Installation

To install MadNLP, simply proceed to

pkg> add MadNLP

Note

The default installation comes is shipped only with two linear solvers (Umfpack and Lapack), which are not adapted to solve the KKT systems arising in large-scale nonlinear problems. We recommend using a specialized linear solver to speed-up the solution of the KKT systems.

In addition to Lapack and Umfpack, the user can install the following extensions to use a specialized linear solver.

HSL linear solver

Obtain a license and download HSL_jll.jl from https://licences.stfc.ac.uk/product/julia-hsl. There are two versions available: LBT and OpenBLAS. LBT is the recommended option for Julia >= v1.9. Install this download into your current environment using:

import Pkg
Pkg.develop(path = "/full/path/to/HSL_jll.jl")

If the user has already compiled the HSL solver library, one can simply override the path to the artifact by editing ~/.julia/artifacts/Overrides.toml

# replace HSL_jll artifact /usr/local/lib/libhsl.so
ecece3e2c69a413a0e935cf52e03a3ad5492e137 = "/usr/local"

Mumps linear solver

Mumps is an open-source sparse linear solver, whose binaries are kindly provided as a Julia artifact. Installing Mumps simply amounts to

pkg> add MadNLPMumps

Pardiso linear solver

To use Pardiso, the user needs to obtain the Pardiso shared libraries from https://panua.ch/, provide the absolute path to the shared library:

julia> ENV["MADNLP_PARDISO_LIBRARY_PATH"] = "/usr/lib/libpardiso600-GNU800-X86-64.so"

and place the license file in the home directory. After obtaining the library and the license file, run

pkg> build MadNLPPardiso

The build process requires a C compiler.