'Adjacency lists' diaporamas de présentation

The ASC Language

The ASC Language. Part 2 of Associative Computing. Contents. References The MST example and background Variables and Data Types Operator Notation Input and Output Mask Control Statements Loop Control Statements Accessing Values in Parallel Variables Performance Monitor

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233-234

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External Memory Graph Algorithms and Applications to GIS

External Memory Graph Algorithms and Applications to GIS. Laura Toma Duke University July 14 2003. Massive Data. Massive datasets are being collected everywhere Storage management software is billion-$ industry. Examples : Geography: NASA satellites generate 1.2TB per day

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233-234

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Algorithm Design and Analysis (ADA)

Algorithm Design and Analysis (ADA). 242-535 , Semester 1 2013-2014. Objective introduce the main kinds of graphs, discuss two implementation approaches, and remind you about trees. 8 . Introduction to Graphs. Overview. Graphs Graph Terminology Implementing Graphs adjency matrix

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Online Topological Ordering

Online Topological Ordering. Siddhartha Sen , COS 518 11/20/2007. Outline. Problem statement and motivation Prior work (summary) Result by Ajwani et al. Algorithm Correctness Running time Implementation Comparison to prior work Incremental complexity analysis Practical implications

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Introduction to Data Structure

Introduction to Data Structure. CHAPTER 6 GRAPHS. 6.1 The Graph Abstract Data Type 6.2 Elementary Graph Operations 6.3 Minimum Cost Spanning Trees 6.4 Shortest Paths and Transitive Closure 6.5 Activity Networks. Contents. Chapter 1 Basic Concepts Chapter 2 Arrays

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Lecture 11 Algorithm Analysis

Lecture 11 Algorithm Analysis. Arne Kutzner Hanyang University / Seoul Korea. Elementary Graph Algorithms. Graph Representation. Given graph G = (V, E) . May be either directed or undirected When expressing the running time of an algorithm, it is often in terms of both | V | and | E |.

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Mesh Data Structure

Mesh Data Structure. Meshes. Corners ? V x F Half-edges ? E x F. Mesh: straight-line graph embedded in R 3. Boundary edge: adjacent to 1 face Regular edge: adjacent to 2 faces Singular edge: adjacent to >2 faces. Closed mesh: mesh with no boundary edges

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Testing Expansion in Bounded Degree Graphs

Testing Expansion in Bounded Degree Graphs. Christian Sohler University of Dortmund (joint work with Artur Czumaj, University of Warwick). Testing Expansion in Bounded Degree Graphs Introduction. Property Testing[Rubinfeld, Sudan]:

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Graphs

Graphs. Graphs are collections of vertices and edges. Vertices are simple objects with associated names and other properties. Edges are connections between two vertices.

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Directed Depth First Search

Directed Depth First Search. A. Adjacency Lists A: F G B: A H C: A D D: C F E: C D G F: E : G: : H: B : I: H :. B. H. C. G. I. D. E. F. Directed Depth First Search. A. B. H. C. G. I. D. E. F. dfs(A) A-F A-G. Undiscovered. Marked. Active. Finished.

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10 - Graphs

10 - Graphs. Original Slides by Rada Mihalcea. What is a Graph?. A graph G = ( V ,E) is composed of: V : set of vertices E : set of edges connecting the vertices in V An edge e = (u,v) is a pair of vertices Example:. a. b. V = {a,b,c,d,e} E = {(a,b),(a,c),(a,d),

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CHAPTER 9 GRAPH ALGORITHMS

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Graph Theory in Molecular Modeling

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Graph Traversals

Is G connected?. Is there a path from vertex a to vertex b ? . Does G have a cycle? . Will removing a single edge disconnect G ?. If G is directed, what are the strongly connected components?. If G is the WWW, follow links to locate information. .

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Chapter 9: Graphs

Mark Allen Weiss: Data Structures and Algorithm Analysis in Java. Chapter 9: Graphs. Scheduling Networks. Lydia Sinapova, Simpson College. Scheduling Networks. Definitions Purpose of the Model Algorithm Critical Activities Complexity Example. Definitions.

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Representing Graphs

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CHAPTER 9 GRAPH ALGORITHMS

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A SEQUENTIAL IMPORTANCE SAMPLING ALGORITHM FOR GENERATING RANDOM GRAPHS WITH PRESCRIBED DEGREES

A SEQUENTIAL IMPORTANCE SAMPLING ALGORITHM FOR GENERATING RANDOM GRAPHS WITH PRESCRIBED DEGREES. (Introduction). For example d = (2, 2, 2). Other Algorithms. 1 . Algorithms for random graphs with given degree distributions . 2 . The Pairing Model . 3 . Algorithms Based on the Pairing Model

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