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| Author | : Alan George |
| Publisher | : Prentice Hall |
| Total Pages | : 346 |
| Release | : 1981 |
| Genre | : Mathematics |
| ISBN | : |
| Author | : Gerard Meurant |
| Publisher | : Elsevier |
| Total Pages | : 777 |
| Release | : 1999-06-16 |
| Genre | : Mathematics |
| ISBN | : 0080529518 |
This book deals with numerical methods for solving large sparse linear systems of equations, particularly those arising from the discretization of partial differential equations. It covers both direct and iterative methods. Direct methods which are considered are variants of Gaussian elimination and fast solvers for separable partial differential equations in rectangular domains. The book reviews the classical iterative methods like Jacobi, Gauss-Seidel and alternating directions algorithms. A particular emphasis is put on the conjugate gradient as well as conjugate gradient -like methods for non symmetric problems. Most efficient preconditioners used to speed up convergence are studied. A chapter is devoted to the multigrid method and the book ends with domain decomposition algorithms that are well suited for solving linear systems on parallel computers.
| Author | : Yousef Saad |
| Publisher | : SIAM |
| Total Pages | : 537 |
| Release | : 2003-04-01 |
| Genre | : Mathematics |
| ISBN | : 0898715342 |
Mathematics of Computing -- General.
| Author | : Timothy A. Davis |
| Publisher | : SIAM |
| Total Pages | : 228 |
| Release | : 2006-09-01 |
| Genre | : Computers |
| ISBN | : 0898716136 |
The sparse backslash book. Everything you wanted to know but never dared to ask about modern direct linear solvers. Chen Greif, Assistant Professor, Department of Computer Science, University of British Columbia.Overall, the book is magnificent. It fills a long-felt need for an accessible textbook on modern sparse direct methods. Its choice of scope is excellent John Gilbert, Professor, Department of Computer Science, University of California, Santa Barbara.Computational scientists often encounter problems requiring the solution of sparse systems of linear equations. Attacking these problems efficiently requires an in-depth knowledge of the underlying theory, algorithms, and data structures found in sparse matrix software libraries. Here, Davis presents the fundamentals of sparse matrix algorithms to provide the requisite background. The book includes CSparse, a concise downloadable sparse matrix package that illustrates the algorithms and theorems presented in the book and equips readers with the tools necessary to understand larger and more complex software packages.With a strong emphasis on MATLAB and the C programming language, Direct Methods for Sparse Linear Systems equips readers with the working knowledge required to use sparse solver packages and write code to interface applications to those packages. The book also explains how MATLAB performs its sparse matrix computations.Audience This invaluable book is essential to computational scientists and software developers who want to understand the theory and algorithms behind modern techniques used to solve large sparse linear systems. The book also serves as an excellent practical resource for students with an interest in combinatorial scientific computing.Preface; Chapter 1: Introduction; Chapter 2: Basic algorithms; Chapter 3: Solving triangular systems; Chapter 4: Cholesky factorization; Chapter 5: Orthogonal methods; Chapter 6: LU factorization; Chapter 7: Fill-reducing orderings; Chapter 8: Solving sparse linear systems; Chapter 9: CSparse; Chapter 10: Sparse matrices in MATLAB; Appendix: Basics of the C programming language; Bibliography; Index.
| Author | : Jonathan Schaeffer |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 450 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1461556112 |
Major advances in computing are occurring at an ever-increasing pace. This is especially so in the area of high performance computing (HPC), where today's supercomputer is tomorrow's workstation. High Performance Computing Systems and Applications is a record of HPCS'98, the 12th annual Symposium on High Performance Computing Systems and Applications. The quality of the conference was significantly enhanced by the high proportion of keynote and invited speakers. This book presents the latest research in HPC architecture, networking, applications and tools. Of special note are the sections on computational biology and physics. High Performance Computing Systems and Applications is suitable as a secondary text for a graduate-level course on computer architecture and networking, and as a reference for researchers and practitioners in industry.
| Author | : Renchang Dai |
| Publisher | : John Wiley & Sons |
| Total Pages | : 516 |
| Release | : 2023-10-17 |
| Genre | : Technology & Engineering |
| ISBN | : 1119903866 |
Graph Database and Graph Computing for Power System Analysis Understand a new way to model power systems with this comprehensive and practical guide Graph databases have become one of the essential tools for managing large data systems. Their structure improves over traditional table-based relational databases in that it reconciles more closely to the inherent physics of a power system, enabling it to model the components and the network of a power system in an organic way. The authors’ pioneering research has demonstrated the effectiveness and the potential of graph data management and graph computing to transform power system analysis. Graph Database and Graph Computing for Power System Analysis presents a comprehensive and accessible introduction to this research and its emerging applications. Programs and applications conventionally modeled for traditional relational databases are reconceived here to incorporate graph computing. The result is a detailed guide which demonstrates the utility and flexibility of this cutting-edge technology. The book’s readers will also find: Design configurations for a graph-based program to solve linear equations, differential equations, optimization problems, and more Detailed demonstrations of graph-based topology analysis, state estimation, power flow analysis, security-constrained economic dispatch, automatic generation control, small-signal stability, transient stability, and other concepts, analysis, and applications An authorial team with decades of experience in software design and power systems analysis Graph Database and Graph Computing for Power System Analysis is essential for researchers and academics in power systems analysis and energy-related fields, as well as for advanced graduate students looking to understand this particular set of technologies.
| Author | : S.A. Soman |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 349 |
| Release | : 2012-12-06 |
| Genre | : Technology & Engineering |
| ISBN | : 1461508231 |
Computational methods in Power Systems require significant inputs from diverse disciplines, such as data base structures, numerical analysis etc. Strategic decisions in sparsity exploitation and algorithm design influence large-scale simulation and high-speed computations. Selection of programming paradigm shapes the design, its modularity and reusability. This has a far reaching effect on software maintenance. Computational Methods for Large Sparse Power Systems Analysis: An Object Oriented Approach provides a unified object oriented (OO) treatment for power system analysis. Sparsity exploitation techniques in OO paradigm are emphasized to facilitate large scale and fast computing. Specific applications like large-scale load flow, short circuit analysis, state estimation and optimal power flow are discussed within this framework. A chapter on modeling and computational issues in power system dynamics is also included. Motivational examples and illustrations are included throughout the book. A library of C++ classes provided along with this book has classes for transmission lines, transformers, substation etc. A CD-ROM with C++ programs is also included. It contains load flow, short circuit analysis and network topology processor applications. Power system data is provided and systems up to 150 buses can be studied. Other Special Features: This book is the first of its kind, covering power system applications designed with an OO perspective. Chapters on object orientation for modeling of power system computations, data structure, large sparse linear system solver, sparse QR decomposition in an OO framework are special features of this book.
| Author | : Daniele Bertaccini |
| Publisher | : CRC Press |
| Total Pages | : 375 |
| Release | : 2018-02-19 |
| Genre | : Mathematics |
| ISBN | : 1498764177 |
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate preconditioning techniques for some of the most important classes of large and sparse linear systems. The solution of large and sparse linear systems is the most time-consuming part for most of the scientific computing simulations. Indeed, mathematical models become more and more accurate by including a greater volume of data, but this requires the solution of larger and harder algebraic systems. In recent years, research has focused on the efficient solution of large sparse and/or structured systems generated by the discretization of numerical models by using iterative solvers.
| Author | : Menezes |
| Publisher | : |
| Total Pages | : 664 |
| Release | : 2014-01-15 |
| Genre | : |
| ISBN | : 9783662197080 |
| Author | : David M. Young |
| Publisher | : Elsevier |
| Total Pages | : 599 |
| Release | : 2014-05-10 |
| Genre | : Mathematics |
| ISBN | : 1483274136 |
Iterative Solution of Large Linear Systems describes the systematic development of a substantial portion of the theory of iterative methods for solving large linear systems, with emphasis on practical techniques. The focal point of the book is an analysis of the convergence properties of the successive overrelaxation (SOR) method as applied to a linear system where the matrix is "consistently ordered". Comprised of 18 chapters, this volume begins by showing how the solution of a certain partial differential equation by finite difference methods leads to a large linear system with a sparse matrix. The next chapter reviews matrix theory and the properties of matrices, as well as several theorems of matrix theory without proof. A number of iterative methods, including the SOR method, are then considered. Convergence theorems are also given for various iterative methods under certain assumptions on the matrix A of the system. Subsequent chapters deal with the eigenvalues of the SOR method for consistently ordered matrices; the optimum relaxation factor; nonstationary linear iterative methods; and semi-iterative methods. This book will be of interest to students and practitioners in the fields of computer science and applied mathematics.
