Chapter: Ch. 7. Parallel computing in global optimization

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Home > Handbook of parallel computing and statistics / > Ch. 7. Parallel computing in global optimization

Handbook of parallel computing and statistics / |

Kontoghiorghes, Erricos John.

Chapman & Hall/CRC,

Handbook of parallel computing and statistics /

Ch. 7. Parallel computing in global optimization

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1674942401997_51372836

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Chapters/Headings	Author(s)	Pages	Info
Ch. 1. A brief introduction to parallel computing	Marcin Paprzycki and Przemyslaw Stpiczynski
Ch. 2. Parallel computer architecture	Pedro Trancoso and Paraskevas Evripidou
Ch. 3. Fortran and Java for high-performance computing	R. Perrott, C. Phillips and T. Stitt
Ch. 4. Parallel algorithms for the singular value decomposition	Michael W. Berry, Dani Mezher, Bernard Phillipe and Ahmed Sameh
Ch. 5. Iterative methods for the partial eigensolution of symmetric matrices on parallel machines	Maurice Clint
Ch. 6. Parallel optimization methods	Yair Censor and Stavros A. Zenios
Ch. 7. Parallel computing in global optimization	Marco D'Apuzzo, Marina Marino, Athanasios Migdalas, Panos M. Pardalos and Gerardo Toraldo
Ch. 8. Nonlinear optimization: a parallel linear algebra standpoint	Marco D'Apuzzo, Marina Marino, Athanasios Migdalas, Panos M. Pardalos and Gerardo Toraldo
Ch. 9. On some statistical methods for parallel computation	Edward J. Wegman
Ch. 10. Parallel algorithms for predictive modeling	Markus Hegland
Ch. 11. Parallel programs for adaptive designs	Quentin F. Stout and Janis Hardwick
Ch. 12. A modular VLSI architecture for the real-time estimation of higher order moments and cumulants	Elias S. Manolakos
Ch. 13. Principal component analysis for information retrieval	Michael W. Berry and Dian I. Martin
Ch. 14. Matrix rank reduction for data analysis and feature extraction	Haesun Park and Lars Elden
Ch. 15. Parallel computation in econometrics: a simplified approach	Jurgen A. Doornik, Neil Shephard and David F. Hendry
Ch. 16. Parallel Bayesian computation	Darren J. Wilkinson.
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