Numerical Linear Algebra for High-performance Computers PDF Download
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Author: Jack J. Dongarra
Publisher: SIAM
ISBN: 9780898719611
Category : Computers
Languages : en
Pages : 360
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Book Description
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.
Author: Jack J. Dongarra
Publisher: SIAM
ISBN: 0898714281
Category : Computers
Languages : en
Pages : 353
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Book Description
Provides a rapid introduction to the world of vector and parallel processing for these linear algebra applications.
Author: J. J. Dongarra
Publisher: Society for Industrial and Applied Mathematics (SIAM)
ISBN:
Category : Computers
Languages : en
Pages : 274
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Book Description
Mathematics of Computing -- Parallelism.
Author: Jack J. Dongarra
Publisher: SIAM
ISBN: 9780898719611
Category : Computers
Languages : en
Pages : 360
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Book Description
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.
Author: Victor Eijkhout
Publisher: Lulu.com
ISBN: 1257992546
Category : Computers
Languages : en
Pages : 536
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Book Description
This is a textbook that teaches the bridging topics between numerical analysis, parallel computing, code performance, large scale applications.
Author: James W. Demmel
Publisher: SIAM
ISBN: 0898713897
Category : Mathematics
Languages : en
Pages : 426
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Book Description
This comprehensive textbook is designed for first-year graduate students from a variety of engineering and scientific disciplines.
Author: Denis Caromel
Publisher: Springer
ISBN: 9783540653875
Category : Computers
Languages : en
Pages : 242
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Book Description
This volume contains the Proceedings of the International Symposium on C- puting in Object-Oriented Parallel Environments (ISCOPE ’98), held at Santa 1 Fe, New Mexico, USA on December 8{11, 1998. ISCOPE is in its second year, and continues to grow both in attendance and in the diversity of the subjects covered. ISCOPE’97 and its predecessor conferences focused more narrowly on scienti c computing in the high-performance arena. ISCOPE ’98 retains this emphasis, but has broadened to include discrete-event simulation, mobile c- puting, and web-based metacomputing. The ISCOPE ’98 Program Committee received 39 submissions, and acc- ted 10 (26%) as Regular Papers, based on their excellent content, maturity of development, and likelihood for widespread interest. These 10 are divided into three technical categories. Applications: The rst paper describes an approach to simulating advanced nuclear power reactor designs that incorporates multiple local solution - thods and a natural extension to parallel execution. The second paper disc- ses a Time Warp simulation kernel that is highly con gurable and portable. The third gives an account of the development of software for simulating high-intensity charged particle beams in linear particle accelerators, based on the POOMA framework, that shows performance considerably better than an HPF version, along with good parallel speedup.
Author: Justin Solomon
Publisher: CRC Press
ISBN: 1482251892
Category : Computers
Languages : en
Pages : 400
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Book Description
Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic desig
Author: Bo Kagström
Publisher: Springer
ISBN: 3540757554
Category : Computers
Languages : en
Pages : 1218
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Book Description
This book constitutes the thoroughly refereed post-proceedings of the 8th International Workshop on Applied Parallel Computing, PARA 2006. It covers partial differential equations, parallel scientific computing algorithms, linear algebra, simulation environments, algorithms and applications for blue gene/L, scientific computing tools and applications, parallel search algorithms, peer-to-peer computing, mobility and security, algorithms for single-chip multiprocessors.
Author: Ed Bueler
Publisher: SIAM
ISBN: 1611976316
Category : Mathematics
Languages : en
Pages : 407
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Book Description
The Portable, Extensible Toolkit for Scientific Computation (PETSc) is an open-source library of advanced data structures and methods for solving linear and nonlinear equations and for managing discretizations. This book uses these modern numerical tools to demonstrate how to solve nonlinear partial differential equations (PDEs) in parallel. It starts from key mathematical concepts, such as Krylov space methods, preconditioning, multigrid, and Newton’s method. In PETSc these components are composed at run time into fast solvers. Discretizations are introduced from the beginning, with an emphasis on finite difference and finite element methodologies. The example C programs of the first 12 chapters, listed on the inside front cover, solve (mostly) elliptic and parabolic PDE problems. Discretization leads to large, sparse, and generally nonlinear systems of algebraic equations. For such problems, mathematical solver concepts are explained and illustrated through the examples, with sufficient context to speed further development. PETSc for Partial Differential Equations addresses both discretizations and fast solvers for PDEs, emphasizing practice more than theory. Well-structured examples lead to run-time choices that result in high solver performance and parallel scalability. The last two chapters build on the reader’s understanding of fast solver concepts when applying the Firedrake Python finite element solver library. This textbook, the first to cover PETSc programming for nonlinear PDEs, provides an on-ramp for graduate students and researchers to a major area of high-performance computing for science and engineering. It is suitable as a supplement for courses in scientific computing or numerical methods for differential equations.
Author: Daniel J. Bates
Publisher: SIAM
ISBN: 1611972701
Category : Science
Languages : en
Pages : 372
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Book Description
This book is a guide to concepts and practice in numerical algebraic geometry ? the solution of systems of polynomial equations by numerical methods. Through numerous examples, the authors show how to apply the well-received and widely used open-source Bertini software package to compute solutions, including a detailed manual on syntax and usage options. The authors also maintain a complementary web page where readers can find supplementary materials and Bertini input files. Numerically Solving Polynomial Systems with Bertini approaches numerical algebraic geometry from a user's point of view with numerous examples of how Bertini is applicable to polynomial systems. It treats the fundamental task of solving a given polynomial system and describes the latest advances in the field, including algorithms for intersecting and projecting algebraic sets, methods for treating singular sets, the nascent field of real numerical algebraic geometry, and applications to large polynomial systems arising from differential equations. Those who wish to solve polynomial systems can start gently by finding isolated solutions to small systems, advance rapidly to using algorithms for finding positive-dimensional solution sets (curves, surfaces, etc.), and learn how to use parallel computers on large problems. These techniques are of interest to engineers and scientists in fields where polynomial equations arise, including robotics, control theory, economics, physics, numerical PDEs, and computational chemistry.
