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Code for generating optimal Stability Polynomials by Second Order Cones in arbitrary precision.
In order to use EiCOS
you need to have Eigen3
installed. If you are on Ubuntu or an other Debian based Linux distribution it is recommended to install Eigen3
via
sudo apt install libeigen3-dev
Within this project the multiprecision floating point types are based on the Boost Multiprecision types. See the docs for a detailed introduction.
On Debian-based systems it is again easiest to install Boost over the package manager via
sudo apt-get install libboost-all-dev
although this brings in the whole Boost library.
To build EiCOS
you need CMake
to be installed on your system, which is the case on most Linux distributions.
To be able to use SSOCs
you need to compile the shared library libeicos_MP.so
of my fork from the EiCOS
repository.
After installing Eigen3
and the Boost multiprecision library you need to cd
to the directory where you downloaded or forked EiCOS
.
It is assumed that this is ~/git/EiCOS/
in the compile scripts, where ~
is synonymous with $HOME
.
Then, execute
cmake -DCMAKE_BUILD_TYPE=Release .
to generate the make files with release flags. Then type
make
to compile the shared library libeicos_MP.so
.
A successful output should look like this:
[ 50%] Building CXX object CMakeFiles/eicos_MP.dir/src/eicos_MP.cpp.o
[100%] Linking CXX shared library libeicos_MP.so
[100%] Built target eicos_MP
If you installed EiCOS
not in ~/git/EiCOS
you need to exchange that path wherever it occurrs in the Makefile
.
Then, you can simply execute
make MP_TARGETS -j 2
which gives you both SSOCs_MP.exe
and SSOCs_PERK4.exe
.
It might be required that you make these binaries executable, i.e.,
chmod +x *.exe
To generate the fourth order accurate stability polynomial for the fourth order Paired-Explicit Runge-Kutta schemes type
./SSOCs_PERK4_MP.exe <Degree> <dtMax> <path/to/spectrum/file> <OPTIONAL:Stages>
where
<Degree>
needs to be exchanged for the stability polynomial degree. For the PERK4 schemes (SSOCs_PERK4.cpp
), this needs to be an integer > 5, while for the general version (SSOCs.cpp
) also a polynomial with degreee 5 may be optimized.<dtMax>
is the maximum timestep that may be possible. In principle this can be chosen arbitrarily large, which slows down the optimization. Supplying a too small value gives wrong results if the true admissible timestep is larger.<path/to/spectrum/file>
is the path to the file with the eigenvalues used for constraining the stability polynomial. The file should contain the eigenvalues should that one eigenvalue is there per row with syntaxRe(lambda)+Im(lambda)i
to allow correct processing.- The last argument is optional and may be supplied to obtain the Butcher array coefficients of a method with
<Degree>
stage-evaluations which is embedded into a<Stages>
stage overall paired-explicit Runge-Kutta method.
If you use the implementations provided here, please also cite this repository as
@misc{doehring2024ssocs,
title={{SSOCs}: Arbitrary Precision Stability Polynomials by Second-Order Cones},
author={Doehring, Daniel},
year={2024},
howpublished={\url{https://github.com/DanielDoehring/SSOCs}},
doi={https://doi.org/10.5281/zenodo.11184359}
}
This code was developed at the Institute of Applied and Computational Mathematics (ACoM) at RWTH Aachen University.
This code is a result of research performed in the research unit "Structure-Preserving Numerical Methods for Bulk- and Interface Coupling of Heterogeneous Models (SNuBIC)"
This project has benefited from funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through the research unit FOR 5409 "Structure-Preserving Numerical Methods for Bulk- and Interface Coupling of Heterogeneous Models (SNuBIC)" (project number 463312734).