Local adaptive mesh refinement for shock hydrodynamics
Journal of Computational Physics
Fluids in the universe: adaptive mesh refinement in cosmology
Computing in Science and Engineering
ASAP '96 Proceedings of the IEEE International Conference on Application-Specific Systems, Architectures, and Processors
Markov model prediction of I/O requests for scientific applications
ICS '02 Proceedings of the 16th international conference on Supercomputing
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
Deploying Web-Based Visual Exploration Tools on the Grid
IEEE Computer Graphics and Applications
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
The Feature Tree: Visualizing Feature Tracking in Distributed AMR Datasets
PVG '03 Proceedings of the 2003 IEEE Symposium on Parallel and Large-Data Visualization and Graphics
Evaluating I/O characteristics and methods for storing structured scientific data
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Extraction of crack-free isosurfaces from adaptive mesh refinement data
EGVISSYM'01 Proceedings of the 3rd Joint Eurographics - IEEE TCVG conference on Visualization
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Adaptive mesh refinement, developed by Marsha Berger and colleagues in the 1980s for gas dynamical simulations, is a type of multiscale algorithm that achieves high spatial resolution in localized regions of dynamic, multidimensional numerical simulations. Greg Bryan's excellent article in the March/April 1999 issue of Computing in Science & Engineering describes our cosmological AMR algorithm and how we have applied it to star, galaxy, and galaxy cluster formation. Basically, the algorithm allows us to place very high resolution grids precisely where we need them-where stars and galaxies condense out of diffuse gas. In our applications, AMR allows us to achieve a local mesh refinement relative to the global coarse grid of more than a factor of 106. Such resolution would be totally impossible to achieve with a global, uniform fine grid. Thus, AMR allows us to simulate multiscale phenomena that are out of reach with fixed grid methods.The AMR algorithm accomplishes this by producing a deep, dynamic hierarchy of increasingly refined grid patches. The data structures for storing AMR data are complex, hierarchical, dynamic, and in general quite large. Existing visualization, animation, and data-management tools developed for simple mesh data structures cannot handle AMR data sets. Consequently, in the past several years we have been working at the National Center for Supercomputing Applications to overcome this deficit. Here we describe our progress in four main areas: portable file formats, desktop visualization tools, virtual-reality navigation and animation techniques, and Web-based workbenches for handling and exploring AMR data. Although we have applied our work specifically to cosmology, we believe our solutions have broader applicability.