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Parallel-in-Time Integration Methods = 9th Parallel-in-Time Workshop, June 8–12, 2020 /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Parallel-in-Time Integration Methods/ edited by Benjamin Ong, Jacob Schroder, Jemma Shipton, Stephanie Friedhoff.
其他題名:	9th Parallel-in-Time Workshop, June 8–12, 2020 /
其他作者:	Ong, Benjamin.
面頁冊數:	IX, 127 p. 41 illus., 38 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computer mathematics. -
電子資源:	https://doi.org/10.1007/978-3-030-75933-9
ISBN:	9783030759339

Parallel-in-Time Integration Methods = 9th Parallel-in-Time Workshop, June 8–12, 2020 /
Parallel-in-Time Integration Methods9th Parallel-in-Time Workshop, June 8–12, 2020 /[electronic resource] :edited by Benjamin Ong, Jacob Schroder, Jemma Shipton, Stephanie Friedhoff. - 1st ed. 2021. - IX, 127 p. 41 illus., 38 illus. in color.online resource. - Springer Proceedings in Mathematics & Statistics,3562194-1017 ;. - Springer Proceedings in Mathematics & Statistics,125.

Tight two-level convergence of linear Parareal and MGRIT: Extensions and implications in practice (Southworth et al.) -- A Parallel algorithm for solving linear parabolic evolution equations (van Venetië et al.) -- Using performance analysis tools for a parallel-in-time integrator (Speck et al.) -- Twelve Ways to Fool the Masses When Giving Parallel-In-Time Results (Götschel et al.) -- IMEX Runge-Kutta Parareal for Non-Diffusive Equations (Buvoli et al.).

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. .

ISBN: 9783030759339

Standard No.: 10.1007/978-3-030-75933-9doiSubjects--Topical Terms:

1199796
Computer mathematics.

LC Class. No.: QA71-90

Dewey Class. No.: 518

Parallel-in-Time Integration Methods = 9th Parallel-in-Time Workshop, June 8–12, 2020 /
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