Parallel Cell Projection Rendering of Adaptive Mesh Refinement Data

Authors:
Gunther H. Weber;Martin Ohler;Oliver Kreylos;John M. Shalf;E. Wes Bethel;Bernd Hamann;Gerik Scheuermann
Affiliations:
University of California, Davis/ University of Kaiserslautern, Germany/ Lawrence Berkeley National Laboratory;University of Kaiserslautern, Germany;University of California, Davis/ Lawrence Berkeley National Laboratory;Lawrence Berkeley National Laboratory;Lawrence Berkeley National Laboratory;University of California, Davis/ Lawrence Berkeley National Laboratory;University of Kaiserslautern, Germany
Venue:
PVG '03 Proceedings of the 2003 IEEE Symposium on Parallel and Large-Data Visualization and Graphics
Year:
2003

Citing 21
Cited 1

Display of Surfaces from Volume Data

IEEE Computer Graphics and Applications
Local adaptive mesh refinement for shock hydrodynamics

Journal of Computational Physics
Hierarchical splatting: a progressive refinement algorithm for volume rendering

Proceedings of the 18th annual conference on Computer graphics and interactive techniques
An introduction to parallel rendering

Parallel Computing - Special issue on applications: parallel graphics and visualisation
A scalable parallel cell-projection volume rendering algorithm for three-dimensional unstructured data

PRS '97 Proceedings of the IEEE symposium on Parallel rendering
Fluids in the universe: adaptive mesh refinement in cosmology

Computing in Science and Engineering
Multidimensional binary search trees used for associative searching

Communications of the ACM
A rendering algorithm for visualizing 3D scalar fields

SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Case study: interactive rendering of adaptive mesh refinement data

Proceedings of the conference on Visualization '02
Rendering the first star in the universe: a case study

Proceedings of the conference on Visualization '02
Optical Models for Direct Volume Rendering

IEEE Transactions on Visualization and Computer Graphics
Diving Deep: Data-Management and Visualization Strategies for Adaptive Mesh Refinement Simulations

Computing in Science and Engineering
Parallel Volume Rendering Using Binary-Swap Compositing

IEEE Computer Graphics and Applications
Fast Polygon Scan Conversion with Medical Applications

IEEE Computer Graphics and Applications
High-quality Volume Rendering of Adaptive Mesh Refinement Data

VMV '01 Proceedings of the Vision Modeling and Visualization Conference 2001
Sorting for Polyhedron Compositing

Focus on Scientific Visualization
Parallel Rendering of 3D AMR Data on the SGI/Cray T3E

FRONTIERS '99 Proceedings of the The 7th Symposium on the Frontiers of Massively Parallel Computation
Compositing digital images

SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Hierarchical and Geometrical Methods in Scientific Visualization

Hierarchical and Geometrical Methods in Scientific Visualization
Interactive volume rendering of large sparse data sets using adaptive mesh refinement hierarchies

IEEE Transactions on Visualization and Computer Graphics
Extraction of crack-free isosurfaces from adaptive mesh refinement data

EGVISSYM'01 Proceedings of the 3rd Joint Eurographics - IEEE TCVG conference on Visualization

Survey of parallel and distributed volume rendering: revisited

ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part III

Quantified Score

Hi-index	0.00

Visualization

Abstract

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 visualization is still a relatively unexplored topic, our work is motivated by the need to perform efficient visualization of large AMR data sets. We present a software algorithm for parallel direct volume rendering of AMR data using a cell-projection technique on several different parallel platforms. Our algorithm can use one of several different distribution methods, and we present performance results for each of these alternative approaches. By partitioning an AMR data set into blocks of constant resolution and estimating rendering costs of individual blocks using an application specific benchmark, it is possible to achieve even load balancing.