An adaptive framework for visualizing unstructured grids with time-varying scalar fields

Interactive visualization of time-varying volume data is essential for many scientific simulations. This is a challenging problem since this data is often large, can be organized in different formats (regular or irregular grids), with variable instances of time (from hundreds to thousands) and variable domain fields. It is common to consider subsets of this problem, such as time-varying scalar fields (TVSFs) on static structured grids, which are suitable for compression using multi-resolution techniques and can be efficiently rendered using texture-mapping hardware. In this work we propose a rendering system that considers unstructured grids, which do not have the same regular properties crucial to compression and rendering. Our solution simultaneously leverages multiple processors and the graphics processing unit (GPU) to perform decompression, level-of-detail selection, and volume visualization of dynamic data. The resulting framework is general enough to adaptively handle visualization tasks such as direct volume rendering and isosurfacing while allowing the user to control the speed and quality of the animation.