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Author: Benjamin Ong
Publisher: Springer Nature
ISBN: 3030759334
Category : Mathematics
Languages : en
Pages : 134
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Book Description
This volume includes contributions from the 9th Parallel-in-Time (PinT) workshop, an annual gathering devoted to the field of time-parallel methods, aiming to adapt existing computer models to next-generation machines by adding a new dimension of scalability. As the latest supercomputers advance in microprocessing ability, they require new mathematical algorithms in order to fully realize their potential for complex systems. The use of parallel-in-time methods will provide dramatically faster simulations in many important areas, including biomedical (e.g., heart modeling), computational fluid dynamics (e.g., aerodynamics and weather prediction), and machine learning applications. Computational and applied mathematics is crucial to this progress, as it requires advanced methodologies from the theory of partial differential equations in a functional analytic setting, numerical discretization and integration, convergence analyses of iterative methods, and the development and implementation of new parallel algorithms. Therefore, the workshop seeks to bring together an interdisciplinary group of experts across these fields to disseminate cutting-edge research and facilitate discussions on parallel time integration methods.
Author: Benjamin Ong
Publisher: Springer Nature
ISBN: 3030759334
Category : Mathematics
Languages : en
Pages : 134
Get Book Here
Book Description
This volume includes contributions from the 9th Parallel-in-Time (PinT) workshop, an annual gathering devoted to the field of time-parallel methods, aiming to adapt existing computer models to next-generation machines by adding a new dimension of scalability. As the latest supercomputers advance in microprocessing ability, they require new mathematical algorithms in order to fully realize their potential for complex systems. The use of parallel-in-time methods will provide dramatically faster simulations in many important areas, including biomedical (e.g., heart modeling), computational fluid dynamics (e.g., aerodynamics and weather prediction), and machine learning applications. Computational and applied mathematics is crucial to this progress, as it requires advanced methodologies from the theory of partial differential equations in a functional analytic setting, numerical discretization and integration, convergence analyses of iterative methods, and the development and implementation of new parallel algorithms. Therefore, the workshop seeks to bring together an interdisciplinary group of experts across these fields to disseminate cutting-edge research and facilitate discussions on parallel time integration methods.
Author: Benjamin Ong
Publisher:
ISBN: 9783030759346
Category :
Languages : en
Pages : 0
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Book Description
This volume includes contributions from the 9th Parallel-in-Time (PinT) workshop, an annual gathering devoted to the field of time-parallel methods, aiming to adapt existing computer models to next-generation machines by adding a new dimension of scalability. As the latest supercomputers advance in microprocessing ability, they require new mathematical algorithms in order to fully realize their potential for complex systems. The use of parallel-in-time methods will provide dramatically faster simulations in many important areas, including biomedical (e.g., heart modeling), computational fluid dynamics (e.g., aerodynamics and weather prediction), and machine learning applications. Computational and applied mathematics is crucial to this progress, as it requires advanced methodologies from the theory of partial differential equations in a functional analytic setting, numerical discretization and integration, convergence analyses of iterative methods, and the development and implementation of new parallel algorithms. Therefore, the workshop seeks to bring together an interdisciplinary group of experts across these fields to disseminate cutting-edge research and facilitate discussions on parallel time integration methods. .
Author: Antony Jameson
Publisher: Cambridge University Press
ISBN: 1108837883
Category : Science
Languages : en
Pages : 627
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Book Description
Learn the design and analysis of numerical algorithms for aerodynamics. Ideal for graduates, researchers, and professionals in the field.
Author: George Em Karniadakis
Publisher: Cambridge University Press
ISBN: 110749477X
Category : Computers
Languages : en
Pages : 640
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Book Description
Numerical algorithms, modern programming techniques, and parallel computing are often taught serially across different courses and different textbooks. The need to integrate concepts and tools usually comes only in employment or in research - after the courses are concluded - forcing the student to synthesise what is perceived to be three independent subfields into one. This book provides a seamless approach to stimulate the student simultaneously through the eyes of multiple disciplines, leading to enhanced understanding of scientific computing as a whole. The book includes both basic as well as advanced topics and places equal emphasis on the discretization of partial differential equations and on solvers. Some of the advanced topics include wavelets, high-order methods, non-symmetric systems, and parallelization of sparse systems. The material covered is suited to students from engineering, computer science, physics and mathematics.
Author: Yuefan Deng
Publisher: World Scientific
ISBN: 9814307602
Category : Computers
Languages : en
Pages : 218
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Book Description
The book provides a practical guide to computational scientists and engineers to help advance their research by exploiting the superpower of supercomputers with many processors and complex networks. This book focuses on the design and analysis of basic parallel algorithms, the key components for composing larger packages for a wide range of applications.
Author: Yeran Meguerdich Soukiassian
Publisher:
ISBN:
Category :
Languages : en
Pages : 246
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Book Description
Solving time-dependent differential equations in a time-parallel way is almost i mpossible, since any time-integration procedure is inherently sequential. Howeve r in recent years, predictor-corrector schemes have been proposed by several aut hors attempting to solve a time dependent differential equation by first dividin g the integration interval into a coarse grid of subintervals, then proceeding b y judiciously predicting the value of the solution at the beginning of each subi nterval. Independent solving of the differential equation on each of the subinte rvals leads to corrections of the predicted values. An iterative process is thus generated which success is directly dependent on its global speed of convergenc e over the coarse grid. This thesis proposes a new method of parallel integratio n: RaPTI, the ̀̀Ratio Based Parallel Time Integration" algorithm. It is a predic tor-corrector scheme based on a ratio phenomenon that can be verified on the bas is of a re-scaling technique. Such technique has also the advantage of automatic ally generating the ̀̀time-slices" of the coarse grid. Unlike other methods such as the Parareal algorithm (Lions et al 2001), it continuously performs parallel predictions and corrections with convergence occurring within few iterations du e to the good ̀̀ratio-based" estimates at the start of each time slice. In this thesis we validate RaPTI for one and two-dimensional semi-discrete diffusion-rea ction evolution problems and also to logistic Lotka-Volterra models for two and three species. Good efficiency results are found, outperforming other algorithms such as Lions Parareal method.
Author: Michael A. Heroux
Publisher: SIAM
ISBN: 9780898718133
Category : Computers
Languages : en
Pages : 421
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Book Description
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: Yousef Saad
Publisher: SIAM
ISBN: 0898715342
Category : Mathematics
Languages : en
Pages : 537
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Book Description
Mathematics of Computing -- General.
Author: Ralf Kornhuber
Publisher: Springer Science & Business Media
ISBN: 3540268251
Category : Mathematics
Languages : en
Pages : 686
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Book Description
Domain decomposition is an active, interdisciplinary research area that is devoted to the development, analysis and implementation of coupling and decoupling strategies in mathematics, computational science, engineering and industry. A series of international conferences starting in 1987 set the stage for the presentation of many meanwhile classical results on substructuring, block iterative methods, parallel and distributed high performance computing etc. This volume contains a selection from the papers presented at the 15th International Domain Decomposition Conference held in Berlin, Germany, July 17-25, 2003 by the world's leading experts in the field. Its special focus has been on numerical analysis, computational issues,complex heterogeneous problems, industrial problems, and software development.
Author: Dimitri Bertsekas
Publisher: Athena Scientific
ISBN: 1886529159
Category : Mathematics
Languages : en
Pages : 832
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Book Description
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.
