Abstract
Abstract A triangulation of points in E 2 , or a tetrahedronization of points in E 3 , is used in many applications. It is not necessary to fulfill the Delaunay criteria in all cases. For large data (more then 5 · 10 7 points),parallel methods are used for the purpose of decreasingrun–time. A new approach for fast, effective and highly parallel CPU and GPU triangulation, or tetrahedronization, of large data sets in E 2 or E 3 suitable for in–core and out–core memory processing, is proposed. Experimental results proved that the resulting triangulation/tetrahedralization is close to the Delaunay triangulation/tetrahedralization. It also demonstrates the applicability of the methodproposed in applications.
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