About
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 Nvidia CUDA GPUs as examples, we 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, 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 for the following group https://groups-portal.web.cern.ch/group/openlab-gpu-lectures
This has to be done several hours before the hands-on, because extra GPUs will be reserved for our lecture
Team programming. If the two above are not for you, we will team up and work together.
Bio
The talk
Credits and licence
- Institution
- CERN
- Speaker
- Stephan Hageboeck
- Year
- 2026
- Language
- English
- Subjects
- Computer science
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed