Tor Harald Sandve 44e9d2a34e Fix PR comments
1) swatinit() is changed to setSwatInitScaling() to make it obvious that
we are modifying the props.
2) the descriptions of saturation and pc now makes more sense
3) the method is removed from the sibling class and the interface and
the type of new_props is changed from BlackoilPropsAdInterface to
BlackoilPropsAdFromDeck
5) The same modification is added to sim_fibo_ad_cp
2015-02-19 08:34:55 +01:00
2014-12-08 15:26:48 +01:00
2014-11-17 17:57:29 +01:00
2015-02-19 08:34:55 +01:00
2015-02-19 08:34:55 +01:00
2013-10-30 17:52:37 +01:00
2014-12-08 15:26:18 +01:00
2015-02-11 12:35:40 +01:00

Open Porous Media Automatic Differentiation Library

CONTENT

opm-autodiff contains a small library for automatic differentiation built on the Eigen linear algebra package. It also contains some experimental solver and simulator prototypes demonstrating how it can be used. The most important parts are:

  • AutoDiffBlock.hpp (class for AD on vectorized data with sparse jacobians)
  • AutoDiffHelpers.hpp (various utilities to simplify writing solvers)
  • sim_fibo_ad.cpp (prototype fully implicit black-oil simulator)

LICENSE

The library is distributed under the GNU General Public License, version 3 or later (GPLv3+).

PLATFORMS

The opm-autodiff module is designed to run on Linux platforms. It is also regularly run on Mac OS X. No efforts have been made to ensure that the code will compile and run on windows platforms.

REQUIREMENTS

opm-autodiff requires opm-core, and all its requirements (see opm-core/README). In addition, opm-autodiff requires Eigen, version 3.1 (has not been tested with later versions).

DOWNLOADING

For a read-only download: git clone git://github.com/OPM/opm-autodiff.git

If you want to contribute, fork OPM/opm-autodiff on github.

BUILDING

See build instructions in opm-core/README, or at http://opm-project.org/download.php.

DOCUMENTATION

Efforts have been made to document the code with Doxygen. In order to build the documentation, enter the command

make doc

in the topmost directory. The class AutoDiffBlock is the most important and most well-documented.

REPORTING ISSUES

Issues can be reported in the Git issue tracker online at:

https://github.com/OPM/opm-autodiff/issues

To help diagnose build errors, please provide a link to a build log together with the issue description.

You can capture such a log from the build using the `script' utility, e.g.:

LOGFILE=$(date +%Y%m%d-%H%M-)build.log ;
cmake -E cmake_echo_color --cyan --bold "Log file: $LOGFILE" ;
script -q $LOGFILE -c 'cmake ../opm-core -DCMAKE_BUILD_TYPE=Debug' &&
script -q $LOGFILE -a -c 'ionice nice make -j 4 -l 3' ||
cat CMakeCache.txt CMakeFiles/CMake*.log >> $LOGFILE

The resulting file can be uploaded to for instance gist.github.com.

Description
Simulator programs and utilities for automatic differentiation.
Readme 70 MiB
Languages
C++ 78.3%
ECL 17.7%
CMake 1.8%
Cuda 1.2%
Shell 0.5%
Other 0.5%