Interactive Image-Space Volume Visualization for Dynamic Particle Simulations

Particle-based simulation plays an important role in many different fields of science and engineering. Two common visualization approaches for the resulting data are glyph-based rendering and density sampling employing volume rendering. Fine geometric features are inherently captured by glyph-based methods. However, they might suffer from aliasing and the global structure is often poorly conveyed. Volume rendering preserves the global structure but is limited due to the sampling resolution. To avoid aliasing artifacts and large memory footprints, we propose a direct volume rendering technique with on-demand density sampling of the particle data, as combination of splatting, texture slicing, and ray casting. We optimized our system with a novel ray cast termination employing early-z-test culling and hardware occlusion queries utilizing inter-frame coherency. Our system contains a fully-featured volume renderer and captures all geometric features of the data set representable at the available display resolution. Since no pre-computation is required, the proposed method can be used easily to visualize time-dependent data sets. The effectiveness of our approach is shown with examples from different application fields.

[1]  Thomas Ertl,et al.  Optimized data transfer for time-dependent, GPU-based glyphs , 2009, 2009 IEEE Pacific Visualization Symposium.

[2]  Thomas Ertl,et al.  Interactive Visualization of Molecular Surface Dynamics , 2009, IEEE Transactions on Visualization and Computer Graphics.

[3]  Simon Stegmaier,et al.  A simple and flexible volume rendering framework for graphics-hardware-based raycasting , 2005, Fourth International Workshop on Volume Graphics, 2005..

[4]  Thomas Ertl,et al.  Image-Space GPU Metaballs for Time-Dependent Particle Data Sets , 2007, VMV.

[5]  Tomoyuki Nishita,et al.  GPU‐based Fast Ray Casting for a Large Number of Metaballs , 2008, Comput. Graph. Forum.

[6]  Rüdiger Westermann,et al.  Acceleration techniques for GPU-based volume rendering , 2003, IEEE Visualization, 2003. VIS 2003..

[7]  M. Karplus,et al.  Dynamics of folded proteins , 1977, Nature.

[8]  TariniMarco,et al.  Ambient Occlusion and Edge Cueing for Enhancing Real Time Molecular Visualization , 2006 .

[9]  Thomas Ertl,et al.  Illustrating Magnetic Field Lines using a Discrete Particle Model , 2004, VMV.

[10]  Martin Falk,et al.  Visualization of signal transduction processes in the crowded environment of the cell , 2009, 2009 IEEE Pacific Visualization Symposium.

[11]  Rüdiger Westermann,et al.  Efficiently using graphics hardware in volume rendering applications , 1998, SIGGRAPH.

[12]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[13]  Insung Ihm,et al.  GPU‐Assisted High Quality Particle Rendering , 2009, Comput. Graph. Forum.

[14]  A. Arnold,et al.  Harvesting graphics power for MD simulations , 2007, 0709.3225.

[15]  Thomas Ertl,et al.  Eurographics/ Ieee-vgtc Symposium on Visualization 2010 Coherent Culling and Shading for Large Molecular Dynamics Visualization , 2022 .

[16]  Rüdiger Westermann,et al.  UberFlow: a GPU-based particle engine , 2004, SIGGRAPH '04.

[17]  James F. Blinn,et al.  A Generalization of Algebraic Surface Drawing , 1982, TOGS.

[18]  Lee Westover,et al.  Footprint evaluation for volume rendering , 1990, SIGGRAPH.

[19]  Jens Schneider,et al.  Exploring the Millennium Run - Scalable Rendering of Large-Scale Cosmological Datasets , 2009, IEEE Transactions on Visualization and Computer Graphics.

[20]  J. Monaghan,et al.  Smoothed particle hydrodynamics: Theory and application to non-spherical stars , 1977 .

[21]  Matthieu Chavent,et al.  MetaMol: high-quality visualization of molecular skin surface. , 2008, Journal of molecular graphics & modelling.

[22]  Daniel Baum,et al.  Visualizing dynamic molecular conformations , 2002, IEEE Visualization, 2002. VIS 2002..

[23]  Lars Linsen,et al.  Surface Extraction from Multi-field Particle Volume Data Using Multi-dimensional Cluster Visualization , 2008, IEEE Transactions on Visualization and Computer Graphics.

[24]  Klaus Mueller,et al.  GPU accelerated image aligned splatting , 2005, Fourth International Workshop on Volume Graphics, 2005..

[25]  Renato Pajarola,et al.  Adaptive Sampling and Rendering of Fluids on the GPU , 2008, VG/PBG@SIGGRAPH.

[26]  Nicolas Cuntz,et al.  Dynamic particle coupling for gpu-based fluid simulation , 2010 .

[27]  Thomas Ertl,et al.  GPU-based Visualisation of Protein Secondary Structure , 2008, TPCG.

[28]  Pat Hanrahan,et al.  Volume Rendering , 2020, Definitions.

[29]  Stefan Gumhold,et al.  Splatting Illuminated Ellipsoids with Depth Correction , 2003, VMV.

[30]  Gino van den Bergen,et al.  Point-Based Visualization of Metaballs on a GPU , 2007 .

[31]  William E. Lorensen,et al.  Marching cubes: a high resolution 3D surface construction algorithm , 1996 .

[32]  Andreas Kolb,et al.  Hardware-based simulation and collision detection for large particle systems , 2004, Graphics Hardware.

[33]  Matthias Reuss,et al.  Stochastic simulation of signal transduction: impact of the cellular architecture on diffusion. , 2009, Biophysical journal.

[34]  Thomas Ertl,et al.  Hardware-Accelerated Glyphs for Mono- and Dipoles in Molecular Dynamics Visualization , 2005, EuroVis.