| Start date: | 25 Jun 2024, 09:00 (CEST) | Entry level: | Basic | |
| End date: | 26 Jun 2024, 12:30 (CEST) | Subject area: | Machine learning | |
| Location: | ONLINE (Zoom) | Topics: | Deep learning | |
| Language: | English | Target audience: | Academia, industry, public sector | |
| Price: | Free (for eligible participants) | Organizers: | EuroCC AT, DE(GCS), ME, SE & NVIDIA | |
| HLRS & JSC & LRZ & RISE & UDG & VSC |
Overview
The AI for Science Bootcamp provides a step-by-step overview of the fundamentals of deep neural networks and walks attendees through the hands-on experience of building and improving deep learning models for applications related to scientific computing and physical systems defined by differential equations. The material will cover more advanced topics such as physics-informed neural networks (PINNs) and operator learning and make use of tools like NVIDIA Modulus to develop and train the models. This online bootcamp is a hands-on learning experience where you will be guided through step-by-step instructions with teaching assistants on hand to help throughout.
This Bootcamp, which will be hosted virtually for two half-days on June 25–26, is co-organized by the High-Performance Computing Center Stuttgart (HLRS), Jülich Supercomputing Centre (JSC), Leibniz Supercomputing Centre (LRZ), Vienna Scientific Cluster (VSC), University of Donja Gorica (UDG), Research Institutes of Sweden (RISE), Linköping University (LiU), OpenACC organization, and NVIDIA for EuroCC Austria, EuroCC@GCS, EuroCC Montenegro, and EuroCC Sweden, all National Competence Centres for High-Performance Computing.
Please ensure you meet all prerequisites / eligibility before you apply.
Important dates
- 14 May 2024 – Application Deadline
- 24 June 2024, 11:00 – 12:00 (CEST) – Cluster Dry Run
- 25 June 2024, 09:00 – 12:30 (CEST) – Day 1
- 26 June 2024, 09:00 – 12:30 (CEST) – Day 2
Agenda & Content
See Agenda & Content in the left menu for a detailed timetable and course content.
Content level
Content level: Basic = (100%) + Intermediate = (0%) + Advanced = (0%)
Entry level
Basic – no prior GPU programming experience is required
Prerequisites
Basic experience with Python and PyTorch
Basic knowledge of neural networks is recommended but not required
Target audience
Course for academia, industry, and public administration.
Course format
This course will be delivered as a LIVE ONLINE COURSE (using Zoom).
All communication will be done through Zoom, Slack, and email.
Hands-on labs
Attendees will be given access to a GPU cluster for the duration of the bootcamp.
Lecturers
Lecturers will be from NVIDIA.
Teaching assistants will be from the HPC centres: HLRS, JSC, LRZ, RISE, UDG, VSC.
Language
English
Date, time, and location
25.–26.06.2024, 09:00 – 12:30 CEST, LIVE ONLINE COURSE (using Zoom)
Prices and eligibility
Due to EuroCC2 regulations, generic or private email addresses cannot be accepted. Please use your official university or company email address to prove your affiliation.
This course is partly funded by the EuroCC 2 project. Therefore, the course is open for participants from academia, industry, and public administration from the Member States (MS) of the European Union (EU) and Associated/Other Countries to the Horizon 2020 programme.
Registration
Registration for this training event is handled by openhackathons.org through their AI for Science Bootcamp page.
All further details
Please see the openhackathons.org event page AI for Science Bootcamp for all further details.
Organizers
This course is jointly organized by High-Performance Computing Center Stuttgart (HLRS), Jülich Supercomputing Centre (JSC), Leibniz Supercomputing Centre (LRZ), Vienna Scientific Cluster (VSC), University of Donja Gorica (UDG), Research Institutes of Sweden (RISE), Linköping University (LiU), OpenACC organization, and NVIDIA for EuroCC Austria, EuroCC@GCS, EuroCC Montenegro, and EuroCC Sweden, all National Competence Centres for High-Performance Computing.
Acknowledgements
This course is partially funded by the EuroCC 2 project.
The project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101101903. The JU receives support from the Digital Europe Programme and Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, and Türkiye.
Additional funding for the project comes from the Austrian federal ministries BMBWF and BMK.
