Combinatorial Scientific Computing

Uwe Naumann, Olaf Schenk

Hardback
$75.16

January 25, 2012 by Chapman and Hall/CRC
Reference - 600 Pages - 15 Color & 128 B/W Illustrations
ISBN 9781439827352 - CAT# K11349
Series: Chapman & Hall/CRC Computational Science

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Features

  • Provides an overview of modern combinatorial graph algorithms in computational science
  • Covers a range of topics in scientific computing, including scalable algorithms, software, architectures, and application development
  • Focuses on discrete data structures in computational science, such as hypergraph partitioning, vertex and edge reordering and coloring, and bipartite graph matching
  • Presents applications of high-performance scientific computing in biomedicine, fluid dynamics, and social science

Summary

Combinatorial Scientific Computing explores the latest research on creating algorithms and software tools to solve key combinatorial problems on large-scale high-performance computing architectures. It includes contributions from international researchers who are pioneers in designing software and applications for high-performance computing systems.

The book offers a state-of-the-art overview of the latest research, tool development, and applications. 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 unify these seemingly disparate areas through a common set of abstractions and algorithms based on combinatorics, graphs, and hypergraphs.

Combinatorial algorithms have long played a crucial enabling role in scientific and engineering computations and their importance continues to grow with the demands of new applications and advanced architectures. By addressing current challenges in the field, this volume sets the stage for the accelerated development and deployment of fundamental enabling technologies in high-performance scientific computing.