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How to Install HSL

  • The ma27 linear solver will be installed as part of the HSL installation process.
  • The official installation document can be found here. This guide provides a more detailed version of the installation process.

1. Clone the ThirdParty-HSL Repository

From any directory, run the following commands to clone the ThirdParty-HSL repository and navigate into it:

git clone [email protected]:coin-or-tools/ThirdParty-HSL.git
cd ThirdParty-HSL

2. Obtain Coin-HSL Sources

  1. Go to the STFC Portal.

  2. Click ORDER NOW for the HSL Academic Licence. You will need to create an account if you don’t have one.

  3. After logging in, download the appropriate Coin-HSL archive from your downloads section.

  4. Place the downloaded archive in the ThirdParty-HSL/ directory and unpack the tarball:

    gunzip coinhsl-x.y.z.tar.gz
tar xf coinhsl-x.y.z.tar

  5. Rename the directory coinhsl-x.y.z to coinhsl or set up a symbolic link:

    mv coinhsl-x.y.z coinhsl

    OR

    ln -s coinhsl-x.y.z coinhsl

3. Install Coin-HSL

You can install Coin-HSL either system-wide or in a specific folder.

System-wide Installation

  1. Configure the installation. You can see available options with ./configure --help.

    ./configure

  2. Build the HSL library with:

    make

  3. Install the HSL library and header files with:

    make install

    Note: You may need to use sudo for the above commands (e.g., sudo ./configure, sudo make, sudo make install).

Installation in a Specific Folder

This method is useful if you are on a shared machine, like a server, or if you do not have sudo access.

  1. Let's say you want to install it to $HOME/local.

  2. Ensure that $HOME/local exists. If not, create it:

    mkdir -p $HOME/local

  3. Configure the installation with the --prefix option:

    ./configure --prefix=$HOME/local

  4. Build and install:

    make
make install

  5. Update your environment variables by adding the following lines to your ~/.bashrc and then source it:

  • export PATH=$HOME/local/bin:$PATH

  • export LD_LIBRARY_PATH=$HOME/local/lib:$LD_LIBRARY_PATH

    echo 'export PATH=$HOME/local/bin:$PATH' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=$HOME/local/lib:$LD_LIBRARY_PATH' >> ~/.bashrc
source ~/.bashrc

4. Relink libcoinhsl.so to libhsl.so

This step is required to link HSL to Ipopt.

  • System-wide:

    sudo ln -s /usr/local/lib/libcoinhsl.so /usr/local/lib/libhsl.so

  • Specific folder:

    ln -s $HOME/local/lib/libcoinhsl.so $HOME/local/lib/libhsl.so

5. Validate the Installation

If you have cyipopt installed, you can validate the installation with the following Python script:

from cyipopt import minimize_ipopt

objective = lambda x: (x[0] - 1) ** 2 + (x[1] - 2.5) ** 2
gradient = lambda x: [2 * (x[0] - 1), 2 * (x[1] - 2.5)]

x0 = [2, 2]
res = minimize_ipopt(objective, x0, jac=gradient, options={"linear_solver": "ma27"})

print(res)
  • If HSL is installed successfully along with ma27, you will see:
******************************************************************************
This program contains Ipopt, a library for large-scale nonlinear optimization.
 Ipopt is released as open source code under the Eclipse Public License (EPL).
         For more information visit https://github.com/coin-or/Ipopt
******************************************************************************

 message: b'Algorithm terminated successfully at a locally optimal point, satisfying the convergence tolerances (can be specified by options).'
 success: True
  status: 0
     fun: 0.0
       x: [ 1.000e+00  2.500e+00]
     nit: 1
    info:     status: 0
                   x: [ 1.000e+00  2.500e+00]
                   g: []
             obj_val: 0.0
              mult_g: []
            mult_x_L: [ 0.000e+00  0.000e+00]
            mult_x_U: [ 0.000e+00  0.000e+00]
          status_msg: b'Algorithm terminated successfully at a locally optimal point, satisfying the convergence tolerances (can be specified by options).'
    nfev: 7
    njev: 3
  • Otherwise, you will see:
 message: b'Invalid option encountered.'
 success: False
  status: -12
     fun: 0.0
       x: [ 2.000e+00  2.000e+00]
     nit: 0
    info:     status: -12
                   x: [ 2.000e+00  2.000e+00]
                   g: []
             obj_val: 0.0
              mult_g: []
            mult_x_L: [ 0.000e+00  0.000e+00]
            mult_x_U: [ 0.000e+00  0.000e+00]
          status_msg: b'Invalid option encountered.'
    nfev: 0
    njev: 0