Handbook of Parallel Computing and Statistics

Erricos John Kontoghiorghes

ISBN 10: 0367577925 / ISBN 13: 9780367577926

Published by Chapman And Hall/CRC, 2020

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - 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 t.

Seller Inventory # 9780367577926

Bibliographic Details

• Title: Handbook of Parallel Computing and Statistics
• Publisher: Chapman And Hall/CRC
• Publication Date: 2020
• Language: English
• ISBN 10: 0367577925
• ISBN 13: 9780367577926
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 254W x 178H x 29D millimeters 254 millimeters width by 178 millimeters height by 29 millimeters depth
• Weight: 1018 grams

About this title

Synopsis

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.

About the Author

Erricos John Kontoghiorghes