Combinatorial scientific computing

"Foreword the ongoing era of high-performance computing is filled with enormous potential for scientific simulation, but also with daunting challenges. Architectures for high-performance computing may have thousands of processors and complex memory hierarchies paired with a relatively poor inte...

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Bibliographic Details
Other Authors: Naumann, Uwe, 1969-, Schenk, Olaf, 1967-
Format: Electronic
Language:English
Published: Boca Raton, Fla. : CRC Press, c2012.
Series:Chapman & Hall/CRC computational science series ; 12.
Subjects:
Online Access:Distributed by publisher. Purchase or institutional license may be required for access.
Table of Contents:
  • 1. Combinatorial scientific computing : past successes, current opportunities, future challenges / Bruce Hendrickson and Alex Pothen
  • 2. Combinatorial problems in solving linear systems / Iain Duff and Bora Uȧr
  • 3. Combinatorial preconditioners / Sivan Toledo and Haim Avron
  • 4. A scalable hybrid linear solver based on combinatorial algorithms / Madan Sathe ... [et al.]
  • 5. Combinatorial problems in algorithmic differentiation / Uwe Naumann and Andrea Walther
  • 6. Combinatorial problems in OpenAD / Jean Utke and Uwe Naumann
  • 7. Getting started with ADOL-C / Andrea Walther and Andreas Griewank
  • 8. Algorithmic differentiation and nonlinear optimization for an inverse medium problem / Johannes Huber ... [et al.]
  • 9. Combinatorial aspects/algorithms in computational fluid dynamics / Rainald Lh̲ner
  • 10. Unstructured mesh generation / Jonathan Richard Shewchuk
  • 11. 3D Delaunay mesh generation / Klaus Gr̃tner ... [et al.]
  • 12. Two-dimensional approaches to sparse matrix partitioning / Rob H. Bisseling ... [et al.]
  • 13. Parallel partitioning, coloring, and ordering in scientific computing / E.G. Boman ... [et al.]
  • 14. Scotch and PT-Scotch graph partitioning software : an overview / Franȯis Pellegrini
  • 15. Massively parallel graph partitioning : a case in human bone simulations / C. Bekas ... [et al.]
  • 16. Algorithmic and statistical perspectives on large-scale data analysis / Michael W. Mahoney
  • 17. Computational challenges in emerging combinatorial scientific computing applications / David A. Bader and Kamesh Madduri
  • 18. Spectral graph theory / Daniel Spielman
  • 19. Algorithms for visualizing large networks / Yifan Hu.