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An introduction to parallel algorithms
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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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Algorithms for All Single Deletions in a Minimum Spanning Tree, Simultaneously
TL;DR: These algorithms present sequential and parallel algorithms for deter mining the minimum spanning tree of each graph G t for all edges t in T and each graphs G — v for all v in V, simultaneously, simultaneously.
Journal ArticleDOI
Additive tree 2-spanners of permutation graphs
Hon-Chan Chen,Fu-Hsing Wang +1 more
TL;DR: It is shown that any permutation graph has an additive tree 2-spanner, and it can be found in O(n) time sequentially or with O(log n) time with O- processors on the EREW PRAM computational model by using a previously published algorithm.
Posted Content
Bandwidth-Optimal Random Shuffling for GPUs.
TL;DR: In this paper, the authors proposed a parallel pseudo-random shuffle algorithm for parallel data shuffling on GPUs, which trades increased per-thread arithmetic operations for reduced global memory transactions.
Journal ArticleDOI
Optimal hypercube simulation on the partitioned optical passive stars network
TL;DR: It is shown that one-hop movements on the hypercube along the same dimension can be simulated on the POPS(d,g) network in slots for d≠g and in 2 slots ford=g.
Journal ArticleDOI
PRAM programming: in theory and in practice
TL;DR: This work objectively compares optimized BSP and PRAM algorithms implemented with the authors' C++ PRAM library and provides encouraging experimental results for the new style of programming, which achieves simplicity of programming over direct-mode BSP programming for reasonable overhead cost.
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.