SC17 Denver, CO

Lean Visualization of Large Scale Tree-Based AMR Meshes

Workshop: The 2nd International Workshop on Data Reduction for Big Scientific Data (DRBSD-2)
Authors: Philippe P. Pébaÿ (NexGen Analytics)

Abstract: We present a novel adaptive method for the visualization and analysis of large-scale, parallel, tree-based adaptive mesh refinement (AMR) scientific simulations. When compared to those obtained with standard approaches for the visualization of such datasets, our results indicate a gain of at least 80% in terms of memory footprint with a better rendering, while retaining similar execution speed.

Furthermore, our adaptive approach allows for further acceleration of the rendering of 2-dimensional AMR grids, hereby solving the problem posed by the loss of interactivity that occurs when dealing with large and/or deeply refined meshes. This was achieved by taking advantage of the intrinsic structure of tree-based AMR grids, allowing for on-the-fly data reduction at visualization time with guaranteed rendering accuracy.

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