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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

Discrete range searching primitive for the GPU and its applications

TL;DR: It is suggested that graph algorithms that use the least common ancestor, can be enabled on the GPU based on DRS primitive, and some applications of DRS in tree queries and string querying are shown.
Proceedings ArticleDOI

O(log2 n) time efficient parallel factorization of dense, sparse separable, and banded matrices

TL;DR: New parallel methods for various exact factorizations of several classes of matrices are given, match the best known work bounds of parallel algorithms with polylog time bounds, and are within a log factor of the work bounds for the bestknown sequential algorithms for the same problems.

A Parallel Algorithm Development Model for the GPU Architecture

TL;DR: A parallel GPU model is proposed which offers both a general design and a fine-grained approach, intended to accommodate nearly any GPU architecture, which can result in significant increases in performance when algorithms are designed based on its principles.
Journal ArticleDOI

Efficient and flexible text extraction from document pages

TL;DR: A novel method for extracting text from document pages of mixed content by detecting pieces of text lines in small overlapping columns of width shifted with respect to each other by image elements and merging these pieces in a bottom-up fashion to form complete text lines and blocks oftext lines.
Book ChapterDOI

Techniques for designing efficient parallel graph algorithms for SMPs and multicore processors

TL;DR: Techniques for designing and implementing efficient parallel algorithms for graph problems on symmetric multiprocessors and chip multiprocessionors with a case study of parallel tree and connectivity algorithms are proposed.
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.