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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

SNAP, Small-world Network Analysis and Partitioning: An open-source parallel graph framework for the exploration of large-scale networks

TL;DR: This work discusses the design, implementation, and performance of three novel parallel community detection algorithms that optimize modularity, a popular measure for clustering quality in social network analysis, and exploits typical network characteristics of small-world networks, such as the low graph diameter, sparse connectivity, and skewed degree distribution.
Proceedings ArticleDOI

Fast GPU-based locality sensitive hashing for k-nearest neighbor computation

TL;DR: An efficient GPU-based parallel LSH algorithm to perform approximate k-nearest neighbor computation in high-dimensional spaces and demonstrates the results on large image datasets with 200,000 images which are represented as 512 dimensional vectors.
Proceedings ArticleDOI

Extending the Representational State Transfer (REST) architectural style for decentralized systems

TL;DR: Variations of the World Wide Web's Representational State Transfer (REST) architectural style are presented, implemented, and evaluated to support distributed and decentralized systems.
Journal ArticleDOI

Communication-Efficient Parallel Sorting

TL;DR: The bound on the number of communication rounds is asymptotically optimal for the full range of values for p, for it is shown that just computing the "or" of n bits distributed evenly to the first O(n/h) of an arbitrary number of processors in a BSP computer requires $\Omega(\log n/\log (h+1))$ communication rounds.
Proceedings ArticleDOI

Fundamental parallel algorithms for private-cache chip multiprocessors

TL;DR: This paper presents two sorting algorithms, a distribution sort and a mergesort, and studies sorting lower bounds in a computational model, which is called the parallel external-memory (PEM) model, that formalizes the essential properties of the algorithms for private-cache CMPs.
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.