Spack

Advanced Installation || pip || uv || pixi || conda || Spack

Install libEnsemble using the Spack distribution:

spack install py-libensemble

The above command will install the latest release of libEnsemble with the required dependencies only. Other optional dependencies can be specified through variants. The following line installs libEnsemble version 1.5.0 with some common variants (e.g., using APOSMM):

spack install py-libensemble @1.5.0 +mpi +scipy +mpmath +petsc4py +nlopt

The list of variants can be found by running:

spack info py-libensemble

On some platforms you may wish to run libEnsemble without mpi4py, using a serial PETSc build. This is often preferable if running on the launch nodes of a three-tier system:

spack install py-libensemble +scipy +mpmath +petsc4py ^py-petsc4py~mpi ^petsc~mpi~hdf5~hypre~superlu-dist

The installation will create modules for libEnsemble and the dependent packages. These can be loaded by running:

spack load -r py-libensemble

Any Python packages will be added to the PYTHONPATH when the modules are loaded. If you do not have modules on your system you may need to install lmod (also available in Spack):

spack install lmod
. $(spack location -i lmod)/lmod/lmod/init/bash
spack load lmod

Alternatively, Spack could be used to build the serial petsc4py, and Conda could use this by loading the py-petsc4py module thus created.

Hint: When combining Spack and Conda, you can access your Conda Python and packages in your ~/.spack/packages.yaml while your Conda environment is activated, using CONDA_PREFIX For example, if you have an activated Conda environment with Python 3.11 and SciPy installed:

packages:
python:
    externals:
    - spec: "python"
    prefix: $CONDA_PREFIX
    buildable: False
py-numpy:
    externals:
    - spec: "py-numpy"
    prefix: $CONDA_PREFIX/lib/python3.11/site-packages/numpy
    buildable: False
py-scipy:
    externals:
    - spec: "py-scipy"
    prefix: $CONDA_PREFIX/lib/python3.11/site-packages/scipy
    buildable: True

For more information on Spack builds and any particular considerations for specific systems, see the spack_libe repository. In particular, this includes some example packages.yaml files (which go in ~/.spack/). These files are used to specify dependencies that Spack must obtain from the given system (rather than building from scratch). This may include Python and the packages distributed with it (e.g., numpy), and will often include the system MPI library.