Modules and applications

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On the cluster, we provide many centrally installed software and for some software even multiple versions. To configure the environment for a particular software version, we use modules. Modules configure your current computing environment (PATH, LD_LIBRARY_PATH, MANPATH, etc.) to make sure all required binaries and libraries are found. We employ the following Modules packages on the cluster: LMOD Modules

Modules commands

Here are the most frequently used module commands.

List all modules that match the given module name, e.g., list all available Python

$ module spider python

You can also use avail to see the one available with the current module loaded:

$ module avail python

List all currently loaded modules

$ module list

Currently Loaded Modules:
 1) gcc/12.2.0   2) stack/2024-06

Other commonly used module commands

module                    # get info about module sub-commands
module avail              # List all modules available on the cluster
module key keyword        # list all modules whose description contains keyword
module help name          # get information about module name
module show name          # show what module name does (without loading it)
module unload name        # unload module name
module purge              # unload all modules at once

You can also search through the full stack for a package with

module spider             # report all modules
module spider name        # report all versions of the module name
module --show_hidden spider name  # Show also the hidden modules

Please note that you first need to load a stack. The stack determines the GCC version of the packages that can be loaded.

• stack/2024-04 -> GCC 8.5.0
• stack/2024-06 -> GCC 12.2.0

The 2024-06 also contains packages for Intel OneAPI 2023.2.0

module load stack/2024-06 intel-oneapi-compilers/2023.2.0

All available modules are listed on our wiki.

Where are applications installed?

Centrally installed Central applications are installed in /cluster/software Applications that are needed by many users should be installed centrally, like compilers and libraries Visible and accessible to all users via modules Installed and maintained by cluster support Commercial licenses provided by the IT shop of ETH or by research groups

In $HOME Users can install additional applications in their home directory, but only if the quotas (space: 50GB, files/directories: 500'000) are not exceeded Avoid anaconda installations as they often conflict with the files/directories quota. Alternatively, you can create a Python virtual environment. For Python and R, packages can easily be installed locally, e.g., for Python $ pip3 install --user packagename

The structure of LMOD Modules

LMOD Modules use a hierarchy of modules with three layers to avoid conflicts when multiple modules are loaded at the same time. The core layer contains software which are independent of compilers and MPI libraries, e.g., commercials software which come with their own runtime libraries $ module load comsol/5.6 The stack layer contains software which are dependent of compilers. $ module load stack/2024-06 hdf5/1.14.3 The MPI layer contains software which are dependent of compilers and MPI libraries $ module load stack/2024-06 openmpi/4.1.6 openblas/0.3.24

Modules for GPUs

We have installed a Python module which is linked with CUDA and NCCL libraries and contains machine learning / deep learning packages such as scikit-Learn, TensorFlow and Pytorch. This module can be loaded with the following commands:

$ module load stack/2024-06 python_cuda/3.11.6

You can also find and load CUDA, cuDNN and NCCL libraries available on the cluster matching your needs.

 $ module load stack/2024-06
 $ module avail cuda
 -------- /cluster/software/stacks/2024-06/spack/share/spack/lmod/linux-ubuntu22.04-x86_64/gcc/12.2.0 ------
   cuda/11.8.0    cuda/12.1.1 (D)

Application lists

Ubuntu:

• Euler - Ubuntu software stacks

CentOS (deprecated):

• Euler - New software stack

Example

• Python virtual environment

Further reading

• User guide: Setting up your environment
• Setting up a software stack for a research group
• Creating a local module directory
• Unpacking RPM packages in users space

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