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An introduction to parallel algorithms
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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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Proceedings ArticleDOI
Using 1D radar observations to detect a space explosion core among the explosion fragments: sequential and distributed algorithms
P.S. Debroux,J. Boehm,F. Modave,Vladik Kreinovich,Gang Xiang,Jan Beck,Kavitha Tupelly,Raj Kandathi,Luc Longpre,Karen Villaverde +9 more
TL;DR: New algorithms for processing 1D data that distinguish between the body at the core of the explosion and the slowly out-moving fragments are proposed.
Proceedings ArticleDOI
Work-time optimal k-merge algorithms on the PRAM
TL;DR: This work proposes simple and intuitive work-time optimal algorithms for the k-merge problem on two PRAM models that perform O(nlogk) work and run in O(log n) time on the EREW-PRAM and in O (log log n+log k) timeon the CREW- PRAM.
Journal ArticleDOI
Fast, efficient mutual and self simulations for shared memory and reconfigurable mesh
Yossi Matias,Assaf Schuster +1 more
TL;DR: The PRAM simulation is used to obtain the first efficient self-simulation algorithm of an RMESH with general switches, and it is shown that a 2 × n RMESH can be optimally simulated on a CRCW PRAM in Θ(α(n)) time, where α(·) is the slow-growing inverse Ackermann function.
Dissertation
A Performance Model For Gpu Architectures: Analysis And Design Of Fundamental Algorithms
TL;DR: This dissertation attempts to remedy this by presenting the Synchronous Parallel Throughput (SPT) model, a general performance model that aims to capture the factors that most impact algorithm performance on many-core architectures, and focuses on two factors that often create performance bottlenecks: memory latency and synchronization overhead.
Work Efficient Parallel Scheduling Algorithms
TL;DR: A parallel algorithm is presented that optimally schedules arbitrary precedence constraints on two processors and it is shown that optimal two processor schedules can be computed much more efficiently, if the precedence constraints are restricted to be series parallel graphs.
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.