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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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Journal ArticleDOI
Polynomial interpolation and polynomial root finding on OTIS-mesh
TL;DR: The optimality/near optimality of the algorithms is shown to achieve with the assumption that the data elements are initially stored following the row-column mapping and group mapping of theOTIS-mesh network.
Book ChapterDOI
Efficient Secure Linear Algebra in the Presence of Covert or Computationally Unbounded Adversaries
Payman Mohassel,Enav Weinreb +1 more
TL;DR: The main result is a new upper bound of O(n2 + 1/t) communication for testing singularity of a shared n×nmatrix in constant round, for any constant round in both adversarial environments.
Book ChapterDOI
A note on secure computation of the moore-penrose pseudoinverse and its application to secure linear algebra
TL;DR: A new method for secure polynomial evaluation that exploits properties of Chebychev polynomials, as well as a new secure protocol for computing the characteristicPolynomial of a matrix based on Leverrier's lemma that exploits this new method.
Journal ArticleDOI
Efficient breadth first search on multi-GPU systems
TL;DR: This work proposes a novel technique for mapping threads to data that achieves a perfect load balance by leveraging prefix-sum and binary search operations and shows that a cluster of GPUs can efficiently perform a distributed BFS on graphs with billions of nodes.
Proceedings ArticleDOI
Fast Two Dimensional Convex Hull on the GPU
TL;DR: This paper presents a GPU-optimized implementation for finding the convex hull of a two dimensional point set and achieves a speedup of up to 14 over the standard sequential CPU implementation.
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.