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Implicit-explicit time integration for adaptive simulations in MUSE [presentation]
Implicit-explicit time integration for adaptive simulations in MUSE [video]
Implicit-explicit time integration for adaptive simulations in MUSE [presentation]
Dean, R. (2010). Implicit-explicit time integration for adaptive simulations in MUSE [presentation]. In Summer Internships in Parallel Computational Science 2010. Boulder, CO, US.
This presentation was delivered by a student in the Summer Internships in Parallel Computational Science Program (SIParCS) at the National Center for Atmospheric Research (NCAR). SIParCS embeds graduate and undergraduate students as summer interns in NCAR's Computational and Information System La... Show moreThis presentation was delivered by a student in the Summer Internships in Parallel Computational Science Program (SIParCS) at the National Center for Atmospheric Research (NCAR). SIParCS embeds graduate and undergraduate students as summer interns in NCAR's Computational and Information System Laboratory, offering them significant hands-on R&D opportunities in high performance computing (HPC) and related fields that use HPC for scientific discovery and modeling. Complex climate models in the Multiscale Unified Simulation Environment (MUSE) contain both stiff and non-stiff terms; a particular stiff or non-stiff time integration method is not likely to be the most efficient choice. In this presentation, I outline trial experiments in Matlab comparing the use of Implicit-Explicit (IMEX) Runge-Kutta methods, which are comprised of a combination of a stiff and non-stiff method, to a range of standard and specialized time integration methods. Show less