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An introduction to parallel algorithms

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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Proceedings ArticleDOI

Parallel Exact Inference on Multicore Using MapReduce

TL;DR: The experimental results show that the methods achieve 20x speedup on an Intel West mere-EX based system, andMapReduce based algorithms are proposed for evidence propagation in junction trees.
Proceedings ArticleDOI

An O(p + log p) algorithm of discrete FGDLS

TL;DR: An O(p + log p) algorithm for the FGDLS method in the discrete case is proposed, which applies the balanced workload scheduling to the piecewise constant workloads to obtain the iteration bounds.
Journal IssueDOI

Applications of parallel processing technologies in heuristic search planning: methodologies and experiments

TL;DR: It shows that an appropriate parallelization of a sequential planning system often brings gain in performance and-or scalability and the application of parallel programming techniques to boost the performance of heuristic search-based planning systems in various aspects.
Posted Content

Bidirectional Text Compression in External Memory

TL;DR: This work evaluates an external memory decompressor for texts compressed with any uni- or bidirectional compression scheme and shows that it is significantly faster than all known LZ77 compressors, while producing a roughly similar number of factors.
Proceedings ArticleDOI

Data Parallelism for Belief Propagation in Factor Graphs

TL;DR: This paper develops algorithms for basic operations called node level primitives for updating the distribution tables in a factor graph and proposes a complete belief propagation algorithm to perform exact inference in such graphs.
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.