Contents
Home
Abstract
Kurzfassung
Acknowledgement
List of Figures
List of Tables
List of Abbreviations
1 Introduction and Motivation
1.1 Research Goals
1.2 Research Setting
1.3 Thesis Outline
2 Theory and Background
2.1 Graphs
2.1.1 Graph Coloring
2.1.2 Solving the Graph Coloring Problem
2.1.3 Solution Quality
2.2 Meshes
2.2.1 Mesh Quality
2.2.2 Mesh Adaptation
2.2.2.1 Refinement
2.2.2.2 Swapping
2.2.2.3 Coarsening
2.2.2.4 Smoothing
2.3 Parallel Computers
2.3.1 Basic Computer Architecture
2.3.1.1 Multi-Core Processor
2.3.1.2 Multi-Threaded Processor
2.3.2 Parallel Programming
2.3.2.1 Shared-Memory Systems
2.3.2.2 Distributed-Memory Systems
2.3.2.3 Hybrid Systems
2.3.2.4 Accelerators
2.3.2.5 Basics of Parallelization
2.4 Benchmarking Platforms
3 Approximative Shared-Memory Graph Coloring Algorithms
3.1 Related Work
3.1.1 Exact Algorithms
3.1.2 Approximative Algorithms
3.1.3 Shared-Memory Parallel Algorithms
3.2 Evaluation
3.2.1 Benchmark Platforms and Setup
3.2.2 Test Graphs
3.2.3 Coloring Quality
3.2.4 Performance Analysis
3.3 Summary and Conclusion
4 Coarse-Grained Shared-Memory Parallel Mesh Adaptation
4.1 Related Work
4.1.1 Distributed-Memory Methods
4.1.2 Shared-Memory Parallel Methods
4.1.3 Hybrid Methods
4.2 Software Tools
4.3 Coarse-Grained Parallel Mesh Adaptation Framework
4.3.1 Partitioning and Coloring
4.3.2 Mesh Adaptation and Mesh Healing
4.4 Evaluation
4.4.1 Test Geometries and Benchmark Setup
4.4.2 Partition Coloring
4.4.3 Strong Scalability
4.4.4 Mesh Quality
4.5 Summary and Conclusion
5 Material Interface-Aware Surface Mesh Partitioning for Process TCAD
5.1 Related Work
5.2 Dual-Damascene Process
5.3 Multi-Material Representation
5.4 Multi-Material Interface-Aware Iterative Partitioning
5.5 Evaluation
5.5.1 Simulation Setup
5.5.2 Performance and Accuracy
5.5.3 Variation of Thresholds
5.5.4 Strong Scalability
5.6 Summary and Conclusion
6 Summary and Outlook
Bibliography
Curriculum Vitae
Own Publications
2.1 Hardware overview of the two different benchmarking platforms
3.1 Overview of the evaluated coloring algorithms
3.2 Graph probability parameters used with PaRMAT
3.3 Properties of the test graphs
3.4 Resulting number of colors for the test graphs using different algorithms
3.5 Resulting RSDs for the test graphs
3.6 Runtimes of the different algorithms on the set of test graphs
5.1 Colors and normalized weighting factors used in the etching simulation
5.2 The investigated level-set resolutions
5.3 Total simulation runtimes in minutes for different level-set resolutions
5.4 Distribution of computed surface deviations