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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
Optimal algebraic Breadth-First Search for sparse graphs
TL;DR: A new optimal, algebraic BFS for sparse graphs is given, thus closing a gap in the literature and takes O(n) algebraic operations as opposed to O(m) operations needed by theoretically optimal sparse matrix approaches on a sparse graph.
Proceedings ArticleDOI
Parallel algorithms for image processing: practical algorithms with experiments
A. Baumker,W. Dittrich +1 more
TL;DR: The authors' algorithms are randomized and 2-optimal with high probability for a wide range of BSP* parameters where the range becomes larger with growing input sizes and improve on previous results as they either need an asymptotically smaller amount of data to be communicated or fewer communication rounds.
Book ChapterDOI
Sorting and Permuting without Bank Conflicts on GPUs
Peyman Afshani,Nodari Sitchinava +1 more
TL;DR: The complexity of designing algorithms without any bank conflicts in the shared memory of Graphical Processing Units (GPUs) is looked at.
Proceedings ArticleDOI
Enlarging the scope of vector-based computations: extending Fortran 90 by nested data parallelism
K. T. P. Au,Manuel M. T. Chakravarty,J. Darlington,Yike Guo,Stefan Jähnichen,Martin Köhler,Gabriele Keller,W. Pfannenstiel,Martin Simons +8 more
TL;DR: This paper describes the integration of nested data parallelism into Fortran 90 and introduces the imperative data-parallel languageFortran 90V and gives an overview of its implementation.
Journal ArticleDOI
Efficient List Ranking on the Reconfigurable Mesh, with Applications
TL;DR: This work proposes a deterministic list-ranking algorithm that runs in O(log*n ) time as well as a randomized one running in O (1) expected time, both on a reconfigurable mesh of size $n \times n$ .
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.