The Tapenade automatic differentiation tool
نویسندگان
چکیده
منابع مشابه
Building the Tangent and Adjoint codes of the Ocean General Circulation Model OPA with the Automatic Differentiation tool TAPENADE
The ocean general circulation model OPA is developed by the LODYC team at Paris VI university. OPA has recently undergone a major rewriting, migrating to FORTRAN95, and its adjoint code needs to be rebuilt. For earlier versions, the adjoint of OPA was written by hand at a high development cost. We use the Automatic Differentiation tool TAPENADE to build mechanicaly the tangent and adjoint codes...
متن کاملInterfacing OpenAD and Tapenade
Development of a capable algorithmic differentiation (AD) tool requires large developer effort to provide the various flavors of derivatives, to experiment with the many AD model variants, and to apply them to the candidate application languages. Considering the relatively small size of the academic teams that develop AD tools, collaboration between them is a natural idea. This collaboration ca...
متن کاملauto_deriv: Tool for automatic differentiation of a Fortran code
AUTO_DERIV is a module comprised of a set of FORTRAN 90 procedures which can be used to calculate the first and second partial derivatives of any continuous function with many independent variables. The function should be expressed as one or more FORTRAN 90 or FORTRAN 77 procedures. A new type of variables is defined and the overloading mechanism of functions and operators provided by the FORTR...
متن کاملADIC: An Extensible Automatic Differentiation Tool for ANSI-C
In scienti c computing, we often require the derivatives @f=@x of a function f expressed as a program with respect to some input parameter(s) x, say. Automatic di erentiation (AD) techniques augment the program with derivative computation by applying the chain rule of calculus to elementary operations in an automated fashion. This article introduces ADIC (Automatic Di erentiation of C), a new A...
متن کاملAutomatic Differentiation on Differentiable Manifolds as a Tool for Robotics
Automatic differentiation (AD) is a useful tool for computing Jacobians of functions needed in estimation and control algorithms. However, for many interesting problems in robotics, state variables live on a differentiable manifold. The most common example are robot orientations that are elements of the Lie group SO(3). This causes problems for AD algorithms that only consider differentiation a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ACM Transactions on Mathematical Software
سال: 2013
ISSN: 0098-3500,1557-7295
DOI: 10.1145/2450153.2450158