LEADER 03508nam 22005415 450 001 9910495236303321 005 20251113204823.0 010 $a3-030-75933-4 024 7 $a10.1007/978-3-030-75933-9 035 $a(CKB)5590000000549916 035 $a(MiAaPQ)EBC6711406 035 $a(Au-PeEL)EBL6711406 035 $a(OCoLC)1265347388 035 $a(PPN)257352597 035 $a(DE-He213)978-3-030-75933-9 035 $a(EXLCZ)995590000000549916 100 $a20210824d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aParallel-in-Time Integration Methods $e9th Parallel-in-Time Workshop, June 8?12, 2020 /$fedited by Benjamin Ong, Jacob Schroder, Jemma Shipton, Stephanie Friedhoff 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (134 pages) 225 1 $aSpringer Proceedings in Mathematics & Statistics,$x2194-1017 ;$v356 311 08$a3-030-75932-6 327 $aTight 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.). 330 $aThis volume includes contributions from the 9th Parallel-in-Time (PinT) workshop, an annual gathering devoted to the field of time-parallel methods, aiming to adapt existing computer models to next-generation machines by adding a new dimension of scalability. As the latest supercomputers advance in microprocessing ability, they require new mathematical algorithms in order to fully realize their potential for complex systems. The use of parallel-in-time methods will provide dramatically faster simulations in many important areas, including biomedical (e.g., heart modeling), computational fluid dynamics (e.g., aerodynamics and weather prediction), and machine learning applications. Computational and applied mathematics is crucial to this progress, as it requires advanced methodologies from the theory of partial differential equations in a functional analytic setting, numerical discretization and integration, convergence analyses of iterative methods, and the development and implementation of new parallel algorithms. Therefore, the workshop seeks to bring together an interdisciplinary group of experts across these fields to disseminate cutting-edge research and facilitate discussions on parallel time integration methods. . 410 0$aSpringer Proceedings in Mathematics & Statistics,$x2194-1017 ;$v356 606 $aMathematics$xData processing 606 $aMathematics 606 $aComputational Mathematics and Numerical Analysis 606 $aMathematics and Computing 615 0$aMathematics$xData processing. 615 0$aMathematics. 615 14$aComputational Mathematics and Numerical Analysis. 615 24$aMathematics and Computing. 676 $a004.35 702 $aOng$b Benjamin 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910495236303321 996 $aParallel-in-time integration methods$92843013 997 $aUNINA