-8_16
Wald IZellmann SUsher WMorrical NLang UPascucci V(2021)Ray Tracing Structured AMR Data Using ExaBricksIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.303047027:2(625-634)Online publication date: Feb-2021
https://doi.org/10.1109/TVCG.2020.3030470
Wang FMarshak NUsher WBurstedde CKnoll AHeister TJohnson C(2020)CPU Ray Tracing of Tree‐Based Adaptive Mesh Refinement DataComputer Graphics Forum10.1111/cgf.1395839:3(1-12)Online publication date: 18-Jul-2020
https://doi.org/10.1111/cgf.13958
Wang CZhang CLiu TLiao W(2020)Cube-Tet transformation method accelerating the process of topology optimizationEngineering Optimization10.1080/0305215X.2020.183944553:11(1980-1998)Online publication date: 18-Nov-2020
https://doi.org/10.1080/0305215X.2020.1839445
Usher WWald IAmstutz JGünther JBrownlee CPascucci V(2019)Scalable Ray Tracing Using the Distributed FrameBufferComputer Graphics Forum10.1111/cgf.1370238:3(455-466)Online publication date: 10-Jul-2019
https://doi.org/10.1111/cgf.13702
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents