List of Tables

• 4.1. The average computation time for a time integration step and the number of required time steps for the material-dependent etching process shown in Figure 4.12 using an AMD Opteron 8222 SE processor ( $\SI {3}{\giga \hertz }$ ).
• 4.2. The average computation times for a time integration step, the directional visibility test, and the normal vector calculation for the directional etching process shown in Figure 4.14.
• 4.3. The average computation time for a time integration step and the void detection algorithm. The number of vertices of the maximum reduced graph during the entire simulation is also given, and is very small compared to the number of defined grid points.
• 4.4. Benchmarks for a time integration step of a sphere expanding with constant speed. The computation times as well as the parallel efficiency are given for varying sphere diameters ${{d}}$ and number of used CPUs.
• 5.1. Comparison of different data structures for ray tracing. All tests were carried out on 16 cores of AMD Opteron 8435 processors ( $\SI {2.6}{\giga \hertz }$ ).
• 5.2. Parallel scalability of the example shown in Figure 5.5. The neighbor links arrays data structure using the SAH with ${\chi }=0.8$ was used for these benchmarks.
• 5.3. Runtimes for sampling 100 million direction vectors on an Intel Core 2 Duo E6600 processor running at $\SI {2.4}{\giga \hertz }$ .
• 6.1. The numeric values of the parameters used for the passivation cycle of the Bosch process.
• 6.2. The numeric values of the parameters used for the etching cycle of the Bosch process.