Parallel and Distributed Computation: Numerical Methods
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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Algorithms for Systems of Linear Equations and Matrix Inversion
Iterative Methods for Monlinear Problems
Shortest Paths and Dynamic Programming
Network Flow Problems
Totally Asynchronous Iterative Algorithms
Partially Asynchronous Iterative Methods
Organizing an Asynchronous Network of Processors for Distributed Computation
Partial Solutions Manual
Linear Algebra and Analysis
Probability Theory and Markov Chains