MathWorks MATLAB R2014a and above, or GNU Octave 5.1 and above.
MATLAB R2017a has improved handling of negative definite matrices with in the "backslash" operator. We recommend using this version or later ones for optimal performance.
Note that MATLAB R2017a and R2017b also contain a bug in "backslash" that can cause extraordinarily slow computations with certain block structured matrices. Use
spparms('usema57', 0);
to fix this, or upgrade to at least R2017b update 5.
The mess_get_* model (down)loader functions require at least R2019b,
since MATLAB ships its own SSL certificates and those are outdated in
the older versions.
MATLAB R2021a has proven to be up to 20% faster than predecessors in our continuous integration tests. So upgrading is highly recommended.
Some of the demonstration examples rely on MATLAB style ODE solvers with proper support for non-trivial mass matrices. We highly recommend Octave 5.2 and above with proper SUNDIALS support compiled in.
Octave 6.2.0 based on OpenBLAS has shown to be competitive with MATLAB versions released around the same time for our continuous integration tests.
The splitting schemes further need Octave to be compiled with FFTW support.
1.) Some functions can benefit from the Control Systems Toolbox in MATLAB or the
Control package in Octave. More precisely, whenever projected Lyapunov or
Riccati equations are solved, we use lyap, care or icare if available,
but fallbacks exist in case any of those is not found.
(affected files: helpers/mess_solve_projected_eqn.m)
2.) Factorizations of symmetric and (semi)definite projected solutions in the
context of 1.) can benefit from the file cholp.m from the Test
Matrix Computation Toolbox by Nicholas J. Higham.
(affected files: helpers/mess_solve_projected_eqn.m)