## Introduction to Parallel AlgorithmsParallel algorithms Made Easy The complexity of today's applications coupled with the widespread use of parallel computing has made the design and analysis of parallel algorithms topics of growing interest. This volume fills a need in the field for an introductory treatment of parallel algorithms-appropriate even at the undergraduate level, where no other textbooks on the subject exist. It features a systematic approach to the latest design techniques, providing analysis and implementation details for each parallel algorithm described in the book. Introduction to Parallel Algorithms covers foundations of parallel computing; parallel algorithms for trees and graphs; parallel algorithms for sorting, searching, and merging; and numerical algorithms. This remarkable book: * Presents basic concepts in clear and simple terms * Incorporates numerous examples to enhance students' understanding * Shows how to develop parallel algorithms for all classical problems in computer science, mathematics, and engineering * Employs extensive illustrations of new design techniques * Discusses parallel algorithms in the context of PRAM model * Includes end-of-chapter exercises and detailed references on parallel computing. This book enables universities to offer parallel algorithm courses at the senior undergraduate level in computer science and engineering. It is also an invaluable text/reference for graduate students, scientists, and engineers in computer science, mathematics, and engineering. |

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An Excellent book.... explains concepts in a brilliant way

### Contents

FOUNDATlONS OF PARALLEL COMPUTlNG | 3 |

Elements of Parallel Computing | 18 |

Data Structures for Parallel Computing | 59 |

Paradigms for Parallel Algorithm | 108 |

Simple Algorithms | 123 |

Tree Algorithms | 145 |

Graph Algorithms | 184 |

NC Algorithms for Chordal Graphs | 213 |

### Common terms and phrases

1n order adjacency matrix algorithm to find architectures BEG1N BEGlN biconnected called child chordal graph clique tree cliques of G complete binary tree Complexity Analysis connected components connected graph Consider contains CREW PRAM model cycle data structure defined denote Develop a parallel dominating set elements equation EREW Euler circuit evaluate example fc-cube Figure formula G is chordal given graph shown Hence induced subgraph integer intersection graph interval graph iteration Let G level number linear linked list lnput loop lowest common ancestor M1MD maximal cliques memory merging method minimal minimum number of edges number of processors number of vertices Output pair parallel algorithm parallel computing parent path matching prefix sum problem procedure processing rake operation recursive relative speedup represented result rooted tree sequential algorithm shown in Fig solve sorting network spanning tree step subtrees THEOREM Toeplitz matrix values variable vector vector processors verify vertex weight