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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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Book ChapterDOI
Pattern Matching in Compressed Texts
TL;DR: The basic compression algorithm is extended into another that achieves, for any k ≥1, O(nk+m1+1/k log m) steps, and the problem of pattern matching when the text is in compressed form is considered.
Book ChapterDOI
Architecture Independent Massive Parallelization of Divide-and-Conquer Algorithms
Klaus Achatz,Wolfram Schulte +1 more
TL;DR: A set of semantics preserving transformation rules are applied, which transform the parallel control structure of DC into a sequential control flow, thereby making the implicit data parallelism in a DC scheme explicit.
Journal ArticleDOI
An Investigation of Scalable SIMD I/O Techniques with Application to Parallel JPEG Compression
G.W. Cook,Edward J. Delp +1 more
TL;DR: This paper addresses the parallel implementation of the JPEG still-image compression standard on the MasPar MP-1, a massively parallel SIMD computer, and develops two novel byte alignment algorithms which are used to efficiently input and output compressed data from the parallel system.
Book ChapterDOI
Near Optimal Work-Stealing Tree Scheduler for Highly Irregular Data-Parallel Workloads
TL;DR: A work-stealing algorithm for runtime scheduling of data-parallel operations in the context of shared-memory architectures on data sets with highly-irregular workloads that are not known a priori to the scheduler is presented.
Proceedings Article
Evaluating Arithmetic Expressions Using Tree Contraction: A Fast and Scalable Parallel Implementation for Symmetric Multiprocessors (SMPs) (Extended Abstract)
TL;DR: In this paper, a uniform shared-memory algorithm from a PRAM algorithm is presented, which scales nearly linearly across a significant range of processors and across the entire range of instance sizes tested.
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.