## Algorithms Sequential & Parallel: A Unified ApproachAlgorithms: Sequential and Parallel takes an innovative approach to a traditional algorithms-based course of study. This new approach addresses the changing challenges of computer scientists in the fields of computational science and engineering. With the onset of parallel computing becoming more mainstream, the authors address this dynamic by merging the application and analysis of algorithmic paradigms to both the (traditional) sequential model of computing and to a variety of parallel models. This book offers the student and the scientist an integrated coverage of a fundamental course in algorithms. The book was successfully class tested at both the undergraduate and graduate levels at the State University of New York at Buffalo. *The text offers a unified approach that relates sequential and parallel algorithms where appropriate and contrasts where appropriate. *Mathematical tools are developed in early chapters. *A variety of examples are worked out in great detail with multiple methods of solutions. *Sequential and parallel examples and exercises are featured. *Supplemental material is available for instructors. *A Prentice Hall Companion Website with additional material is a |

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### Contents

ASYMPTOTIC ANALYSIS | 2 |

Rules for Analysis of Algorithms | 17 |

Mathematical Induction | 30 |

Copyright | |

13 other sections not shown

### Other editions - View all

Algorithms Sequential & Parallel: A Unified Approach Russ Miller,Laurence Boxer Limited preview - 2012 |

Algorithms Sequential & Parallel: A Unified Approach Russ Miller,Laurence Boxer Limited preview - 2012 |

Algorithms Sequential and Parallel: A Unified Approach Russ Miller,Laurence Boxer No preview available - 2005 |

### Common terms and phrases

0(n log adjacency matrix algorithm follows analysis architecture assume asymptotic bigList binary search bisection width bitonic sequences Bitonic Sort breadth-first search broadcast chapter column communication diameter connected components consider convex hull data items depth-first search distance divide-and-conquer edge efficient algorithm elements endpoint entry equalList Euler tour example extreme points function Gaussian elimination given graph G hull(S hypercube implementation initially input iteration line segments linear array linked list log2 machine MergeSort mesh mesh-of-trees minimum models of computation neighbors nodes Notice number of processors optimal output pair Parallel Algorithms parallel prefix partition path perform pointer pointer jumping positive integer PRAM algorithm prefix sum prefix values presented problem processor Pi QuickSort reader records recursive represent requires result rotation running semigroup operation sequential shown in Figure smallList solution sorting algorithm sorting network spanning tree step stored subarray Suppose tangent line transitive closure traversal undirected graph vertex vertices worst-case