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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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Journal ArticleDOI
Simple Optimal Parallel Multiple Pattern Matching
TL;DR: This paper presents a simple algorithm for solving the multipattern matching problem, with optimal speedup, and the sequential version of the algorithm derived by slowing down the parallel design yields a new and simple (linear-time) algorithm for string matching.
Journal ArticleDOI
Parallelism in divide-and-conquer non-dominated sorting: a theoretical study considering the PRAM-CREW model
TL;DR: The scope of parallelism in an approach called divide-and-conquer based non-dominated sorting (DCNS) is explored, with the time complexity of the parallel version of the DCNS approach in different scenarios proved to be $$\mathcal {O}(\log M + N)$$O(logM+N).
Parallelizing the Linkage Tree Genetic Algorithm and Searching for the Optimal Replacement for the Linkage Tree
TL;DR: Two parallel implementations of LTGA are presented that enable us to leverage the computational power of a multi-processor architecture and solve a problem that previously could not be solved, being the problem of finding high-quality predetermined linkage models that result in a better performance ofLTGA for intricate problems by replacing the online-learned LTs.
Posted Content
Removing Sequential Bottleneck of Dijkstra's Algorithm for the Shortest Path Problem.
TL;DR: A method which maintains lower bounds as well as upper bounds for reaching a vertex is introduced which enables one to find the optimal cost for multiple vertices in one iteration and thereby reduces the sequential bottleneck in Dijkstra's algorithm.
Proceedings ArticleDOI
Randomized Initialization on the 1-Dimensional Reconfigurable Mesh
TL;DR: This paper shows initialization algorithms on the 1-dimensional reconfigurable mesh with n processors, and shows that expected sublinear-time initialization is possible if the authors use randomized techniques, and proves that any randomized initialization need to run in O(log n) time.
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.