Parallel Algorithms for Linear Models

Parallel Algorithms for Linear Models

Author: Erricos Kontoghiorghes

Publisher: Springer Science & Business Media

Published: 2000-01-31

Total Pages: 216

ISBN-13: 9780792377207

DOWNLOAD EBOOK

Parallel Algorithms for Linear Models provides a complete and detailed account of the design, analysis and implementation of parallel algorithms for solving large-scale linear models. It investigates and presents efficient, numerically stable algorithms for computing the least-squares estimators and other quantities of interest on massively parallel systems. The monograph is in two parts. The first part consists of four chapters and deals with the computational aspects for solving linear models that have applicability in diverse areas. The remaining two chapters form the second part, which concentrates on numerical and computational methods for solving various problems associated with seemingly unrelated regression equations (SURE) and simultaneous equations models. The practical issues of the parallel algorithms and the theoretical aspects of the numerical methods will be of interest to a broad range of researchers working in the areas of numerical and computational methods in statistics and econometrics, parallel numerical algorithms, parallel computing and numerical linear algebra. The aim of this monograph is to promote research in the interface of econometrics, computational statistics, numerical linear algebra and parallelism.


Parallel Algorithms for Regular Architectures

Parallel Algorithms for Regular Architectures

Author: Russ Miller

Publisher: MIT Press

Published: 1996

Total Pages: 336

ISBN-13: 9780262132336

DOWNLOAD EBOOK

Parallel-Algorithms for Regular Architectures is the first book to concentrate exclusively on algorithms and paradigms for programming parallel computers such as the hypercube, mesh, pyramid, and mesh-of-trees.


Handbook of Parallel Computing and Statistics

Handbook of Parallel Computing and Statistics

Author: Erricos John Kontoghiorghes

Publisher: CRC Press

Published: 2005-12-21

Total Pages: 560

ISBN-13: 9781420028683

DOWNLOAD EBOOK

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


Parallel Algorithms for Linear Models

Parallel Algorithms for Linear Models

Author: Erricos Kontoghiorghes

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 196

ISBN-13: 1461545714

DOWNLOAD EBOOK

Parallel Algorithms for Linear Models provides a complete and detailed account of the design, analysis and implementation of parallel algorithms for solving large-scale linear models. It investigates and presents efficient, numerically stable algorithms for computing the least-squares estimators and other quantities of interest on massively parallel systems. The monograph is in two parts. The first part consists of four chapters and deals with the computational aspects for solving linear models that have applicability in diverse areas. The remaining two chapters form the second part, which concentrates on numerical and computational methods for solving various problems associated with seemingly unrelated regression equations (SURE) and simultaneous equations models. The practical issues of the parallel algorithms and the theoretical aspects of the numerical methods will be of interest to a broad range of researchers working in the areas of numerical and computational methods in statistics and econometrics, parallel numerical algorithms, parallel computing and numerical linear algebra. The aim of this monograph is to promote research in the interface of econometrics, computational statistics, numerical linear algebra and parallelism.


Computational Methods in Decision-Making, Economics and Finance

Computational Methods in Decision-Making, Economics and Finance

Author: Erricos John Kontoghiorghes

Publisher: Springer Science & Business Media

Published: 2002-08-31

Total Pages: 656

ISBN-13: 9781402008399

DOWNLOAD EBOOK

Computing has become essential for the modeling, analysis, and optimization of systems. This book is devoted to algorithms, computational analysis, and decision models. The chapters are organized in two parts: optimization models of decisions and models of pricing and equilibria. Optimization is at the core of rational decision making. Even when the decision maker has more than one goal or there is significant uncertainty in the system, optimization provides a rational framework for efficient decisions. The Markowitz mean-variance formulation is a classical example. The first part of the book is on recent developments in optimization decision models for finance and economics. The first four chapters of this part focus directly on multi-stage problems in finance. Chapters 5-8 involve the use of worst-case robust analysis. Chapters 9-11 are devoted to portfolio optimization. The final four chapters are on transportation-inventory with stochastic demand; optimal investment with CRRA utility; hedging financial contracts; and, automatic differentiation for computational finance. The uncertainty associated with prediction and modeling constantly requires the development of improved methods and models. Similarly, as systems strive towards equilibria, the characterization and computation of equilibria assists analysis and prediction. The second part of the book is devoted to recent research in computational tools and models of equilibria, prediction, and pricing. The first three chapters of this part consider hedging issues in finance. Chapters 19-22 consider prediction and modeling methodologies. Chapters 23-26 focus on auctions and equilibria. Volatility models are investigated in chapters 27-28. The final two chapters investigate risk assessment and product pricing. Audience: Researchers working in computational issues related to economics, finance, and management science.


Parallel Algorithms and Cluster Computing

Parallel Algorithms and Cluster Computing

Author: Karl Heinz Hoffmann

Publisher: Springer Science & Business Media

Published: 2007-06-24

Total Pages: 365

ISBN-13: 3540335412

DOWNLOAD EBOOK

This book presents advances in high performance computing as well as advances accomplished using high performance computing. It contains a collection of papers presenting results achieved in the collaboration of scientists from computer science, mathematics, physics, and mechanical engineering. From science problems to mathematical algorithms and on to the effective implementation of these algorithms on massively parallel and cluster computers, the book presents state-of-the-art methods and technology, and exemplary results in these fields.


COMPSTAT

COMPSTAT

Author: Albert Prat

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 509

ISBN-13: 3642469922

DOWNLOAD EBOOK

COMPSTAT symposia have been held regularly since 1974 when they started in Vienna. This tradition has made COMPSTAT a major forum for the interplay of statistics and computer sciences with contributions from many well known scientists all over the world. The scientific programme of COMPSTAT '96 covers all aspects of this interplay, from user-experiences and evaluation of software through the development and implementation of new statistical ideas. All papers presented belong to one of the three following categories: - Statistical methods (preferable new ones) that require a substantial use of computing; - Computer environments, tools and software useful in statistics; - Applications of computational statistics in areas of substantial interest (environment, health, industry, biometrics, etc.).


Parallel Algorithms

Parallel Algorithms

Author: Henri Casanova

Publisher: CRC Press

Published: 2008-07-17

Total Pages: 360

ISBN-13: 1584889462

DOWNLOAD EBOOK

Focusing on algorithms for distributed-memory parallel architectures, Parallel Algorithms presents a rigorous yet accessible treatment of theoretical models of parallel computation, parallel algorithm design for homogeneous and heterogeneous platforms, complexity and performance analysis, and essential notions of scheduling. The book extract