Open AccessBook
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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Journal ArticleDOI
Construction of universal one-way hash functions: Tree hashing revisited
TL;DR: A binary tree based parallel algorithm for extending the domain of a universal one-way hash function (UOWHF) for t≥2, where m is the length of the message digest.
Journal ArticleDOI
On the usage of simulators to detect inefficiency of parallel programs caused by “bad” schedulings: the SIMPARC approach
Yosi Ben-Asher,Gadi Haber +1 more
TL;DR: The simulator and the experiments form a methodology for detecting possible bottlenecks of performance degradation, and it is shown that the gap between them can be used to detect whether the current scheduling is a possible cause for a performance degradation.
Journal ArticleDOI
An Extended PRAM-NUMA Model of Computation for TCF Programming
Martti Forsell,Ville Leppänen +1 more
TL;DR: This paper proposes an extended PRAM-NUMA model of computation that can be used to implement efficient shared memory computers for general purpose parallel applications with enough parallelism and yet support sequential and NUMA legacy code and avoid loss of performance in applications with low parallelism.
Book ChapterDOI
Models for Parallel Algorithm Design: An Introduction
Afonso Ferreira,Michel Morvan +1 more
TL;DR: This chapter presents three classical models used for the design of parallel algorithms: the PRAM (shared memory) model, the distributed memory model, and the coarse grained multicomputer model.
Journal ArticleDOI
Orthogonally Drawing Cubic Graphs in Parallel
TL;DR: This parallel algorithm is the first dealing with nonplanar, nonbiconnected graphs, and no embedding of the graph is requested as input nor is anst-numbering (orlmc- numbering) computed.
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.