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Algorithms for Parallel Processing

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Cover of 'Algorithms for Parallel Processing'

Table of Contents

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    Book Overview
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    Chapter 1 A General-Purpose Shared-Memory Model for Parallel Computation
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    Chapter 2 Supporting a Coherent Shared Address Space Across SMP Nodes: An Application-Driven Investigation
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    Chapter 3 Single-Message vs. Batch Communication
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    Chapter 4 Some Simple and Practical Strategies for Parallelism
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    Chapter 5 Locality in Computing Connected Components
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    Chapter 6 Routing in Optical and Wireless Networks
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    Chapter 7 Transparent Parallel Transactions on Replicated Autonomous Databases
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    Chapter 8 Mathematical Tools for Loop Transformations: From Systems of Uniform Recurrence Equations to the Polytope Model
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    Chapter 9 The Scalability of Mesh Improvement Algorithms
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    Chapter 10 Data Parallel Performance Optimizations Using Array Aliasing
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    Chapter 11 Coarsening, Sampling, and Smoothing: Elements of the Multilevel Method
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    Chapter 12 Some Methods of Parallel Pseudorandom Number Generation
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    Chapter 13 Performance of Parallel Sparse Triangular Solution
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    Chapter 14 Determining an out-of-Core FFT Decomposition Strategy for Parallel Disks by Dynamic Programming
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    Chapter 15 Enabling Department-Scale Supercomputing
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    Chapter 16 Providing Uniform Dynamic Access to Numerical Software
Attention for Chapter 4: Some Simple and Practical Strategies for Parallelism
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Chapter title
Some Simple and Practical Strategies for Parallelism
Chapter number 4
Book title
Algorithms for Parallel Processing
Published by
Springer, New York, NY, January 1999
DOI 10.1007/978-1-4612-1516-5_4
Book ISBNs
978-1-4612-7175-8, 978-1-4612-1516-5
Authors

Nicholas Carriero, David Gelernter

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