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Parallel-in-Time Integration Methods: 9th Parallel-in-Time Workshop, June 8-12, 2020: 356 (Springer Proceedings in Mathematics & Statistics, 356) - Tapa dura

Libro 355 de 463: Springer Proceedings in Mathematics & Statistics
 
9783030759322: Parallel-in-Time Integration Methods: 9th Parallel-in-Time Workshop, June 8-12, 2020: 356 (Springer Proceedings in Mathematics & Statistics, 356)
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ISBN 10: 3030759326 ISBN 13: 9783030759322
Editorial: Springer, 2021

Sinopsis

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. 

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De la contraportada

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.

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Editorial
Springer
Año de publicación
2021
Idioma
Inglés
ISBN 10 
3030759326
ISBN 13 
9783030759322
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
140
Editor
Ong Benjamin, Schroder Jacob, Shipton Jemma
Contacto del fabricante
ProductSafety@springernature.com
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