“In-Core and Out-Core Memory Fast Parallel Triangulation Algorithm for Large Data Sets in E² and E³” by Smolik and Skala
Conference:
Type(s):
Entry Number: 57
Title:
- In-Core and Out-Core Memory Fast Parallel Triangulation Algorithm for Large Data Sets in E² and E³
Presenter(s)/Author(s):
Abstract:
Today’s applications need to process large data sets using several processors with a shared memory, i.e. in parallel processing, or/and on systems using distributed processing. In this paper we describe an approach applicable for effective triangulation in E² and E³ (tetrahedralization) for large data sets using CPU and/or GPU parallel or distributed systems, e.g. computational clusters.
In many cases we do not need exact Delaunay triangulation [Chen 2011] or another specific triangulation. Triangulation as “close enough” to the required type of triangulation is acceptable. Weakening this strict requirement enables us to formulate a simple “Divide & Conquer” algorithm [Cignoni et al. 1998]. The approach is independent from the triangulation property requirements.
References:
- Chen, M.-B. 2011. A Parallel 3D Delaunay Triangulation Method, 9th ISPA 2011, IEEE, pp. 52–56.
- Cignoni, P., Montani, C., and Scopigno, R. 1998. DeWall: A Fast Divide & Conquer Delaunay Triangulation Algorithm in Ed, Computer Aided Design, Vol. 30, No. 5, pp. 333–341.
- Schaller, G., and Meyer-Hermann, M. 2004. Kinetic and Dynamic Delaunay Tetrahedralization in Three Dimensions, Computer Physics Communications, Vol. 162, No. 1, pp. 9–23.
