General – Parallel Computing. A Brief Introduction to Parallel Computing. Parallel Computer Architecture. Fortran and Java for High-Performance Computing. Parallel Algorithms for the Singular Value Decomposition. Iterative Methods for the Partial Eigensolution of Symmetric Matrices on Parallel Machines. Optimization. Parallel Optimization Methods. Parallel Computing in Global Optimization. Nonlinear Optimization: A Parallel Linear Algebra Standpoint. Statistical Applications. On Some Statistical Methods for Parallel Computation. Parallel Algorithms for Predictive Modeling. Parallel Programs for Adaptive Designs. A Modular VLSI Architecture for the Real-Time Estimation of Higher Order Moments and Cumulants. Principal Component Analysis for Information Retrieval. Matrix Rank Reduction for Data Analysis and Feature Extraction. Parallel Computation in Econometrics: A Simplified Approach. Parallel Bayesian Computation. Index.
Erricos John Kontoghiorghes
“… What this book brings is an excellent introduction into the
state of the art in parallel computers as it exists today. … This
book is an excellent summary of parallel computing as it exists
today. It would be of particular help to the person responsible for
writing the proposal for an organization to buy/build one. The book
is probably a bit too advanced for a course at an undergraduate
level, but would be excellent for first year graduate students in a
wide variety of fields from computer science to bio-informatics,
data mining, cryptography or any number of other fields requiring
heavy duty computation.”
— In Books-On-Line
“[The book’s] chapters cover reasonably well the different domains
where parallel computing is required and applied. The general
introduction is clear and sound. There is some overlapping in the
introduction of several chapters, which … makes the reading of a
particular chapter easier. Overall, the balance between general
introduction, problem-specific information, and applications is
well equilibrated.
…I am convinced that this handbook is of interest to a large
community of researchers, students, and practitioners (dealing with
computational methods in any domain) as the book covers a wide
range of applications where parallel computing is of great
actuality. The book will guide them in the analysis [of] whether a
particular computational problem is feasible for a parallelization
and if this is the case, help them to realize it. With respect to
this, the extensive bibliography included in the handbook is
particularly precious…”
—Manfred Gilli, Professor, Department of Econometrics, University
of Geneva, Switzerland
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