Parallel Computing In Optimization
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Author | : Yair Censor |
Publisher | : Oxford University Press, USA |
Total Pages | : 574 |
Release | : 1997 |
Genre | : Computers |
ISBN | : 9780195100624 |
This book offers a unique pathway to methods of parallel optimization by introducing parallel computing ideas into both optimization theory and into some numerical algorithms for large-scale optimization problems. The three parts of the book bring together relevant theory, careful study of algorithms, and modeling of significant real world problems such as image reconstruction, radiation therapy treatment planning, financial planning, transportation and multi-commodity network flow problems, planning under uncertainty, and matrix balancing problems.
Author | : Dimitri Bertsekas |
Publisher | : Athena Scientific |
Total Pages | : 832 |
Release | : 2015-03-01 |
Genre | : Mathematics |
ISBN | : 1886529159 |
This highly acclaimed work, first published by Prentice Hall in 1989, is a comprehensive and theoretically sound treatment of parallel and distributed numerical methods. It focuses on algorithms that are naturally suited for massive parallelization, and it explores the fundamental convergence, rate of convergence, communication, and synchronization issues associated with such algorithms. This is an extensive book, which aside from its focus on parallel and distributed algorithms, contains a wealth of material on a broad variety of computation and optimization topics. It is an excellent supplement to several of our other books, including Convex Optimization Algorithms (Athena Scientific, 2015), Nonlinear Programming (Athena Scientific, 1999), Dynamic Programming and Optimal Control (Athena Scientific, 2012), Neuro-Dynamic Programming (Athena Scientific, 1996), and Network Optimization (Athena Scientific, 1998). The on-line edition of the book contains a 95-page solutions manual.
Author | : El-Ghazali Talbi |
Publisher | : John Wiley & Sons |
Total Pages | : 348 |
Release | : 2006-10-27 |
Genre | : Computers |
ISBN | : 0470053917 |
This text provides an excellent balance of theory and application that enables you to deploy powerful algorithms, frameworks, and methodologies to solve complex optimization problems in a diverse range of industries. Each chapter is written by leading experts in the fields of parallel and distributed optimization. Collectively, the contributions serve as a complete reference to the field of combinatorial optimization, including details and findings of recent and ongoing investigations.
Author | : Michael Joseph Wolfe |
Publisher | : Addison Wesley |
Total Pages | : 600 |
Release | : 1996 |
Genre | : Computers |
ISBN | : |
Software -- Operating Systems.
Author | : Yoshiyasu Takefuji |
Publisher | : Springer Science & Business Media |
Total Pages | : 254 |
Release | : 1992-01-31 |
Genre | : Technology & Engineering |
ISBN | : 9780792391906 |
Neural Network Parallel Computing is the first book available to the professional market on neural network computing for optimization problems. This introductory book is not only for the novice reader, but for experts in a variety of areas including parallel computing, neural network computing, computer science, communications, graph theory, computer aided design for VLSI circuits, molecular biology, management science, and operations research. The goal of the book is to facilitate an understanding as to the uses of neural network models in real-world applications. Neural Network Parallel Computing presents a major breakthrough in science and a variety of engineering fields. The computational power of neural network computing is demonstrated by solving numerous problems such as N-queen, crossbar switch scheduling, four-coloring and k-colorability, graph planarization and channel routing, RNA secondary structure prediction, knight's tour, spare allocation, sorting and searching, and tiling. Neural Network Parallel Computing is an excellent reference for researchers in all areas covered by the book. Furthermore, the text may be used in a senior or graduate level course on the topic.
Author | : Kevin R. Wadleigh |
Publisher | : Prentice Hall Professional |
Total Pages | : 414 |
Release | : 2000 |
Genre | : Computers |
ISBN | : 9780130170088 |
The hands-on guide to high-performance coding and algorithm optimization. This hands-on guide to software optimization introduces state-of-the-art solutions for every key aspect of software performance - both code-based and algorithm-based. Two leading HP software performance experts offer comparative optimization strategies for RISC and for the new Explicitly Parallel Instruction Computing (EPIC) design used in Intel IA-64 processors. Using many practical examples, they offer specific techniques for: Predicting and measuring performance - and identifying your best optimization opportunities Storage optimization: cache, system memory, virtual memory, and I/0 Parallel processing: distributed-memory and shared-memory (SMP and ccNUMA) Compilers and loop optimization Enhancing parallelism: compiler directives, threads, and message passing Mathematical libraries and algorithms Whether you're a developer, ISV, or technical researcher, if you need to optimize high-performance software on today's leading processors, one book delivers the advanced techniques and code examples you need: Software Optimization for High Performance Computing.
Author | : Klaus Schittkowski |
Publisher | : Springer Science & Business Media |
Total Pages | : 455 |
Release | : 2013-06-29 |
Genre | : Mathematics |
ISBN | : 3642824501 |
This book contains the written versions of main lectures presented at the Advanced Study Institute (ASI) on Computational Mathematical Programming, which was held in Bad Windsheim, Germany F. R., from July 23 to August 2, 1984, under the sponsorship of NATO. The ASI was organized by the Committee on Algorithms (COAL) of the Mathematical Programming Society. Co-directors were Karla Hoffmann (National Bureau of Standards, Washington, U.S.A.) and Jan Teigen (Rabobank Nederland, Zeist, The Netherlands). Ninety participants coming from about 20 different countries attended the ASI and contributed their efforts to achieve a highly interesting and stimulating meeting. Since 1947 when the first linear programming technique was developed, the importance of optimization models and their mathematical solution methods has steadily increased, and now plays a leading role in applied research areas. The basic idea of optimization theory is to minimize (or maximize) a function of several variables subject to certain restrictions. This general mathematical concept covers a broad class of possible practical applications arising in mechanical, electrical, or chemical engineering, physics, economics, medicine, biology, etc. There are both industrial applications (e.g. design of mechanical structures, production plans) and applications in the natural, engineering, and social sciences (e.g. chemical equilibrium problems, christollography problems).
Author | : Michael A. Heroux |
Publisher | : SIAM |
Total Pages | : 421 |
Release | : 2006-01-01 |
Genre | : Computers |
ISBN | : 9780898718133 |
Parallel processing has been an enabling technology in scientific computing for more than 20 years. This book is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, computer scientists, and computational scientists focus on to make parallel processing effective for scientific problems. Presently, the impact of parallel processing on scientific computing varies greatly across disciplines, but it plays a vital role in most problem domains and is absolutely essential in many of them. Parallel Processing for Scientific Computing is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth provides a sampling of applications that require parallel computing for scaling to solve larger and realistic models that can advance science and engineering.
Author | : Vipin Kumar |
Publisher | : Addison Wesley Longman |
Total Pages | : 632 |
Release | : 1994 |
Genre | : Computers |
ISBN | : |
Mathematics of Computing -- Parallelism.
Author | : Roman G. Strongin |
Publisher | : Springer Science & Business Media |
Total Pages | : 717 |
Release | : 2013-11-09 |
Genre | : Mathematics |
ISBN | : 146154677X |
Everything should be made as simple as possible, but not simpler. (Albert Einstein, Readers Digest, 1977) The modern practice of creating technical systems and technological processes of high effi.ciency besides the employment of new principles, new materials, new physical effects and other new solutions ( which is very traditional and plays the key role in the selection of the general structure of the object to be designed) also includes the choice of the best combination for the set of parameters (geometrical sizes, electrical and strength characteristics, etc.) concretizing this general structure, because the Variation of these parameters ( with the structure or linkage being already set defined) can essentially affect the objective performance indexes. The mathematical tools for choosing these best combinations are exactly what is this book about. With the advent of computers and the computer-aided design the pro bations of the selected variants are usually performed not for the real examples ( this may require some very expensive building of sample op tions and of the special installations to test them ), but by the analysis of the corresponding mathematical models. The sophistication of the mathematical models for the objects to be designed, which is the natu ral consequence of the raising complexity of these objects, greatly com plicates the objective performance analysis. Today, the main (and very often the only) available instrument for such an analysis is computer aided simulation of an object's behavior, based on numerical experiments with its mathematical model.