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Software and package installation on Bianca

Objectives

  • Understand principles how to install software and packages yourself
  • Understand what containers are
    • understand difference of Docker and Apptainer/Singularity
  • Know by doing how to install software, packages and libraries from at least one of the following
    • ... using Conda
    • ... using Python packages with pip
    • ... using R packages
    • ... using Apptainer/Singularity
  • Understand how to build from source
Notes for teachers

Teaching goals:

  • The learners have explored the UPPMAX documentation
  • The learners have installed a package (R, python or julia)
  • The learners understand how to install own software

Lesson plan:

gantt
  title IDEs
  dateFormat X
  axisFormat %m
  Introduction: intro, 0, 10m
  Vote on wih IDE: vote, after intro, 5m
  Exercise with personal favorite package: crit, exercise, after vote, 20m
  Feedback: feedback, after exercise, 10m
  Installing software and developing: monologue, after feedback, 5m
  Break: milestone, after monologue

The module system

Forgot how to use the module system?

See the basic Bianca course page 'Using the module system'.

  • There is a lot of programs and tools installed as modules on Bianca.
  • These have typically been installed on Rackham and is synced over to Bianca a couple of times per day.
  • You can request installations but that may take several days or weeks to be handled by the application experts at UPPMAX.
  • But you may be able to do installations yourself. Here the use of Rackham comes handy because of the:
    • internet connection
    • the computer architecture is somewhat similar such that precompiled binaries or compiled programs (x86_64) on Rackham will most often work also on Bianca.
    • you can use the wharf to transfer installation files and packages to Bianca from Rackham

Content

  • Principles of software installation on Bianca
    • From source
    • From binary
    • Containers
  • Principles of packages on Bianca
  • Exercise: test yourself in EITHER
    • R
    • Conda
    • Python/pip
    • Julia
  • Feedback
  • Development and Git on Bianca

Install software yourself

  • If not available on Bianca already (like Conda repositories) you may have to use the wharf to install your tools
  • Alternatively let an Application Expert install the tool as a module.

Typical workflow for installation

  • Download the
    • source code or
  • binary (Linux on x86 and 64-bit) to Rackham first
  • Transfer to the wharf
  • Then, either
    • You can install in your home directory.
      • This is handy for personal needs and low numbers of files — i.e. not Conda.
    • Usually better to install in project directory.
      • This way the project contains both data and software — good for reproducibility, collaboration, and everyone's general sanity.
  • Binaries for Linux on x86 and 64-bit should be able to be run directly as it is, see the software specific installation documentation.
  • or build from source, see next session.

Build from source

About CPU hardware on Bianca
  • Architecture: x86_64
    • Intel Xeon E5-2630 v3 Huawei XH620 V3 nodes
    • Advanced Vector Extensions 2 (AVX2)
  • CPU op-mode(s): 32-bit, 64-bit
  • Byte Order: Little Endian
  • CPU(s): 16
  • Thread(s) per core: 1
  • Core(s) per socket: 8
  • Socket(s): 2
  • NUMA node(s): 2
  • Model name: Intel Core Processor (Haswell, no TSX, IBRS)
  • CPU MHz: 2394.446
  • For more info, type: lscpu in the terminal

Containers

Info

  • Containers let you install programs without needing to think about the computer environment, like
    • operative system
    • dependencies (libraries and other programs) with correct versions
  • 2(3) types
    • Singularity/Apptainer
    • Docker that does not work on HPC-systems
      • But docker images can be used byt Singularity and Apptainer
  • Everything is included
  • Draw-backs
    • you install also things that may be already installed
    • therefore, probably more disk space is needed

Packages and libraries to scripting programs

  • Python, R and Julia all have some centrally installed packages that are available from the modules.
  • R has a special module called R_packages, and some Machine Learning python packages are included in the python_ml_packages module.
  • If not found there you can try to install those by yourself.

Info

  • "Install packages or not? Check it!"

Check and install packages!

R

  • On UPPMAX the module R_packages is an omnibus package library containing almost all packages in the CRAN and BioConductor repositories.
  • As of 2023-05-31, there were a total of 23100 R packages installed in R_packages/4.2.1.
    • A total of 23109 packages were available in CRAN and BioConductor, and 23000 of these were installed in R_packages/4.2.1
    • The additional 100 R packages available in this module were installed from the CRAN/BioConductor archives, or were hosted on github, gitlab or elsewhere.

Chances are good the R packages you need are already available once you load this module. You can quickly check by loading it:

$ ml R_packages/4.2.1

Then within R, try loading the package you want, like glmnet:

library(glmnet)

Is it not there? Then proceed!

Installation principle

  • install on Rackham
  • sync to wharf
  • move the files on Bianca

Python and other

  • Check python versions: ml avail python
  • Check the help output from: ml help python/3.9.5 at UPPMAX
  • Load a python version, like: ml python/3.10.8
  • from the Python shell with the import command
  • from BASH shell with the pip list command

Is it not there? Then proceed!

Tip Python packages

  • Try Conda first directly on Bianca. We have mirrored all major Conda repositories directly on UPPMAX, on both Rackham and Bianca. These are updated every third day.
  • If you want to keep number of files down, use PyPI (pip), but then you need to use Rackham and the wharf.

Conda

  • We have mirrored all major Conda repositories directly on UPPMAX, on both Rackham and Bianca. These are updated every third day.

Python packages with pip

Installation principle

  • install on Rackham
    • pip install --user <package>
    • python setup.py install --user or --prefix=<path>
  • sync to wharf
  • move the files on Bianca to correct place
  • you may have to update $PYTHONPATH

Julia packages

  • At UPPMAX there is a central library with installed packages.
  • This is good, especially when working on Bianca, since you then do not need to install via the wharf.
  • A selection of the Julia packages and libraries installed on UPPMAX are:
    CSV
    CUDA
    MPI
    Distributed
    IJulia
    Plots
    PyPlot
    DataFrames
    

Installation principle

  • install on Rackham
  • sync to wharf
  • move the files on Bianca

Exercise 20 min

Pick one of the following topics!

Discussion

  • Did it work out well?
  • Any questions?
  • Any input?

Own development and Git

Keypoints

  • You have got an overview of the procedures to install packages/libraries and tools on Bianca through the wharf
  • If you feel uncomfortable or think that many users would benefit from the software, ask the support to install it.