BOOTCAMP: AI for Science Bootcamp

This Bootcamp will be held online with Zoom. Cluster dry run already on Mon, May 26.

This bootcamp focuses on Scientific Machine Learning (differently to the 2023 edition).

Deep Learning (DL) has revolutionized the way of performing classification, pattern recognition, and regression tasks in various application areas. Scientific applications solving linear and non-linear equations with demanding accuracy and computational performance requirements can use a class of DL networks, called Physics-Informed Neural Networks (PINN). In fact, PINNs are specifically designed to integrate scientific computing equations, such as Ordinary Differential Equations (ODE), Partial Differential Equations (PDE), non-linear, and integral-differential equations into the DL network training.

This workshop introduces Scientific Machine Learning (SciML) with PINN and provides hands-on experience with the PDE solver NVIDIA Modulus, a neural network framework that blends the power of physics in the form of governing partial differential equations (PDEs) with data to build high-fidelity, parameterized surrogate models with near-real-time latency. 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.

The Bootcamp is co-organised by HLRS, JSC, LRZ, VSC Vienna, Cyfronet AGH, IT4Innovations, RISE, LiU, OpenACC.org and NVIDIA for EuroCC Austria, EuroCC Czechia, EuroCC Poland, EuroCC Montenegro, SLING, EuroCC@GCS and EuroCC Sweden, all National Competence Centres for High-Performance Computing.

Veranstaltungsort

Online course
Organizer: HLRS, University of Stuttgart, Germany

Veranstaltungsbeginn

27. Mai 2025
09:00

Verstaltungsende

28. Mai 2025
13:30

Sprache

Englisch

Einstiegslevel

Mittel

Themenbereiche

Bootcamp/Hackathon

Themen

Künstliche Intelligenz

Big Data

Deep Learning

Maschinelles Lernen

Scientific Machine Learning

Zurück zur Liste

Prerequisites and content levels

Prerequisites

Basic experience with Python. No GPU programming experience is required.
Some knowledge in PDE theory (e.g. weak formulation).

Content levels

Intermediate level: 7 hours 15 mins

Learn more about course curricula and content levels.

Instructors

Main lecturer: Niki Andreas Loppi (NVIDIA)

Agenda

CEST time:

Day 0 (Mon, May 26): Cluster Dry Run

11:30 - 12:00 Cluster Dry Run Session

Day 1 (Tue, May 27): Introduction

09:00 - 09:15 Welcome (Moderator)
09:15 - 09:30 Connecting to a cluster
09:30 - 10:00 Introduction to NVIDIA Modulus (Lecture)
10:00 - 12:00 Physics-Informed approach to an AI for Scientific application (Lecture and Lab)
- Lab 1: Simulating Projectile Motion
- Lab 2: Steady State Diffusion in a Composite Bar using PINNs
12:00 - 12:30 Wrap up and Q&A

Day 2 (Wed, May 28): Advanced Topics

09:30 - 10:30 Physics-Informed approach to an AI for Scientific application (Lecture and Lab)
- Lab 3: Forecasting weather using Navier-Stokes PDE
- Lab 4: Spring mass problem - Solving transient problems and inverse problems - Optional
10:30 - 12:15 Data-driven approach to an AI for Scientific application. (Lecture and Lab)
- Lab 1: Solving the Darcy-Flow problem using FNO
- Lab 2: Solving the Darcy-Flow problem using AFNO
- Lab 3: Forecasting weather using FourCastNet
12:15 - 12:30 Wrap up and QA

Hands-on sessions

Attendees will be given access to a GPU cluster for the duration of the Bootcamp.

The code is publicly available on github.

Registration information

Please register at OpenACC-Standard.org via the button at the top of this page with your institutional e-mail address to prove your affiliation.

The final participants will be selected and informed after the registration deadline has passed.

This course is offered in cooperation by HLRS, JSC, LRZ, VSC Vienna, Cyfronet AGH, IT4Innovations, RISE, LiU, OpenACC.org and NVIDIA. Registration is done via www.gpuhackathons.org hosted by OpenACC-Standard.org. Your registration data will be transferred to these partners. For legal notes see the Privacy Policy.

Registration closes on April 18, 2025 at 23:55.

Fees

Students without Master's degree or equivalent. Participants from EU or EuroCC countries only: 0 EUR
PhD students or employees at a German university or public research institute: 0 EUR
PhD students or employees at a university or public research institute in an EU or EuroCC country other than Germany: 0 EUR.
Other participants, e.g., from industry, other public service providers, or government. Participants from EU or EuroCC countries only: 0 EUR

Our course fee includes coffee breaks (in classroom courses only).

For lists of EU and EuroCC countries have a look at the Horizon Europe and EuroCC website.

Only participants from institutions belonging to these countries can take part in this course.

Contact

Maksym Deliyergiyev phone 0711 685 87261, maksym.deliyergiyev(at)hlrs.de

HLRS Training Collaborations in HPC

HLRS is part of the Gauss Centre for Supercomputing (GCS), together with JSC in Jülich and LRZ in Garching near Munich. EuroCC@GCS is the German National Competence Centre (NCC) for High-Performance Computing. HLRS is also a member of the Baden-Württemberg initiative bwHPC.

This course is provided within the framework of EuroCC2.

Official course URL(s)

http://www.hlrs.de/training/2025/BC-AI-NV.

Further courses

See the training overview and the Supercomputing Academy pages.

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