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On-site HPC trainings and tutorials

We propose periodical on-site events for our users. They are free of charge and can be attended by anyone from the University of Luxembourg faculties and interdisciplinary centers. Additionally, we also accept users from LIST, LISER and LIH. If you are part of another public research center, please contact us.

Forthcoming events

  • HPC School for beginners - July 2024, 1st-2nd, 1.040, MNO - Belval Campus
  • Python HPC School - March 2024, 27-28th, 1.030 MNO - Belval Campus

HPC School for beginners

This event aims to equip you with essential skills and knowledge to embark on your High-Performance Computing journey. The event is organized monthly and is composed of two half days (usually 9am-12pm).

Feel free to only attend the second day session if:

  • You can connect to the ULHPC
  • You are comfortable with the command line interface

Limited spots available per session (usually 30 max).

Upcoming sessions:

  • Date: July 2024, 1st-2nd
  • Time: 9am to 12pm (both days).
  • Location: 1.040, MNO - Belval Campus.

Morning 1 - Accessing the Cluster and Command Line Introduction

Learn how to access the HPC cluster, set up your machine, and navigate the command line interface effectively. Gain confidence in interacting with the cluster environment.

Morning 2 - Understanding HPC Workflow: Job Submission and Monitoring

Explore the inner workings of HPC systems. Discover the process of submitting and managing computational tasks. Learn how to monitor and optimize job performance.

Python HPC School

In this workshop, we will explore the process of improving Python code for efficient execution. Chances are, you 're already familiar with Python and Numpy. However, we will start by mastering profiling and efficient NumPy usage as these are crucial steps before venturing into parallelization. Once your code is fine-tuned with Numpy we will explore the utilization of Python's parallel libraries to unlock the potential of using multiple CPU cores. By the end, you will be well equipped to harness Python's potential for high-performance tasks on the HPC infrastructure.

Target Audience Description

The workshop is designed for individuals who are interested in advancing their skills and knowledge in Python-based scientific and data computing. The ideal participants would typically possess basic to intermediate Python and Numpy skills, along with some familiarity with parallel programming. This workshop will give a good starting point to leverage the usage of the HPC computing power to speed up your Python programs.

Upcoming sessions

Limited spots available per session (usually 30 max).

  • Date: March, 2024, 27th and 28th.
  • Time: 10h to 12h and 14h to 16h (both days).
  • Location: MNO 1.030. - Belval campus

First day – Jupyter notebook on ULHPC / profiling efficient usage of Numpy


  • Setting up a Jupyter notebook on an HPC node - 10am to 11am
  • Taking time and profiling python code - 11am to 12pm
  • Lunch break - 12pm to 2pm
  • Numpy basics for replacing python loops for efficient computations - 2pm to 4pm


  • Having an HPC account to access the cluster.
  • Basic knowledge on SLURM (beginners HPC school).
  • A basic understanding of Python programming.
  • Familiarity with Jupyter Notebook (installed and configured).
  • A basic understanding of Numpy and linear algebra.

Second day – Improving performance with python parallel packages


  • Use case understanding and Python implementation - 10am to 10:30am
  • Numpy implementation - 10:30am to 11am
  • Python’s Multiprocessing - 11am to 12pm
  • Lunch break - 12pm to 2pm
  • PyMP - 2pm to 2:30pm
  • Cython - 2:30pm to 3pm
  • Numba and final remarks- 3pm to 4pm


  • Having an HPC account to access the cluster.
  • Basic knowledge on SLURM (beginners HPC school).
  • A basic understanding of Python programming.
  • Familiarity with Jupyter Notebook (installed and configured).
  • A basic understanding of Numpy and linear algebra.
  • Familiarity with parallel programming.

Conda environment management for Python and R

The creation of Conda environments is supported in the University of Luxembourg HPC systems. But when Conda environments are needed and what tools are available to create Conda environments? Attend this tutorial if your projects involve R or Python and you need support with installing packages.

The topics that will be covered include:

  • how to install packages using the facilities available in R and Python,
  • how to document and exchange environment setups,
  • when a Conda environment is required for a project, and
  • what tools are available for the creation of Conda environments.

Upcoming sessions

  • Mar. 2024 (please await further announcements regarding specific dates)

Introduction to numerical methods with BLAS

This seminar covers basic principles of numerical library usage with BLAS as an example. The library mechanisms for organizing software are studied in detail, covering topics such as the differences between static and dynamic libraries. The practical sessions will demonstrate the generation of library files from source code, and how programs can use library functions.

After an overview of software libraries, the BLAS library is presented, including the available operations and the organization of the code. The attendees will have the opportunity to use functions of BLAS in a few practical examples. The effects of caches in numerical library performance are then studied in detail. In the practical sessions the attendees will have the opportunity to try cache aware programming techniques that better exploit the performance of the available hardware.

Overall in this seminar you learn how to:

  • compile libraries from source code,
  • compile and link code that uses numerical libraries,
  • understand the effects of caches in numerical library performance, and
  • exploit caches to leverage better performance.

Upcoming sessions

  • No sessions are planned at the moment. Future sessions will be announced here, please wait for announcements or contact the HPC team via email to express your interest.

Last update: July 19, 2024