# GPU programming

- Institution: CERN
- Department: CERN openlab summer student lecture programme
- Speaker: Stephan Hageboeck
- Year: 2025
- Language: English
- Subjects: Computer science
- Source: [CERN](https://videos.cern.ch/record/3022559)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

Abstract

In this lecture, we will look into the basics of GPU computing to understand in which circumstances the usage of GPUs is beneficial for scientific computing. Using the Nvidia CUDA GPUs as examples, will learn how the hardware works, which guides us towards how it has to be programmed.

Requirements

Students should have written basic C/C++ programs before, and should be familiar with pointers and arrays and/or vectors of data.

Hands on: We have the option to play with a few basic CUDA applications. There's three ways in which you can participate:

Linux / Mac laptop with ssh.

Any laptop and a browser using SWAN.

Please create a cernbox if you haven't done so. After logging in to CERN, just visit https://cernbox.cern.ch, and it will be created automatically.

Then, register at https://e-groups.cern.ch/e-groups/EgroupsSubscription.do?egroupName=openlab-gpu-lecture25

This has to be done one day before the hands-on

Team programming. If the two above are not for you, we will team up and work together.

Bio

Stephan obtained a PhD in particle physics, searching for decays of the Higgs boson with the ATLAS detector. Afterwards, he worked for the ROOT project at CERN, focussing on high-throughput computing and RooFit, a package for fitting and statistical analysis of data. Now, Stephan is a computing engineer in CERN IT's innovation group, focussing on GPU computing for high-energy physics.

Please note that pictures and videos might be taken during the event. The pictures and videos might be used for communication about the event. By joining the lecture, you are agreeing to being featured in these communication actions. .

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## Lectures

1. [GPU programming](https://invisiblenetwork.ai/learn/cern/3022559/a2bdd0057c80), 1 h 37 min (CERN's player)