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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...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Boca Raton :
CRC Press,
2012.
|
| Colección: | Chapman & Hall/CRC computational science series.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 245 | 0 | 0 | |a Combinatorial scientific computing / |c edited by Uwe Naumann, Olaf Schenk. |
| 260 | |a Boca Raton : |b CRC Press, |c 2012. | ||
| 300 | |a 1 online resource (xxiii, 549 pages, 8 unnumbered pages of plates) : |b illustrations (some color) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Chapman & Hall/CRC computational science series | |
| 504 | |a Includes bibliographical references. | ||
| 520 | |a "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 interconnecting network performance. Due to the advances being made in computational science and engineering, the applications that run on these machines involve complex multiscale or multiphase physics, adaptive meshes and/or sophisticated numerical methods. A key challenge for scientific computing is obtaining high performance for these advanced applications on such complicated computers and, thus, to enable scientific simulations on a scale heretofore impossible. A typical model in computational science is expressed using the language of continuous mathematics, such as partial differential equations and linear algebra, but techniques from discrete or combinatorial mathematics also play an important role in solving these models efficiently. Several discrete combinatorial problems and data structures, such as graph and hypergraph partitioning, supernodes and elimination trees, vertex and edge reordering, vertex and edge coloring, and bipartite graph matching, arise in these contexts. As an example, parallel partitioning tools can be used to ease the task of distributing the computational workload across the processors. The computation of such problems can be represented as a composition of graphs and multilevel graph problems that have to be mapped to different microprocessors"-- |c Provided by publisher. | ||
| 505 | 0 | 0 | |t Combinatorial scientific computing : past success, current opportunities, future challenges / |r Bruce Hendrickson, Alex Pothen -- |t Combinatorial problems in solving linear systems / |r Iain Duff, Bora Uc̜ar -- |t Combinatorial preconditioners / |r Sivan Toledo, Haim Avron -- |t A scalable hybrid linear solver based on combinatorial algorithms / |r Madan Sathe [and others] -- |t Combinatorial problems in algorithmic differentiation / |r Uwe Naumann, Andrea Walther -- |t Combinatorial problems in OpenAD / |r Jean Utke, Uwe Naumann -- |t Getting started with ADOL-C / |r Andrea Walther, Andreas Griewank -- |t Algorithmic differentiation and nonlinear optimization for an inverse medium problem / |r Johannes Huber [and others] -- |t Combinatorial aspects/algorithms in computational fluid dynamics / |r Rainald Löhner -- |t Unstructured mesh generation / |r Jonathan Richard Shewchuk -- |t 3D Delaunay mesh generation / |r Klaus Gärtner [and others] -- |t Two-dimensional approaches to sparse matrix partitioning / |r Rob H. Bisseling [and others] -- |t Parallel partitioning, coloring, and ordering in scientific computing / |r E.G. Boman [and others] -- |t Scotch and PT-scotch graph partitioning software : an overview / |r Franc̜ois Pellegrini -- |t Massively parallel graph partitioning : a case in human bone simulations / |r C. Bekas [and others] -- |t Algorithmic and statistical perspectives on large-scale data analysis / |r Michael W. Mahoney -- |t Computational challenges in emerging combinatorial scientific computing applications / |r David A. Bader, Kamesh Madduri --- |t Spectral graph theory / |r Daniel Spielman -- |t Algorithms for visualizing large networks / |r Yifan Hu. |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Computer programming. | |
| 650 | 0 | |a Science |x Data processing. | |
| 650 | 0 | |a Combinatorial analysis. | |
| 650 | 6 | |a Programmation (Informatique) | |
| 650 | 6 | |a Sciences |x Informatique. | |
| 650 | 6 | |a Analyse combinatoire. | |
| 650 | 7 | |a computer programming. |2 aat | |
| 650 | 7 | |a COMPUTERS |x Programming |x Algorithms. |2 bisacsh | |
| 650 | 7 | |a MATHEMATICS |x General. |2 bisacsh | |
| 650 | 7 | |a MATHEMATICS |x Combinatorics. |2 bisacsh | |
| 650 | 7 | |a Combinatorial analysis. |2 fast |0 (OCoLC)fst00868961 | |
| 650 | 7 | |a Computer programming. |2 fast |0 (OCoLC)fst00872390 | |
| 650 | 7 | |a Science |x Data processing. |2 fast |0 (OCoLC)fst01108207 | |
| 700 | 1 | |a Naumann, Uwe, |d 1969- | |
| 700 | 1 | |a Schenk, Olaf, |d 1967- | |
| 776 | 0 | 8 | |i Print version: |t Combinatorial scientific computing. |d Boca Raton : CRC Press, 2012 |w (DLC) 2011044663 |
| 830 | 0 | |a Chapman & Hall/CRC computational science series. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781439827369/?ar |z Texto completo (Requiere registro previo con correo institucional) |
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