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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

What the parallel-processing community has (failed) to offer the multi/many-core generation

TL;DR: There is a mismatch in computer-science education concerning parallelism, and that there may be reasons to be concerned, according to the panelists.
Journal ArticleDOI

Applications of interval computations to earthquake-resistant engineering: How to compute derivatives of interval functions fast

TL;DR: Special control linkages between floors that are normally unattached to the building but can be attached if necessary are designed so designed that adding them changes the building's characteristic frequency.
Book ChapterDOI

A Hardware Implementation of PRAM and Its Performance Evaluation

TL;DR: A PRAM (Parallel Random Access Machine) is the parallel computational model most notable for supporting the parallel algorithmic theory and consists of a number of processors sharing a common memory.
Proceedings ArticleDOI

An optimal randomized ranking algorithm on the k-channel broadcast communication model

TL;DR: The main contribution of the paper is to present an optimal randomized ranking algorithm on the k-channel BCM, which solves the ranking problem, with high probability, in O(n/k+log n) time slots with no station being awake for more than O(log n] time slots.
Posted Content

A Framework for Analyzing Resparsification Algorithms

TL;DR: This work presents a framework for analyzing algorithms that perform repeated sparsifications that only incur error corresponding to a single sparsification step, leading to better results for many of these reseparsification based algorithms.
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.