@misc{14395,
author = {Marie Rognes},
title = {Impact of high abstraction/high performance finite element software in biomedical computing},
abstract = {The development of numerical software in general and finite elementsoftware in particular is recognized as a challenging and error-proneprocess -- traditionally requiring in-depth expertise from a number ofscientific fields. The FEniCS and Dolfin-adjoint projects target thischallenge by developing generic algorithms and open source softwarefor the automated solution of partial differential equations usingfinite element methods. The FEniCS Project is described by in theFEniCS book [1] and a number of research papers, see e.g. [2].The related Dolfin-adjoint software, winner of the 2015 WilkinsonPrize for Numerical Software, automatically derives discrete adjointand tangent linear models from a forward FEniCS model[3]. Theseadjoint and tangent linear models are key ingredients in manyimportant algorithms, such as data assimilation, optimal control,sensitivity analysis, design optimisation, and error estimation.In this presentation, I{\textquoteright}ll give an overview of the FEniCS andDolfin-adjoint projects focusing on current developments andapplications in biomedical computing.[1] A. Logg, K.-A. Mardal, G. N. Wells et al. (2012). AutomatedSolution of Differential Equations by the Finite Element Method,Springer. [doi:10.1007/978-3-642-23099-8][2] M. S. Aln{\ae}s, J. Blechta, J. Hake, A. Johansson, B. Kehlet,A. Logg, C. Richardson, J. Ring, M. E. Rognes and G. N. Wells(2015). The FEniCS Project Version 1.5, Archive of Numerical Software,3(100), [doi:10.11588/ans.2015.100.20553].[3] P. E. Farrell, D. A. Ham, S. W. Funke and M. E. Rognes(2013). Automated derivation of the adjoint of high-level transientfinite element programs, SIAM Journal on Scientific Computing 35.4,pp. C369-C393. doi:10.1137/120873558.},
year = {2017},
journal = {24th International Conference on Domain Decomposition Methods, Svalbard, Norway},
}