Domain Decomposition

Domain Decomposition PDF Author: Barry Smith
Publisher: Cambridge University Press
ISBN: 9780521602860
Category : Computers
Languages : en
Pages : 244

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Book Description
Presents an easy-to-read discussion of domain decomposition algorithms, their implementation and analysis. Ideal for graduate students about to embark on a career in computational science. It will also be a valuable resource for all those interested in parallel computing and numerical computational methods.

Domain Decomposition

Domain Decomposition PDF Author: Barry Smith
Publisher: Cambridge University Press
ISBN: 9780521602860
Category : Computers
Languages : en
Pages : 244

Get Book Here

Book Description
Presents an easy-to-read discussion of domain decomposition algorithms, their implementation and analysis. Ideal for graduate students about to embark on a career in computational science. It will also be a valuable resource for all those interested in parallel computing and numerical computational methods.

Parallel Multilevel Methods

Parallel Multilevel Methods PDF Author: Gerhard Zumbusch
Publisher:
ISBN: 9783322800640
Category :
Languages : en
Pages : 220

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Book Description


Parallel Multilevel Methods

Parallel Multilevel Methods PDF Author: Gerhard Zumbusch
Publisher: Springer Science & Business Media
ISBN: 3322800636
Category : Mathematics
Languages : en
Pages : 215

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Book Description
Main aspects of the efficient treatment of partial differential equations are discretisation, multilevel/multigrid solution and parallelisation. These distinct topics are covered from the historical background to modern developments. It is demonstrated how the ingredients can be put together to give an adaptive and parallel multilevel approach for the solution of elliptic boundary value problems. Error estimators and adaptive grid refinement techniques for ordinary and for sparse grid discretisations are presented. Different types of additive and multiplicative multilevel solvers are discussed with respect to parallel implementation and application to adaptive refined grids. Efficiency issues are treated both for the sequential multilevel methods and for the parallel version by hash table storage techniques. Finally, space-filling curve enumeration for parallel load balancing and processor cache efficiency are discussed.

Adaptive Parallel Multilevel Methods for Partial Differential Equations

Adaptive Parallel Multilevel Methods for Partial Differential Equations PDF Author: Gerhard Zumbusch
Publisher:
ISBN:
Category :
Languages : en
Pages : 205

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Book Description


Parallel Multilevel Methods for Transport Equations

Parallel Multilevel Methods for Transport Equations PDF Author: Suely Oliveira
Publisher:
ISBN:
Category : Computer algorithms
Languages : en
Pages : 224

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Book Description


A Parallel Multilevel Partition of Unity Method for Elliptic Partial Differential Equations

A Parallel Multilevel Partition of Unity Method for Elliptic Partial Differential Equations PDF Author: Marc Alexander Schweitzer
Publisher: Springer Science & Business Media
ISBN: 3642593259
Category : Mathematics
Languages : en
Pages : 197

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Book Description
the solution or its gradient. These new discretization techniques are promising approaches to overcome the severe problem of mesh-generation. Furthermore, the easy coupling of meshfree discretizations of continuous phenomena to dis crete particle models and the straightforward Lagrangian treatment of PDEs via these techniques make them very interesting from a practical as well as a theoretical point of view. Generally speaking, there are two different types of meshfree approaches; first, the classical particle methods [104, 105, 107, 108] and second, meshfree discretizations based on data fitting techniques [13, 39]. Traditional parti cle methods stem from physics applications like Boltzmann equations [3, 50] and are also of great interest in the mathematical modeling community since many applications nowadays require the use of molecular and atomistic mod els (for instance in semi-conductor design). Note however that these methods are Lagrangian methods; i. e. , they are based On a time-dependent formulation or conservation law and can be applied only within this context. In a particle method we use a discrete set of points to discretize the domain of interest and the solution at a certain time. The PDE is then transformed into equa tions of motion for the discrete particles such that the particles can be moved via these equations. After time discretization of the equations of motion we obtain a certain particle distribution for every time step.

A Review of Numerous Parallel Multigrid Methods

A Review of Numerous Parallel Multigrid Methods PDF Author: International Business Machines Corporation. Research Division
Publisher:
ISBN:
Category : Multigrid methods (Numerical analysis)
Languages : en
Pages : 40

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Book Description
Abstract: "Parallel multilevel methods are shown to be the natural precursors to standard multilevel methods based on the personnel computing era of earlier this century. They are also the natural successors to standard multilevel methods in the age of computers. What makes six parallel multilevel methods practical and impractical is discussed in the context of the three algorithms that encapsulate them."

Parallel multilevel iterative methods

Parallel multilevel iterative methods PDF Author: Bi Roubolo Vona
Publisher:
ISBN:
Category : Multigrid methods (Numerical analysis)
Languages : en
Pages : 568

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Book Description


Numerical Solution of Partial Differential Equations on Parallel Computers

Numerical Solution of Partial Differential Equations on Parallel Computers PDF Author: Are Magnus Bruaset
Publisher: Springer Science & Business Media
ISBN: 3540316191
Category : Mathematics
Languages : en
Pages : 491

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Book Description
Since the dawn of computing, the quest for a better understanding of Nature has been a driving force for technological development. Groundbreaking achievements by great scientists have paved the way from the abacus to the supercomputing power of today. When trying to replicate Nature in the computer’s silicon test tube, there is need for precise and computable process descriptions. The scienti?c ?elds of Ma- ematics and Physics provide a powerful vehicle for such descriptions in terms of Partial Differential Equations (PDEs). Formulated as such equations, physical laws can become subject to computational and analytical studies. In the computational setting, the equations can be discreti ed for ef?cient solution on a computer, leading to valuable tools for simulation of natural and man-made processes. Numerical so- tion of PDE-based mathematical models has been an important research topic over centuries, and will remain so for centuries to come. In the context of computer-based simulations, the quality of the computed results is directly connected to the model’s complexity and the number of data points used for the computations. Therefore, computational scientists tend to ?ll even the largest and most powerful computers they can get access to, either by increasing the si e of the data sets, or by introducing new model terms that make the simulations more realistic, or a combination of both. Today, many important simulation problems can not be solved by one single computer, but calls for parallel computing.

The SAGE Handbook of Multilevel Modeling

The SAGE Handbook of Multilevel Modeling PDF Author: Marc A. Scott
Publisher: SAGE
ISBN: 1473971314
Category : Social Science
Languages : en
Pages : 954

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Book Description
In this important new Handbook, the editors have gathered together a range of leading contributors to introduce the theory and practice of multilevel modeling. The Handbook establishes the connections in multilevel modeling, bringing together leading experts from around the world to provide a roadmap for applied researchers linking theory and practice, as well as a unique arsenal of state-of-the-art tools. It forges vital connections that cross traditional disciplinary divides and introduces best practice in the field. Part I establishes the framework for estimation and inference, including chapters dedicated to notation, model selection, fixed and random effects, and causal inference. Part II develops variations and extensions, such as nonlinear, semiparametric and latent class models. Part III includes discussion of missing data and robust methods, assessment of fit and software. Part IV consists of exemplary modeling and data analyses written by methodologists working in specific disciplines. Combining practical pieces with overviews of the field, this Handbook is essential reading for any student or researcher looking to apply multilevel techniques in their own research.