Handbook of Parallel Computing and Statistics

Erricos John Kontoghiorghes (Herausgeber)

Buch | Softcover

546 Seiten

2020
Chapman & Hall/CRC (Verlag)
978-0-367-57792-6 (ISBN)

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Technological improvements continue to push back the frontier of processor speed in modern computers. Unfortunately, the computational intensity demanded by modern research problems grows even faster. Parallel computing has emerged as the most successful bridge to this computational gap, and many popular solutions have emerged based on its concepts, such as grid computing and massively parallel supercomputers. The Handbook of Parallel Computing and Statistics systematically applies the principles of parallel computing for solving increasingly complex problems in statistics research.

This unique reference weaves together the principles and theoretical models of parallel computing with the design, analysis, and application of algorithms for solving statistical problems. After a brief introduction to parallel computing, the book explores the architecture, programming, and computational aspects of parallel processing. Focus then turns to optimization methods followed by statistical applications. These applications include algorithms for predictive modeling, adaptive design, real-time estimation of higher-order moments and cumulants, data mining, econometrics, and Bayesian computation. Expert contributors summarize recent results and explore new directions in these areas.

Its intricate combination of theory and practical applications makes the Handbook of Parallel Computing and Statistics an ideal companion for helping solve the abundance of computation-intensive statistical problems arising in a variety of fields.

Erricos John Kontoghiorghes

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.

Erscheinungsdatum	01.07.2020
Reihe/Serie	Statistics: A Series of Textbooks and Monographs
Sprache	englisch
Maße	178 x 254 mm
Gewicht	453 g
Themenwelt	Mathematik / Informatik ► Informatik ► Theorie / Studium
	Informatik ► Weitere Themen ► Hardware
	Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra
	Mathematik / Informatik ► Mathematik ► Statistik
ISBN-10	0-367-57792-5 / 0367577925
ISBN-13	978-0-367-57792-6 / 9780367577926
Zustand	Neuware