This volume explores the latest research on creating algorithms and software tools to solve key combinatorial problems on large-scale high-performance computing architectures. It focuses on load balancing and parallelization on high-performance computers, large-scale optimization, algorithmic differentiation of numerical simulation code, sparse matrix software tools, and combinatorial challenges and applications in large-scale social networks. The authors, who are pioneers in the field, unify these seemingly disparate areas through a common set of abstractions and algorithms based on combinatorics, graphs, and hypergraphs.…mehr
This volume explores the latest research on creating algorithms and software tools to solve key combinatorial problems on large-scale high-performance computing architectures. It focuses on load balancing and parallelization on high-performance computers, large-scale optimization, algorithmic differentiation of numerical simulation code, sparse matrix software tools, and combinatorial challenges and applications in large-scale social networks. The authors, who are pioneers in the field, unify these seemingly disparate areas through a common set of abstractions and algorithms based on combinatorics, graphs, and hypergraphs.
Uwe Naumann is an associate professor of computer science at RWTH Aachen University. Dr. Naumann has published more than 80 peer-reviewed papers and chaired several workshops. His research focuses on algorithmic differentiation, combinatorial graph algorithms, high-performance scientific computing, and the application of corresponding methods to real-world problems in computational science, engineering, and finance. Olaf Schenk is an associate professor of computer science at the University of Lugano. Dr. Schenk has published more than 70 peer-reviewed book chapters, journal articles, and conference contributions. In 2008, he received an IBM Faculty Award on Cell Processors for Biomedical Hyperthermia Applications. His research interests include algorithmic and architectural problems in computational mathematics, scientific computing, and high-performance computing.
Inhaltsangabe
Combinatorial Scientific Computing: Past Successes, Current Opportunities, Future Challenges. Combinatorial Problems in Solving Linear Systems. Combinatorial Preconditioners. Scalable Hybrid Linear Solvers. Combinatorial Problems in Algorithmic Differentiation. Combinatorial Problems in OpenAD. Getting Started with ADOL-C. Algorithmic Differentiation and Nonlinear Optimization for an Inverse Medium Problem. Combinatorial Aspects/Algorithms in Computational Fluid Dynamics. Unstructured Mesh Generation. 3D Delaunay Mesh Generation. Two-Dimensional Approaches to Sparse Matrix Partitioning. Parallel Partitioning, Ordering, and Coloring in Scientific Computing. Scotch and PT-Scotch Graph Partitioning Software: An Overview. Massively Parallel Graph Partitioning: A Case in Human Bone Simulations. Algorithmic and Statistical Perspectives on Large-Scale Data Analysis. Computational Challenges in Emerging Combinatorial Scientific Computing Applications. Spectral Graph Theory. Algorithms for Visualizing Large Networks.
Combinatorial Scientific Computing: Past Successes, Current Opportunities, Future Challenges. Combinatorial Problems in Solving Linear Systems. Combinatorial Preconditioners. Scalable Hybrid Linear Solvers. Combinatorial Problems in Algorithmic Differentiation. Combinatorial Problems in OpenAD. Getting Started with ADOL-C. Algorithmic Differentiation and Nonlinear Optimization for an Inverse Medium Problem. Combinatorial Aspects/Algorithms in Computational Fluid Dynamics. Unstructured Mesh Generation. 3D Delaunay Mesh Generation. Two-Dimensional Approaches to Sparse Matrix Partitioning. Parallel Partitioning, Ordering, and Coloring in Scientific Computing. Scotch and PT-Scotch Graph Partitioning Software: An Overview. Massively Parallel Graph Partitioning: A Case in Human Bone Simulations. Algorithmic and Statistical Perspectives on Large-Scale Data Analysis. Computational Challenges in Emerging Combinatorial Scientific Computing Applications. Spectral Graph Theory. Algorithms for Visualizing Large Networks.
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