by Dimitri P. Bertsekas and John N. Tsitsiklis
Hardcover Edition (appeared in 2015)
Publication: 2015, 735 pages
Contents, Preface, Ordering, Home
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).
"This major contribution to the literature belongs on the bookshelf of
every scientist with an interest in computational science, directly beside
Knuth's three volumes and Numerical Recipes..."
Anna Nagurney, University of Massachusetts, in the International Journal of Supercomputer Applications
"This major work of exceptional scholarship summarizes more than
three decades of research into general-purpose
algorithms for solving systems of equations
and optimization problems."
W. F. Smyth, in Computing Reviews
"This book marks an important landmark in the theory of distributed
systems and I highly recommend it to students and practicing engineers
in the fields of operations research and computer science, as well
as to mathematicians interested in numerical methods."
Lorne G. Mason, in IEEE Communications Magazine
Among its special features, the book:
The authors are Professors of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology.