ADOL - C : 1 A Package for the Automatic Differentiation of Algorithms Written in C / C + +

نویسندگان

  • Andrea Walther
  • Andreas Griewank
چکیده

The C++ package ADOL-C described here facilitates the evaluation of first and higher derivatives of vector functions that are defined by computer programs written in C or C++. The resulting derivative evaluation routines may be called from C, C++, Fortran, or any other language that can be linked with C. The numerical values of derivative vectors are obtained free of truncation errors at a small multiple of the run time and random access memory required by the given function evaluation program. Derivative matrices are obtained by columns, by rows or in sparse format. For solution curves defined by ordinary differential equations, special routines are provided that evaluate the Taylor coefficient vectors and their Jacobians with respect to the current state vector. For explicitly or implicitly defined functions derivative tensors are obtained with a complexity that grows only quadratically in their degree. The derivative calculations involve a possibly substantial but always predictable amount of data. Since the data is accessed strictly sequentially it can be automatically paged out to external files.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Package for the Automatic Differentiation of Algorithms Written in C/C++

The C++ package ADOL-C described here facilitates the evaluation of first and higher derivatives of vector functions that are defined by computer programs written in C or C++. The resulting derivative evaluation routines may be called from C, C++, Fortran, or any other language that can be linked with C. The numerical values of derivative vectors are obtained free of truncation errors at a smal...

متن کامل

Efficient Calculation of Sensitivities for Optimization Problems

Sensitivity information is required by numerous applications such as, for example, optimization algorithms, parameter estimations or real time control. Sensitivities can be computed with working accuracy using the forward mode of automatic differentiation (AD). ADOL-C is an AD-tool for programs written in C or C++. Originally, when applying ADOL-C, tapes for values, operations and locations are...

متن کامل

LIEDRIVERS - A Toolbox for the Efficient Computation of Lie Derivatives Based on the Object-Oriented Algorithmic Differentiation Package ADOL-C

Lie derivatives are widely used in mathematics and physics. They are usually computed symbolically using computer algebra software. This symbolic computation might fail for very complicated expressions. Moreover, symbolic differentiation becomes more difficult if the function to be differentiated is not described explicitly as a function but by an algorithm. This is a situation occuring quite o...

متن کامل

A Package for the Automatic Diierentiation of Algorithms Written in C/c++

The C++ package ADOL-C described here facilitates the evaluation of rst and higher derivatives of vector functions that are deened by computer programs written in C or C++. The resulting derivative evaluation routines may be called from C/C++, Fortran, or any other language that can be linked with C. The numerical values of derivative vectors are obtained free of truncation errors at a small mu...

متن کامل

Wrappers for ADOL-C in scripting languages using SWIG

R is a language and environment for statistical computing and graphics [1]. It currently is widely used in statistics and data mining. To obtain derivatives in R, one can use several non-native approaches, including the TMB system [2] and Ryacas [3]. However, none of these options support the di↵erentiation of functions expressed as R programs, as would an algorithmic di↵erentiation (AD) tool f...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2010