Users own software
Researchers need to recompile their own manually built software that has been built previously on Setonix. This is necessary because the CPE has newer versions of various libraries, new paths to libraries (specifically MPICH) to ensure the best possible performance and avoid issues. This process also might require an update to any modules loaded since versions will change.
In general, your software installed using Conda/Mamba should not be affected by the updates. The exception would be if you have installed software using the
conda install --use-local option. The
--use-local option uses local files to do the package installation, rather than the external channels that Conda typically uses (e.g. bioconda of conda-forge). The paths of the local files may have changed, and would need to up rebuilt using the updated paths. In general, the default option is to use the external channels such and conda-forge, so we do not expect this to impact many users.
The version of R provided as a module has changed from 4.1.0 to 4.2.2. This may cause issues with your installed R libraries and packages and require you to update your installed versions to be compatible with this newer version of R. We have provided an example to largely automate the re-installation of your software against the new version of R. This may not successfully reinstall all of your packages, but it should remove much of the burden of migrating to the newer R version.
Step one is to collect the packages you had installed with the previous version of R and save them to a CSV file for use in the next step.
Step two is to create a batch script to send to SLURM to do the installation based on the R script we will prepare in step three.
Step three is to create the R script that will do the installation for you. This uses the CSV file we created in step one. The R script will use the number of CPUs you provided it in the batch script (in this example, that would be four). This script will also tell you which packages were successful or unsuccessful in the SLURM log file.
If you find that you really need a specific version of R, you might need to install your own version of R in your
/software partition. Although there are many ways to install R, one handy way can be using Conda/Mamba, which can install R packages for you as well.
Python virtual environment
Python virtual environments will need to be rebuilt if the environment made use of Pawsey provided modules to deploy the environment. The major one is that the python module is now 3.10.10. The python provided in the previous software installation will still be present but will not be available by default unless one loads the pawsey environment module associated with the previous deployment,
pawseyenv/2022.11 . We then suggest activating the environment to extract the installed packages.
Researchers that installed software with
spack/0.17.0 will need to load the older software stack to load this particular version of spack and query it to get the previously installed packages. The steps involved are
- Load the old pawsey environment module and older version of spack
- query spack to find all the old builds in your software space. For users in multiple projects, this will require querying each project (see here for how to change projects)
- generate scripts to see if specifications are acceptable and then rebuild with newer spack
Pawsey provides a script to migrate software stacks called
spack_generate_migration_scripts.sh. This script will generate the scripts that can be used to check specifications and run the installation, called
spack.install.sh respectively. These scripts may need to be edited to get the desired results as they will endeavour to build the software with the same build time options but not necessarily the same dependencies.
Once you are satisfied with the new builds, please clean up the old builds