tapenade_diff

tapenade diff

Tapenade is an automatic differentiation tool developed by researchers at INRIA (the French National Institute for Research in Computer Science and Automation).

Tapenade is designed to automatically generate derivative code for numerical simulation programs written in Fortran or C. It enables the computation of gradients, Hessians, and other derivatives efficiently, which is particularly useful in fields such as optimization, sensitivity analysis, and scientific computing.

By analyzing the source code of the original program, Tapenade generates code that computes the derivatives of the program's outputs with respect to its inputs. This capability is crucial in many scientific and engineering applications where the ability to efficiently compute derivatives is essential.

Overall, Tapenade simplifies the process of incorporating automatic differentiation into existing numerical simulation codes, making it a valuable tool for researchers and developers working in computational science and engineering.

How we use it

In yaeos we developed a wrapper object that receives a set of routines from a differentiated module and uses and internal logic to get the desired $A_r$ derivatives.

Obtain a tapenade differentiated EoS

Getting a usable $A_r$ equation of state with tapenade is fairly easy.

1. Install tapenade and assure that you have the tapenade executable in your PATH.
2. Setup your new model following the template file. a full implementation of the PengRobinson EoS can be seen at pr.f90 as an example.
3. Run the script gen_tapemodel.sh, providing your file as an argument:

   bash gen_tapemodel.sh <your_model_file.f90>

   This will generate a new folder tapeout, with your differentiated model inside.
4. Some little post-process must be done due to some details in the tapenade implementation. These are described in the base template but can also be checked on the differentiated PR76 result after fixing the last details

To add your new tapenade model just include the file in your src folder and use it with

use yaeos, only: ArModel, pressure
use your_module_name, only: setup_model

class(ArModel), allocatable :: model

model = setup_model(<your parameters>)

call pressure(model, n, v, t)