Parallel and Distributed Computation: Numerical Methods

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Athena Scientific, Mar 1, 2015 - Mathematics - 735 pages
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This highly acclaimed work, first published by Prentice Hall in 1989, is a comprehensive and theoretically sound treatment of parallel and distributed numerical methods. It focuses on algorithms that are naturally suited for massive parallelization, and it explores the fundamental convergence, rate of convergence, communication, and synchronization issues associated with such algorithms.

This is an extensive book, which aside from its focus on parallel and distributed algorithms, contains a wealth of material on a broad variety of computation and optimization topics. It is an excellent supplement to several of our other books, including Convex Optimization Algorithms (Athena Scientific, 2015), Nonlinear Programming (Athena Scientific, 1999), Dynamic Programming and Optimal Control (Athena Scientific, 2012), Neuro-Dynamic Programming (Athena Scientific, 1996), and Network Optimization (Athena Scientific, 1998).

The on-line edition of the book contains a 95-page solutions manual.

 

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Contents

Introduction
1
Algorithms for Systems of Linear Equations and Matrix Inversion
109
Iterative Methods for Monlinear Problems
180
Shortest Paths and Dynamic Programming
291
Network Flow Problems
331
Totally Asynchronous Iterative Algorithms
425
Partially Asynchronous Iterative Methods
481
Organizing an Asynchronous Network of Processors for Distributed Computation
570
Index
707
Partial Solutions Manual
717
Chapter 1
1
Chapter 2
23
Chapter 3
36
Chapter 4
49
Chapter 5
60
Chapter 6
71

Linear Algebra and Analysis
618
Graph Theory
653
Duality Theory
659
Probability Theory and Markov Chains
670
References
680
Chapter 7
74
Chapter 8
90
Corrections
96
Copyright

Other editions - View all

Parallel and Distributed Computation: Numerical Methods
Dimitri P. Bertsekas,John N. Tsitsiklis
Snippet view - 1989
Parallel and Distributed Computation: Numerical Methods
Dimitri P. Bertsekas,John N. Tsitsiklis
Snippet view - 1989

Common terms and phrases

algorithm applies assignment assume Assumption asynchronous bounded broadcast called communication complete component computation condition consider constant continuous convergence convex coordinate corresponding cost cycle defined definition depends differentiable direction discussed distributed dual elements entries equal equation equivalent example execution Exercise exists fact Figure finite fixed flow follows function Furthermore Gauss-Seidel given gradient graph holds hypercube implementation implies inequality initial iteration Lemma length limit linear mapping matrix method minimize multiplication needed node norm Note Notice obtain optimal packet parallel particular path performed phase positive possible problem processor projection proof Prop Proposition prove received relaxation respectively result reversal satisfies seen sequence shortest shown single solution solving Step Subsection Suppose takes termination unique units update variables vector xi(t zero

About the author (2015)

Dimitri P. Bertsekas is Fulton Professor of Computational Decision Making, at Arizona State University, and McAfee Professor of Engineering at the Massachusetts Institute of Technology. He is a winner of many awards and a member of the prestigious United States National Academy of Engineering

John N. Tsitsiklis is Clarence Lebel Professor of Electrical Engineering at the Massachusetts Institute of Technology. He is a winner of many awards and is a member of the prestigious United States National Academy of Engineering

Bibliographic information

QR code for Parallel and Distributed Computation: Numerical Methods
TitleParallel and Distributed Computation: Numerical Methods
AuthorsDimitri Bertsekas, John Tsitsiklis
Editionreprint
PublisherAthena Scientific, 2015
ISBN1886529159, 9781886529151
Length735 pages
Subjects ›  › 

Computers / Data Science / Data Analytics
Mathematics / Optimization
  
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