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FEniCS enables users to quickly translate scientific models into efficient finite element code. With the high-level Python and C interfaces to FEniCS, it is easy to get started, but FEniCS offers also powerful capabilities for more experienced programmers. FEniCS runs on a multitude of platforms ranging from laptops to high-performance clusters.
Latest commits to the Firedrake master branch on Github. Firedrake enables users to employ a wide range of discretisations to an infinite variety of PDEs and employ either conventional CPUs or GPUs to obtain the solution. While the parallel execution of FEM assembly is accomplished by the PyOP2.
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Innovative Solutions And Open Source Software. Innovative consulting services and customized software. An open source software library designed to solve general purpose nonlinear optimization problems. New paper published on AC microgrid optimization and model predictive controls. Another application of Optizelle to an optimal control. New major release of the Optizelle code. HPC considerations for robust, reliable optimization codes.
I am an Associate Professor of Numerical Analysis and Scientific Computing. And EPSRC Early Career Research Fellow. In the Numerical Analysis group. Of the University of Oxford, and a Tutorial Fellow at Oriel College, Oxford. I mainly code in Python, contribute regularly to the FEniCS. Software projects, and lead the development of dolfin-adjoint. My co-supervisors are Alain Goriely.
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Imperial College London
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Royal School of Mines
London, --, SW7 2BP
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The dolfin-adjoint project automatically derives the discrete adjoint and tangent linear models. From a forward model written in the Python interface to DOLFIN. Naumann 2011 states that. The automatic generation of optimal in terms of robustness and efficiency adjoint versions of large-scale simulation code is one of the great open challenges in the field of High-Performance Scientific Computing. The dolfin-adjoint project aims to solve this problem. We now offer Docker images to simplify the instal.PARSED CONTENT
The web page dolfin-adjoint.org had the following in the homepage, "The dolfin-adjoint project automatically derives the discrete adjoint and tangent linear models." I saw that the webpage stated " From a forward model written in the Python interface to DOLFIN." They also said " The automatic generation of optimal in terms of robustness and efficiency adjoint versions of large-scale simulation code is one of the great open challenges in the field of High-Performance Scientific Computing. The dolfin-adjoint project aims to solve this problem. We now offer Docker images to simplify the instal."SEE SUBSEQUENT DOMAINS
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