1.

Record Nr.

UNINA9910894638903321

Titolo

Current cathlab news : CCN

Pubbl/distr/stampa

München, : MediaDomain Verlags GmbH, 2010-2011

Descrizione fisica

Online-Ressource

Disciplina

610

Soggetti

Zeitschrift

Lingua di pubblicazione

Tedesco

Formato

Materiale a stampa

Livello bibliografico

Periodico

Note generali

Gesehen am 24.08.12

2.

Record Nr.

UNINA9910495236303321

Titolo

Parallel-in-Time Integration Methods : 9th Parallel-in-Time Workshop, June 8–12, 2020 / / edited by Benjamin Ong, Jacob Schroder, Jemma Shipton, Stephanie Friedhoff

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021

ISBN

3-030-75933-4

Edizione

[1st ed. 2021.]

Descrizione fisica

1 online resource (134 pages)

Collana

Springer Proceedings in Mathematics & Statistics, , 2194-1017 ; ; 356

Disciplina

004.35

Soggetti

Mathematics - Data processing

Mathematics

Computational Mathematics and Numerical Analysis

Mathematics and Computing

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

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.).

Sommario/riassunto

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. .