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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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Proceedings ArticleDOI
Practical Parallel Lempel-Ziv Factorization
Julian Shun,Fuyao Zhao +1 more
TL;DR: This work presents a simple work-efficient parallel algorithm for Lempel-Ziv factorization, and shows theoretically that the algorithm requires linear work and runs in O(log2 n) time (randomized) for constant alphabets and O(nϵ)Time (ϵ <; 1) for integer alphABets.
Posted Content
ConnectIt: A Framework for Static and Incremental Parallel Graph Connectivity Algorithms
TL;DR: The ConnectIt framework is designed, which provides different sampling strategies as well as various tree linking and compression schemes, and is able to compute connectivity on the largest publicly-available graph in under 10 seconds using a 72-core machine.
Posted Content
Parallel Algorithms for Butterfly Computations
Jessica Shi,Julian Shun +1 more
TL;DR: A framework called ParButterfly is designed that contains new parallel algorithms for the following problems on processing butterflies: global counting, per-vertex counting,per-edge counting, tip decomposition (vertex peeling, and wing decomposition), and edge peeling.
Proceedings ArticleDOI
On-line Scheduling of MPI-2 Programs with Hierarchical Work Stealing
TL;DR: This work presents an on-line scheduling algorithm, called Hierarchical Work Stealing, to obtain good load-balancing of MPI- 2 programs that follow a Divide & Conquer strategy, and results show that the Hierarchic Work St stealing algorithm enables the use ofMPI with high efficiency, even in parallel dynamic HPC platforms that are not as homogeneous as clusters.
Journal ArticleDOI
Adapting parallel algorithms to the W-Stream model, with applications to graph problems
TL;DR: The RelaxedPRAM (RPRAM) computational model is introduced, as an intermediate model between PRAM and W-Stream, which gives new insights on developing streaming algorithms and yields efficient algorithms for several classical problems in this model including sorting, connectivity, minimum spanning tree, biconnected components, and maximal independent set.
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.