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An introduction to parallel algorithms

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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. 0201548569B04062001

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Journal ArticleDOI

Eliminating duplicates under interval and fuzzy uncertainty: An asymptotically optimal algorithm and its geospatial applications

TL;DR: It is shown that a natural duplicate deletion algorithm requires (in the worst case) quadratic time, and a new asymptotically optimal O(n⋅ log (n) algorithm is proposed, which has been successfully applied to gravity databases and will prove to be useful when dealing with many other types of point data.
Journal ArticleDOI

Architectural differences of efficient sequential and parallel computers

TL;DR: The performance of eight general purpose processor architectures representing widely both commercial and scientific processor designs in both single processor and multiprocessor setups is evaluated and it is concluded that there exists no single optimal architecture for general purpose computation.
Journal ArticleDOI

The mesh with hybrid buses: an efficient parallel architecture for digital geometry

TL;DR: An efficient VLSI architecture obtained by augmenting the Mesh with Multiple Broadcasting with precharged 1-bit row and column buses is proposed and it is shown that the MHB is extremely well-suited for solving an entire slew of digital geometry tasks.
Posted Content

Mathematical and Algorithmic Analysis of Network and Biological Data

TL;DR: This dissertation contributes to mathematical and algorithmic problems that arise in the analysis of network and biological data.

Parallel and Distributed Algorithms

TL;DR: In this article, Monte Carlo approximation of π has been used to approximate the area of the circle C with radius one and the square S = [−1,+1]2.
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, +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

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

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.