Parallel Processing Computers Books - Page 14

Handbook of Parallel Computing and Statistics (Statistics, Textbooks and Monographs)

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Total reviews: 2 Average rating: 4.5 of 5

Editorial Review:

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.

Explorations in Parallel Distributed Processing - IBM version (Bradford Books)

James L. McClelland, David E. Rumelhart

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Editorial Review:

Includes two 5 1/4" DS/DD diskettes for IBM PCs and compatibles

IBM Certification Study Guide P5 And Pseries Administration And Support for Aix 5l Version 5.3

IBM Redbooks

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Numerical Integration: on Advanced Computer Systems (Lecture Notes in Computer Science)

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This monograph is a comprehensive treatment of the theoretical and computational aspects of numerical integration.
The authors give a unique overview of the topic by bringing into line many recent research results not yet presented coherently; the extensive bibliography lists 268 items. Particular emphasis is given to the potential parallelism of numerical integration problems and to utilizing it by means of dynamic load distribution techniques. The book discusses the basics and provides methodologies for producing efficient and reliable software for numerical integration on advanced computer systems. The book addresses researchers, graduate students, and computational scientists.

Handbook of CNN Image Processing: All You Need to Know about Cellular Neural Networks (YangSky.com Monographs in Information Sciences)

Tao Yang

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Cellular neural networks (CNN) were invented by Chua and Yang in 1988 in the Department of Electrical Engineering and Computer Sciences, University of California at Berkeley. Since then, CNN has become an extremely active field of researches to massive parallel computation, cellular automata, image processing, visual VLSI chips and vision processors. Written by one of the leading figures in the field, this is a lucid and comprehensive reference book for professionals, academic researchers and students. It covers almost all aspects of CNN including: local rules principles, structure and parameter design, continuous-time CNN, discrete-time CNN, and multi-stage CNN. Also, a systematic classification system of different CNN image operations is presented based on major local rule classes. Hundreds of CNN image operations together with their design processes were presented. The difference and equivalence between continuous-time and discrete-time CNN were formally formulated. The Generalization Principle and newly found Selected and Inverse Selected Principle make it painless to derive tens of CNN operators from a known one. 124 black-and-white figures were used to illustrate the functions of CNN image operators. Many CNN and DTCNN image operations were first time reported to the public, for example, negative CNN classes, selected CNN classes, inverse selected CNN classes, logic-morphologic CNN classes and many more. An extremely detailed index could be used as a fast and efficient looking-up table of hundreds of CNN operators.

Concurrency: State Models & Java Programs

Jeff Magee, Jeff Kramer

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Total reviews: 5 Average rating: 4.0 of 5

This is could be a classic CS book 5 out of 5 stars.
35 of 35 people found this review helpful.

This book does not belong with other Java books. This is a real computer science textbook that should be sitting next to Rivest's Algorithms book. The use of Java is incidental and makes the book very accessible without detracting from the issues at hand. It has to be one of the most well conceived computer science books ever written.

The material covered is maddeningly difficult to master informally because concurrency errors often manifest themselves as rare, random, and disastrous events that cannot be reproduced. Most of the book is laying down a solid formal foundation in which to reason about concurrency; the only hope for getting it right when things are difficult. It also comes with analysis tools (in Java of course!) to help people who learn by exploration, experimentation, and visualisation.

Editorial Review:

Concurrency is an area of software design that is vital in a wide range of applications where responsiveness are issues. They are especially important in the development of control systems. By their nature, concurrent programs are more complex, and therefore more difficult to reason than sequential programs. In order to ensure a thorough understanding of concurrency, concepts, techniques and problems are presented in many forms, through informal descriptions and illustrative examples, abstractly in models, and concretely in Java.

Parallel Computing: Principles and Practice

T. J. Fountain

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This book sets out the principles of parallel computing, explaining why, where, and how parallel computing is used. It is unique in its coverage of both conventional and neural computing (which act in ways similar to human brains), and also covers such topics as the fundamental paradigms employed in the field, how systems are programmed or trained, technical aspects including connectivity and processing element complexity, and how system performance is estimated (and why doing so is difficult). The penultimate chapter comprises a set of case studies of archetypal parallel computers, each study written by an individual closely connected with the system in question. The final chapter correlates the various aspects of parallel computing into a taxonomy of systems.

Concurrent Programming in ML

John H. Reppy

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Buy this book! 5 out of 5 stars.
9 of 9 people found this review helpful.

This is a book on Concurrent ML by the man who invented it. With so little CML information available on the web, this book has been one of the best investments I've made in years. Reppy starts off with a review of concurrency theory and then illustrates programming in CML through big, real-world examples. Throughout the book, he explains the motivation behind his design decisions. You end up with a clear picture of concurrent programming in a functional language -- concurrent programming in a REAL language like ML ...

Editorial Review:

Concurrent Programming ML (CML), included as part of the SML of New Jersey (SML/NJ) distribution, combines the best features of concurrent programming and functional programming. This practical, "how-to" book focuses on the use of concurrency to implement naturally concurrent applications. In addition to a tutorial introduction to programming in CML, the book presents three extended examples using CML for practical systems programming: a parallel software build system, a simple concurrent window manager, and an implementation of distributed tuple spaces. This book also illustrates advanced SML programming techniques, and includes a chapter on the implementation of concurrency using features provided by the SML/NJ system. It will be of interest to programmers, students, and professional researchers working in computer language development.

Numerical Linear Algebra on High-Performance Computers (Software, Environments and Tools)

Jack J. Dongarra, Iain S. Duff, Danny C. Sorensen, Hank A. van der Vorst

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Editorial Review:

This book presents a unified treatment of recently developed techniques and current understanding about solving systems of linear equations and large scale eigenvalue problems on high-performance computers. It provides a rapid introduction to the world of vector and parallel processing for these linear algebra applications. Topics include major elements of advanced-architecture computers and their performance, recent algorithmic development, and software for direct solution of dense matrix problems, direct solution of sparse systems of equations, iterative solution of sparse systems of equations, and solution of large sparse eigenvalue problems. This book supercedes the SIAM publication Solving Linear Systems on Vector and Shared Memory Computers, which appeared in 1990. The new book includes a considerable amount of new material in addition to incorporating a substantial revision of existing text.

Synchronization of Parallel Programmes (Studies in Computer Science)

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The use of modular and parallel programming languages, and the development of distributed architectures is having a profound influence on computer programming and systems design; hardware and performance can now conspire to produce much higher operating speeds than could previously be achieved through sequential processing. Executing cooperating, concurrent processes demands that new specification and implementation techniques be developed.

This book proposes a method for expressing typical cooperation and competition problems, as well as different synchronization and communication methods for implementing them. Using a general abstract expression to state synchronization constraints between parallel processes, the authors then choose either a centralized or a distributed implementation as a solution for the targeted system. Each of these implementations is illustrated with examples drawn from classic problems, and one informal case study (management of access to a swimming pool) acts as a leitmotif throughout the work, providing comparisons between the various approaches offered.

Contents: Introduction-the problem and an example; Languages for the expression of synchronization problems; Tools and methods for centralized implementation; Tools and methods for distributed implementation.

Jacque Andre, Daniel Herman, and Jean-Pierre Verjus are staff researchers at IRISA, INSA, and the University of Rennes in France. Synchronization of Parallel Programs is included in the Scientific Computation Series, edited by Dennis Gannon.