Parallel extraction and simplification of large isosurfaces using an extended tandem algorithm
In order to deal with the common trend in size increase of volumetric datasets, in the past few years research in isosurface extraction has focused on related aspects such as surface simplification and load-balanced parallel algorithms. We present a parallel, block-wise extension of the tandem algorithm [Attali D, Cohen-Steiner D, Edelsbrunner H. Extraction and simplification of iso-surfaces in tandem. In: SGP 05: Proceedings of the third Eurographics symposium on Geometry processing. Aire-la-Ville, Switzerland: Eurographics Association; 2005. p. 139148], which simplifies on the fly an isosurface being extracted. Our approach minimizes the overall memory consumption using an adequate block splitting and merging strategy along with the introduction of a component dumping mechanism that drastically reduces the amount of memory needed for particular datasets such as those encountered in geophysics. As soon as detected, surface components are migrated to the disk along with a meta-data index (oriented bounding box, volume, etc.) that permits further improved exploration scenarios (small component removal or particularly oriented component selection for instance). For ease of implementation, we carefully describe a master and worker algorithm architecture that clearly separates the four required basic tasks. We show several results of our parallel algorithm applied on a geophysical dataset of size 700016002000.
geometric computation distributed design and geo-scientific applications