Combinatorial Scientific Computing

Herausgeber: Naumann, Uwe; Schenk, Olaf

• Gebundenes Buch

Produktbeschreibung

This is the first book to provide an overview of combinatorial scientific computing (CSC). Bringing together a diverse group of researchers, it addresses many of the challenges faced in high-performance computing (HPC) by setting the stage for accelerated development and deployment of fundamental enabling technologies in HPC. The text focuses on load balancing and parallelization on high-performance computers, large-scale optimization, automatic differentiation of numerical simulation code, and sparse matrix software tools. It also discusses key topics in CSC, important software tools, and special topics and applications.

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Produktdetails

• Verlag: Taylor & Francis Ltd (Sales)
• Seitenzahl: 602
• Erscheinungstermin: 25. Januar 2012
• Englisch
• Abmessung: 236mm x 157mm x 33mm
• Gewicht: 957g
• ISBN-13: 9781439827352
• ISBN-10: 1439827354
• Artikelnr.: 32790011

Autorenporträt

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.