Section: Overall Objectives

Overall Objectives

Sciport is a temporary sequel to the former project Tropics. Sciport will stop at the end of 2013, when the new project Ecuador starts.

The team studies Automatic Differentiation (AD) of algorithms and programs, thus at the junction of two research domains :

• AD theory: We study software engineering techniques, to analyze and transform programs mechanically. Automatic Differentiation (AD) transforms a program P that computes a function $F$, into a program P' that computes analytical derivatives of $F$. We put emphasis on the so-called reverse or adjoint mode of AD, a sophisticated transformation that yields gradients for optimization at a remarkably low cost.

• AD application to Scientific Computing: We apply the adjoint mode of AD to e.g. Computational Fluid Dynamics. We adapt the strategies of Scientific Computing to take full advantage of AD. We validate our work on real-size applications.

We want to produce AD code that can compete with hand-written sensitivity and adjoint programs used in the industry. We implement our algorithms into our tool tapenade , which is one of the most popular AD tools.

Our research directions are :

• Modern numerical methods for finite elements or finite differences : multigrid methods, mesh adaptation.

• Optimal shape design or optimal control in fluid dynamics for steady and unsteady simulations. Higher-order derivatives for robust optimization and uncertainty quantification.

• Automatic Differentiation : AD-specific static data-flow analysis, strategies to reduce runtime and memory consumption of the adjoint mode for very large codes. Improved models for adjoint-mode AD, in particular coping with Message-Passing parallellism.