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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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Book ChapterDOI
Fast and Scalable Parallel Algorithms for Matrix Chain Product and Matrix Powers on Optical Buses
TL;DR: The authors' highly scalable algorithms can be implemented on a linear array with a reconfigurable pipelined bus system, which is a distributed memory system using optical interconnections.
Proceedings ArticleDOI
Performance predictions for parallel diagonal-implicitly iterated Runge-Kutta methods
Thomas Rauber,Gudula Rünger +1 more
TL;DR: This work investigates the parallel implementation of the diagonal-implicitly iterated Runge-Kutta method, a solution method for stiff systems of ordinary differential equations, and confirms the accuracy of the prediction model.
Journal ArticleDOI
Compiling machine-independent parallel programs
TL;DR: Initial evidence is presented that explicitly parallel, machine-independent programs can automatically be translated into parallel machine code that is competitive in performance with hand-written code.
Proceedings ArticleDOI
Parallel jaccard and related graph clustering techniques
TL;DR: It is shown that the novel weights can improve the quality of the graph clustering by about 15% and 80% for multi-level and spectral graph partitioning and clustering schemes, respectively.
Book ChapterDOI
A parallel algorithm for finding all successive minimal maximum subsequences
Ho-Kwok Dai,Hung-Chi Su +1 more
TL;DR: This work presents a logarithmic-time and optimal linear-work parallel algorithm on the parallel random access machine model that finds all successive minimal maximum subsequences of a real-valued sequence.
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.