Open AccessBook
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. 0201548569B04062001read more
Citations
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Journal ArticleDOI
Fast randomized parallel methods for planar convex hull construction
TL;DR: A number of efficient parallel algorithms for constructing 2-dimensional convex hulls on a randomized CRCW PRAM are presented, including one that uses a new parallel technique called failure sweeping to achieve n-exponential confidence bounds.
Proceedings ArticleDOI
Serverless architecture for workflow scheduling with unconstrained execution environment
TL;DR: A fully serverless and infinitely scalable architecture that is based on producer-consumer pattern and can be shaped to satisfy wide range of requirements is proposed, which improves upon existing architectures that revolve around cloud functions.
Book ChapterDOI
Time-Optimal Nearest-Neighbor Computations on Enhanced Meshes
Stephan Olariu,Ivan Stojmenovic +1 more
TL;DR: This work proposes time-optimal algorithms for constructing the Euclidian Minimum Spanning Tree, the Relative Neighborhood Graph, as well as the Symmetric Further Neighbor Graph of an n-vertex unimodal polygon on meshes with multiple broadcasting.
Proceedings ArticleDOI
SIMD: an additional pattern for PLPP (pattern language for parallel programming)
TL;DR: A pattern to help software developers construct parallel programs for environments that support this style of data parallelism is presented, in which the program is viewed as a single thread of control, with implicitly parallel updates to data.
Priority queues on parallel machines
TL;DR: A pipelined version of the priority queues adopt to a processor array of size O(log n), supporting the operations MakeQueue, Insert, Meld, FindMin, Extractmin, Delete and DecreaseKey in constant time.
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.