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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Proceedings Article
The Strong Distance Problems.
TL;DR: For the Cartesian product G×H of any two graph G and H, two inequalities are found to obtained an upper bound of srad(G×H) and sdiam(G ×H) for graph G be the hypercube graph BCn, the extension hypercube graphs ECn and FCn.
Theory and Engineering of Scheduling Parallel Jobs
TL;DR: This thesis investigates the interplay and distribution of decision makers, the efficient schedule computation, efficient scheduling for the memory hierarchy and energy-efficiency, and produces a provably fast and efficient scheduling algorithm for malleable jobs.
Efficient parallel computation on multiprocessors with optical interconnection networks
Min He,Sumit Sharma +1 more
TL;DR: This dissertation aims to provide a history of parallel computation in China and some of the techniques used in this area have been proposed and described in detail in a number of publications published in the literature.
Posted Content
Parallel Local Graph Clustering.
TL;DR: In this article, the authors show how to parallelize many local graph clustering algorithms in the shared-memory multicore setting, and analyze the parallel complexity of these algorithms, showing that their parallel algorithms achieve good parallel speedups on a modern multicore machine, thus significantly speeding up the analysis of local graph clusters in the very large-scale setting.
Book ChapterDOI
Communication-Efficient Parallel Multiway and Approximate Minimum Cut Computation
TL;DR: Improved BSP implementations of the algorithm of Karger and Stein are presented and results are close to optimal for the minimal cut problem and for the case of multiway cut and approximate minimum cut the authors obtain optimal, communication efficient results.
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.