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Graph Partitioning.
Graph partitioning is a theoretical subject with applications in many areas, principally: numerical analysis, programs mapping onto parallel architectures, image segmentation, VLSI design. During the last 40 years, the literature has strongly increased and big improvements have been made. This book...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Wiley,
2013.
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| Colección: | ISTE.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Bichot, Charles-Edmond. | |
| 245 | 1 | 0 | |a Graph Partitioning. |
| 260 | |a London : |b Wiley, |c 2013. | ||
| 300 | |a 1 online resource (386 pages) | ||
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| 505 | 0 | |a Cover; Graph Partitioning; Title Page; Copyright Page; Table of Contents; Introduction; Chapter 1. General Introduction to Graph Partitioning; 1.1. Partitioning; 1.2. Mathematical notions; 1.3. Graphs; 1.4. Formal description of the graph partitioning problem; 1.5. Objective functions for graph partitioning; 1.6. Constrained graph partitioning; 1.7. Unconstrained graph partitioning; 1.8. Differences between constrained and unconstrained partitioning; 1.9. From bisection to k-partitioning: he recursive bisection method. | |
| 505 | 8 | |a 1.9.1. Creating a partition with a number of parts a power of 2, from a graph bisection algorithm1.9.2. Creating a k-partition from a graph bisection algorithm using the partitioning balance; 1.10. NP-hardness of graph partitioning optimization problems; 1.10.1. The case of constrained graph partitioning; 1.10.2. The case of unconstrained graph partitioning; 1.11. Conclusion; 1.12. Bibliography; PART 1: GRAPH PARTITIONING FOR NUMERICAL ANALYSIS; Chapter 2. A Partitioning Requiring Rapidity and Quality: The Multilevel Method and Partitions Refinement Algorithms; 2.1. Introduction. | |
| 505 | 8 | |a 2.2. Principles of the multilevel method2.3. Graph coarsening; 2.3.1. Introduction; 2.3.2. Graph matching; 2.3.3. Hendrickson-Leland coarsening algorithm; 2.3.4. The Heavy Edge Matching (HEM) algorithm; 2.4. Partitioning of the coarsened graph; 2.4.1. State-of-the-art partitioning methods; 2.4.2. Region growing methods; 2.5. Uncoarsening and partitions refinement; 2.5.1. Presentation of the uncoarsening and refinement phase; 2.5.2. The Kernighan-Lin algorithm; 2.5.3. Fiduccia-Mattheyses implementation; 2.5.4. Adaptation to direct k-partitioning; 2.5.5. Global Kernighan-Lin Refinement. | |
| 505 | 8 | |a 2.5.6. The Walshaw-Cross refinement algorithm2.6. The spectral method; 2.6.1. Presentation; 2.6.2. Some results of numerical system; 2.6.3. Finding the eigenvalues of the Laplacian matrix of a graph; 2.6.4. Lower bound for constrained graph partitioning; 2.6.5. Spectral methods for contrained partitioning; 2.6.6. Spectral methods for unconstrained graph partitioning; 2.6.7. Problems and improvements; 2.7. Conclusion; 2.8. Bibliography; Chapter 3. Hypergraph Partitioning; 3.1. Definitions and metrics; 3.1.1. Hypergraph and partitioning; 3.1.2. Metrics for hypergraph partitioning. | |
| 505 | 8 | |a 3.2. Connections between graphs, hypergraphs, and matrices3.3. Algorithms for hypergraph partitioning; 3.3.1. Coarsening; 3.3.2. Initial partitioning and uncoarsening and refinement; 3.3.3. Uncoarsening and refinement; 3.4. Purpose; 3.4.1. Hypergraph partitioning benefits; 3.4.2. Matrix partitioning; 3.4.3. Practical results; 3.4.4. Repartitioning; 3.4.5. Use of hypergraphs within a mesh partitioning context; 3.4.6. Other applications; 3.5. Conclusion; 3.6. Software references; 3.7. Bibliography; Chapter 4. Parallelization of Graph Partitioning; 4.1. Introduction; 4.1.1. Need for parallelism. | |
| 500 | |a 4.1.2. Multilevel framework. | ||
| 520 | |a Graph partitioning is a theoretical subject with applications in many areas, principally: numerical analysis, programs mapping onto parallel architectures, image segmentation, VLSI design. During the last 40 years, the literature has strongly increased and big improvements have been made. This book brings together the knowledge accumulated during many years to extract both theoretical foundations of graph partitioning and its main applications. | ||
| 588 | 0 | |a Print version record. | |
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Partitions (Mathematics) | |
| 650 | 0 | |a Graph theory. | |
| 650 | 4 | |a Graph theory. | |
| 650 | 4 | |a Mathematics. | |
| 650 | 4 | |a Partitions (Mathematics) | |
| 650 | 6 | |a Partitions (Mathématiques) | |
| 650 | 7 | |a Graph theory |2 fast | |
| 650 | 7 | |a Partitions (Mathematics) |2 fast | |
| 700 | 1 | |a Siarry, Patrick. | |
| 758 | |i has work: |a Graph partitioning (Text) |1 https://id.oclc.org/worldcat/entity/E39PCXhQGthKFRC9h9BVH7wRVd |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Bichot, Charles-Edmond. |t Graph Partitioning. |d London : Wiley, ©2013 |z 9781848212336 |
| 830 | 0 | |a ISTE. | |
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