SPACK - migration to setup without environment

Having worked with spack environments for some time, we have encountered several severe issues which have convinced us that we need to find a more practical way of maintaining software packages on VSC. In particular we came across the following drawbacks:

  • hard to read and lengthy output of spack find commands.
  • long response times of all spack commands when the number of installed packages grows.
  • difficult and for practical purposes impossible maintenance of a consistent database of software packages (spack.yaml, spack.lock files).
  • unresolvable discrepancies between the list of software packages found in spack as compared to those found in modules.
  • unreliable concretisation procedure (discrepancies between what is shown in spack spec -I .. and what is actually installed with spack install …).

There are now three separate spack installation trees corresponding to the CPU/GPU architectures on VSC:

  • skylake - Intel CPUs; works on Intel Skylake and Cascadelake CPUs
  • zen - AMD CPUs; works on Zen 2 and 3 CPUs
  • cuda-zen - AMD CPUs + NVIDIA GPUs; works on all nodes equipped with graphics cards

By default the spack installation tree suitable for the current compute/login node is activated and will be indicated by a prefix on the command line, e.g.:

zen [user@l51 ~]$


Please note that the prefix (e.g. zen) does not mean that a python virtual environment is loaded.

The installation trees can be found in:


Only the software packages and modules of the currently active tree (denoted by the prefix) will be searched by spack find/load and module avail/load commands.

It is easily possible to switch between installation trees with the short commands cuz,zen, and sky defined as aliases:

alias cuz='spackup cuda-zen'
alias sky='spackup skylake'
alias zen='spackup zen'

Packages depending on GPU, like cuda are only installed in the cuda-zen tree. If you want to compile software intended to run on GPU nodes, you need to:

  1. login on a VSC-5 login node (or a VSC-5 compute node).
  2. type cuz switch to cuda-zen.
  3. compile your code.
zen [userl51 ~]$ cuz
cuda-zen [userl51 ~]$ 
... build your software ...

The commands cuz/zen/sky ultimately call the shell function spackup <arch> which will:

  • set PATH
  • set PS1 prompt
  • source /path/to/spack/instance/share/spack/

You can view the shell function spackup with type spackup, or take a look at the whole script at /etc/profile.d/

If you need to find a list of packages or modules which correspond to the software you have been using until now, you can use the shell function spack search to do that:

zen [user@l51 ~] spack search <hash>

where <hash> is the 7 character hash of the package that you see at the end of the module name or in the output of spack find -l <package>.

Let's assume you have used this netcdf-c module:


which can be found with spack find -l netcdf-c %gcc as:

jsfjwaz netcdf-c@4.8.1

You can use the migration script to find netcdf-c installations with identical build options:

zen [user@l51 ~]$ spack search jsfjwaz

==> The hash 'jsfjwaz7qp52fjxfeg6mbhtt2lj3l573' refers to 'netcdf-c' from 'vsc5' with parameters:
     netcdf-c ~dap~fsync~hdf4~jna+mpi~parallel-netcdf+pic+shared

==> Searching similar 'netcdf-c' modules in installation 'skylake' ...

-- /opt/sw/skylake/spack-0.19.0/share/spack/modules/linux-almalinux8-skylake_avx512 --

==> Load any one of these packages with 'module load mypackage' e.g.:
     module load netcdf-c/4.9.0-intel-2021.7.1-k2p5vx2

==> Get detailed package info with 'spack find -lvd mypackage' e.g.:
     spack find -lvd /k2p5vx

To search for packages in a different spack tree you can just change to that tree with cuz/sky/zen, and then run spack search there.

For example to search in the cuda-zen spack tree:

zen [user@l51 search]$ cuz
cuda-zen [user@l51 search]$ spacksearch jsfjwaz

==> The package hash jsfjwaz refers to netcdf-c and belongs to vsc5 as:
     netcdf-c ~dap~fsync~hdf4~jna+mpi~parallel-netcdf+pic+shared

==> Searching similar netcdf-c modules at cuda-zen...



This approach is not recommended and we will no longer maintain the spack environments or install new packages there

You may continue to use modules from the spack environments skylake and zen3 by adjusting the MODULEPATH variable:

On zen3

export MODULEPATH=/opt/sw/vsc4/VSC/Modules/TUWien:/opt/sw/vsc4/VSC/Modules/Intel/oneAPI:/opt/sw/vsc4/VSC/Modules/Parallel-Environment:/opt/sw/vsc4/VSC/Modules/Libraries:/opt/sw/vsc4/VSC/Modules/Compiler:/opt/sw/vsc4/VSC/Modules/Debugging-and-Profiling:/opt/sw/vsc4/VSC/Modules/Applications:/opt/sw/vsc4/VSC/Modules/p71545::/opt/sw/spack-0.17.1/var/spack/environments/zen3/modules/linux-almalinux8-zen:/opt/sw/spack-0.17.1/var/spack/environments/zen3/modules/linux-almalinux8-zen2:/opt/sw/spack-0.17.1/var/spack/environments/zen3/modules/linux-almalinux8-zen3

On skylake

export MODULEPATH=/opt/sw/vsc4/VSC/Modules/TUWien:/opt/sw/vsc4/VSC/Modules/Intel/oneAPI:/opt/sw/vsc4/VSC/Modules/Parallel-Environment:/opt/sw/vsc4/VSC/Modules/Libraries:/opt/sw/vsc4/VSC/Modules/Compiler:/opt/sw/vsc4/VSC/Modules/Debugging-and-Profiling:/opt/sw/vsc4/VSC/Modules/Applications:/opt/sw/vsc4/VSC/Modules/p71545:/opt/sw/vsc4/VSC/Modules/p71782::/opt/sw/spack-0.19.0/var/spack/environments/skylake/modules/linux-almalinux8-x86_64:/opt/sw/spack-0.19.0/var/spack/environments/skylake/modules/linux-almalinux8-skylake


This approach is not recommended and we will no longer maintain the spack environments or install new packages there

You may also continue to work with the spack environments. If you wish to do so you need the following commands:

On zen3

export SPACK_ROOT=/opt/sw/spack-0.17.1
source /opt/sw/spack-0.17.1/share/spack/
spacktivate zen3

On skylake

export SPACK_ROOT=/opt/sw/spack-0.19.0
source /opt/sw/spack-0.19.0/share/spack/
spacktivate skylake

Some module have prerequisites which need to be loaded in addition to the module. You can check if a module has prerequisites with module show <module>, e.g.:

zen [user@l51 ~]$ module show py-numpy/1.23.4-gcc-12.2.0-xbac5zw |grep prereq
prereq          openblas/0.3.21-gcc-12.2.0-gcn6jxp
prereq          py-setuptools/59.4.0-gcc-12.2.0-qphisr6
prereq          python/3.9.15-gcc-12.2.0-my6jxu2

These prerequisites can be loaded together with the module automatically module load –auto <module>, e.g.:

zen [user@l51 ~]$ module load --auto py-numpy/1.23.4-gcc-12.2.0-xbac5zw
Loading py-numpy/1.23.4-gcc-12.2.0-xbac5zw
  Loading requirement: openblas/0.3.21-gcc-12.2.0-gcn6jxp python/3.9.15-gcc-12.2.0-my6jxu2 py-setuptools/59.4.0-gcc-12.2.0-qphisr6

Loading a module does no longer automatically set the LD_LIBRARY_PATH environment variable, as with some software packages this has lead to conflicts with system libraries. If you have to set LD_LIBRARY_PATH you may use:


Alternatively you may have to set it to specific paths where the needed libraries can be found.

  • doku/spack-transition.txt
  • Last modified: 2023/05/17 14:48
  • by msiegel