Best practices for Data Science on HPC

There are many good reasons to run data science workloads on a High Performance Computing (HPC) system. However, the transition from a laptop to an HPC system can be daunting. This training will help you make that transition.

You will also learn about potential pitfalls and how to avoid them. This training is not just about the good parts, but also about how to avoid the bad parts. 

Learning Outcomes 

• be able to judge when to switch to an HPC environment;

• be able to prepare your environment for R and Python;

• be able to run a job on an HPC cluster that uses that environment;

• be able to determine how long your computation will take;

• be able to determine how much memory your computation will need;

• be able to estimate the efficiency of your computation;

• know the basics of how to run your computations efficiently;

• know when it makes sense to use parallelization;

• understand the basics and pitfalls of I/O on HPC systems;

• are aware of potential pitfalls and how to avoid them. 

!!IMPORTANT: If you wish to participate on-campus, please make sure to send a mail to martial.luyts@kuleuven.be (mandatory!!) before October 28th, 2025. Only a maximum of 40 participants can register on-campus. If no mailing is send by you after registration & before October 28th, 2025, you will be automatically registered as online participant.