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An introduction to parallel algorithms
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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. 0201548569B04062001read more
Citations
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Proceedings ArticleDOI
A performance prediction model for the CUDA GPGPU platform
Kishore Kothapalli,Rishabh Mukherjee,M. Suhail Rehman,Suryakant Patidar,P. J. Narayanan,Kannan Srinathan +5 more
TL;DR: This paper presents a performance prediction model for the CUDA GPGPU platform that encompasses the various facets of the GPU architecture like scheduling, memory hierarchy, and pipelining among others and can be used to analyze pseudo code for a CUDA kernel to obtain a performance estimate.
Journal ArticleDOI
A fast, parallel spanning tree algorithm for symmetric multiprocessors (SMPs)
David A. Bader,Guojing Cong +1 more
TL;DR: A new randomized algorithm and implementation with superior performance that for the first time achieves parallel speedup on arbitrary graphs (both regular and irregular topologies) when compared with the best sequential implementation for finding a spanning tree.
Posted Content
A Tensor Approach to Learning Mixed Membership Community Models
TL;DR: In this article, a tensor spectral decomposition method is proposed to learn the mixed membership Dirichlet model for a family of probabilistic network models with overlapping communities, which allows for nodes to have fractional memberships in multiple communities.
Proceedings ArticleDOI
Julienne: A Framework for Parallel Graph Algorithms using Work-efficient Bucketing
TL;DR: The Julienne framework is developed, which extends a recent shared-memory graph processing framework called Ligra with an interface for maintaining a collection of buckets under vertex insertions and bucket deletions, and develops the first work-efficient parallel algorithm for k-core in the literature with nontrivial parallelism.
Journal ArticleDOI
Solving large FPT problems on coarse-grained parallel machines
TL;DR: The potential of parallelism when applied to the bounded-tree search phase of FPT algorithms is demonstrated, thereby allowing even larger problem instances to be solved in practice.
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,Faye A. Briggs +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
W. Daniel Hillis,Guy L. Steele +1 more
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
Steven Fortune,James C. Wyllie +1 more
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.