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An introduction to parallel algorithms
TLDR
This book provides an introduction to the design and analysis of parallel algorithms, with the emphasis on the application of the PRAM model of parallel computation, with all its variants, to algorithm analysis.Abstract:
Written by an authority in the field, this book provides an introduction to the design and analysis of parallel algorithms. The emphasis is on the application of the PRAM (parallel random access machine) model of parallel computation, with all its variants, to algorithm analysis. Special attention is given to the selection of relevant data structures and to algorithm design principles that have proved to be useful. Features *Uses PRAM (parallel random access machine) as the model for parallel computation. *Covers all essential classes of parallel algorithms. *Rich exercise sets. *Written by a highly respected author within the field. 0201548569B04062001read more
Citations
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Time Lower Bounds for Parallel Network Computations
TL;DR: A survey of several known lower bound techniques involving DAGs, followed by original theorems which clarify or solve open problems and a new general technique which provides lower bounds almost tight in a class of network emulations including multidimensional arrays.
Proceedings ArticleDOI
Computational bounds for the simple and the MRMW PRAM
Fabrizio Luccio,Linda Pagli +1 more
TL;DR: The Multiple Read Multiple Write (MRMW) PRAM model is introduced, that allows a bounded amount of simultaneous transfers from m memory cells to one processor (MR), and vice-versa (MW), and derive exact computational bounds as a function of m.
Journal ArticleDOI
Optimal parallel matching on bipartite permutation graphs
Hiryoung Kim,Alan P. Sprague +1 more
TL;DR: This work presents a cost-optimal parallel algorithm for the maximum matching problem on bipartite permutation graphs on an EREW PRAM and defines a nontrivial binary operation which is associative and equivalent to the greedy algorithm.
Parallel algorithm to solve the bimatriceal subgames generated by the informational extended strategies
TL;DR: Parallel algorithm for mixed system with shared and distributed memory to solve bimatrix game generated by the informational extended strategies is described.
Journal ArticleDOI
Fundamental ideas for a parallel computing course
TL;DR: An introductory undergraduate (or early graduate) course that spans the spectrum of what the authors call parallel computing is analyzed, which should include algorithms, interconnection network architectures, theory, and programming and should build on top of the core CS courses.
References
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Book
Introduction to Parallel Algorithms and Architectures: Arrays, Trees, Hypercubes
TL;DR: This chapter discusses sorting on a Linear Array with a Systolic and Semisystolic Model of Computation, which automates the very labor-intensive and therefore time-heavy and expensive process of manually sorting arrays.
Book
Computer Architecture and Parallel Processing
Kai Hwang,Faye A. Briggs +1 more
TL;DR: The authors have divided the use of computers into the following four levels of sophistication: data processing, information processing, knowledge processing, and intelligence processing.
Journal ArticleDOI
Data parallel algorithms
W. Daniel Hillis,Guy L. Steele +1 more
TL;DR: The success of data parallel algorithms—even on problems that at first glance seem inherently serial—suggests that this style of programming has much wider applicability than was previously thought.
Proceedings ArticleDOI
Parallelism in random access machines
Steven Fortune,James C. Wyllie +1 more
TL;DR: A model of computation based on random access machines operating in parallel and sharing a common memory is presented and can accept in polynomial time exactly the sets accepted by nondeterministic exponential time bounded Turing machines.
Journal ArticleDOI
The Parallel Evaluation of General Arithmetic Expressions
TL;DR: It is shown that arithmetic expressions with n ≥ 1 variables and constants; operations of addition, multiplication, and division; and any depth of parenthesis nesting can be evaluated in time 4 log 2 + 10(n - 1) using processors which can independently perform arithmetic operations in unit time.