<p>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. Among its special features, the book: 1) Quantifies the performance of parallel algorithms, including the limitations imposed by the communication and synchronization penalties. 2) Describes communication algorithms for a variety of system architectures including tree, mesh, and hypercube. 3) Provides a comprehensive convergence analysis of asynchronous methods and a comparison with their asynchronous counterparts. 4) Covers direct and iterative algorithms for linear and nonlinear systems of equations and variational inequalities. 5) Describes optimization methods for nonlinear programming, shortest paths, dynamic programming, network flows, and large-scale decomposition. 6) Includes extensive research material on optimization methods, asynchronous algorithm convergence, rollback synchronization, asynchronous communication network protocols, and others. 7) Supplements the text material with many exercises, whose complete solutions are posted on the internet. 8) Contains a lot of material not found in any other book.</p>

Parallel and Distributed Computation: Numerical Methods

Computers & Technology

Tsitsiklis, John N.

Bertsekas, Dimitri

Programming

PRENTICE/HALL

<p>A uniquely pedagogical, insightful, and rigorous treatment of the analytical/geometrical foundations of optimization. Among its special features, the book: 1) Develops rigorously and comprehensively the theory of convex sets and functions 2) Provides a geometric, highly visual treatment of convex and nonconvex optimization problems, including existence of solutions, optimality conditions, Lagrange multipliers, and duality 3) Includes an insightful and comprehensive presentation of minimax theory and zero sum games, and its connection with duality 4) Describes dual optimization, the associated computational methods, including the novel incremental subgradient methods, and applications in linear, quadratic, and integer programming 5) Contains many examples, illustrations, and exercises with complete solutions (about 200 pages) posted on the internet.</p>

Convex Analysis and Optimization

Science & Math

Mathematics

Athena Scientific

See the best price to sell, buy, or rent books by Bertsekas, Dimitri. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Bertsekas, Dimitri