Computational simulations frequently generate solutions defined over very large tetrahedral volume meshes containing millions of elements. Furthermore, solutions over these meshes may often be expressed using non-linear basis functions. Certain solution techniques may even produce non-conforming meshes. Such data is difficult to visualize interactively, as it is far too large to fit in memory and many common data reduction techniques cannot be applied to non-conforming meshes. Common linear interpolation method cannot faithfully and accurately evaluate the non-linear solutions. In this book, three different methods are proposed to provide accurate, interactive and efficient visualization. The surface method introduces pixel-exact evaluation of higher-order solution data on the GPU, which demonstrates the importance of per-pixel rendering versus linear interpolation for producing high quality visualizations. The interactive volume method adaptively samples points from non-linear solution, decimates points at run time to fit GPU memory limits, and renders them order-independently. The feature method improves efficiency by sampling over feature partitions via TetGrid.
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