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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
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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: 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: 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: Roman Trobec
Publisher: Springer Science & Business Media
ISBN: 1848824092
Category : Computers
Languages : en
Pages : 531
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Book Description
The use of parallel programming and architectures is essential for simulating and solving problems in modern computational practice. There has been rapid progress in microprocessor architecture, interconnection technology and software devel- ment, which are in?uencing directly the rapid growth of parallel and distributed computing. However, in order to make these bene?ts usable in practice, this dev- opment must be accompanied by progress in the design, analysis and application aspects of parallel algorithms. In particular, new approaches from parallel num- ics are important for solving complex computational problems on parallel and/or distributed systems. The contributions to this book are focused on topics most concerned in the trends of today’s parallel computing. These range from parallel algorithmics, progr- ming, tools, network computing to future parallel computing. Particular attention is paid to parallel numerics: linear algebra, differential equations, numerical integ- tion, number theory and their applications in computer simulations, which together form the kernel of the monograph. We expect that the book will be of interest to scientists working on parallel computing, doctoral students, teachers, engineers and mathematicians dealing with numerical applications and computer simulations of natural phenomena.
Author: Ivan Dimov
Publisher: IOS Press
ISBN: 9789051991512
Category : Computers
Languages : en
Pages : 216
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Book Description
This text presents an overview of research in the subjects of computational linear algebra, Monte Carlo algorithms and parallel algorithms in discrete mathematics. Topics covered include theoretical investigations of numerical analysis and parallel algorithms, and practical large-scale problem solving such as modelling of semiconductor devices, ballistic trajectory estimations and the simulation of distributed memory parallel computers.
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: Dieter W. Heermann
Publisher: Springer Science & Business Media
ISBN: 3642762654
Category : Science
Languages : en
Pages : 192
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Book Description
Our aim in this book is to present and enlarge upon those aspects of parallel computing that are needed by practitioners of computational science. Today al most all classical sciences, such as mathematics, physics, chemistry and biology, employ numerical methods to help gain insight into nature. In addition to the traditional numerical methods, such as matrix inversions and the like, a whole new field of computational techniques has come to assume central importance, namely the numerical simulation methods. These methods are much less fully developed than those which are usually taught in a standard numerical math ematics course. However, they form a whole new set of tools for research in the physical sciences and are applicable to a very wide range of problems. At the same time there have been not only enormous strides forward in the speed and capability of computers but also dramatic new developments in computer architecture, and particularly in parallel computers. These improvements offer exciting prospects for computer studies of physical systems, and it is the new techniques and methods connected with such computer simulations that we seek to present in this book, particularly in the light of the possibilities opened up by parallel computers. It is clearly not possible at this early stage to write a definitive book on simulation methods and parallel computing.
Author: Martin Jakob Gander
Publisher:
ISBN:
Category :
Languages : en
Pages : 173
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Book Description
Author: Julien Remi Cortial
Publisher: Stanford University
ISBN:
Category :
Languages : en
Pages : 188
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Book Description
The classical approach for solving evolution Partial Differential Equations (PDEs) using a parallel computer consists in first partitioning the spatial domain and assigning each subdomain to a processor to achieve space-parallelism, then advancing the solution sequentially. However, enabling parallelism along the time dimension, despite its intrinsic difficulty, can be of paramount importance to fast computations when space-parallelism is unfeasible, cannot fully exploit a massively parallel machine or when near-real-time prediction is desired. The aforementioned objective can be achieved by applying classical domain decomposition principles to the time axis. The latter is first partitioned into time-slices to be processed independently. Starting with approximate seed information that provides a set of initial conditions, the response is then advanced in parallel in each time-slice using a standard time-stepping integrator. This decomposed solution exhibits discontinuities or jumps at the time-slice boundaries if the initial guess is not accurate. Applying a Newton-like approach to the time-dependent system, a correction function is then computed to improve the accuracy of the seed values and the process is repeated until convergence is reached. Methods based on the above concept have been successfully applied to various problems but none was found to be competitive for even for the simplest of second-order hyperbolic PDEs, a class of equations that covers the field of structural dynamics among others. To overcome this difficulty, a key idea is to improve the sequential propagator used for correcting the seed values, observing that the original evolution problem and the derived corrective one are closely related. The present work first demonstrates how this insight can be brought to fruition in the context of linear oscillators, with numerical examples featuring structural models ranging from academic to more challenging large-scale ones. An extension of this method to nonlinear equations is then developed and its concrete application to geometrically nonlinear transient dynamics is presented. Finally, it is shown how the time-reversibility property that characterizes some of the above problems can be exploited to develop a new framework that provides an increased speed-up factor.
Author: Michael McCool
Publisher: Elsevier
ISBN: 0124159931
Category : Computers
Languages : en
Pages : 434
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Book Description
Programming is now parallel programming. Much as structured programming revolutionized traditional serial programming decades ago, a new kind of structured programming, based on patterns, is relevant to parallel programming today. Parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders describe how to design and implement maintainable and efficient parallel algorithms using a pattern-based approach. They present both theory and practice, and give detailed concrete examples using multiple programming models. Examples are primarily given using two of the most popular and cutting edge programming models for parallel programming: Threading Building Blocks, and Cilk Plus. These architecture-independent models enable easy integration into existing applications, preserve investments in existing code, and speed the development of parallel applications. Examples from realistic contexts illustrate patterns and themes in parallel algorithm design that are widely applicable regardless of implementation technology. The patterns-based approach offers structure and insight that developers can apply to a variety of parallel programming models Develops a composable, structured, scalable, and machine-independent approach to parallel computing Includes detailed examples in both Cilk Plus and the latest Threading Building Blocks, which support a wide variety of computers
