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, OpenACC.org and NVIDIA for GCS, the Gauss Centre for Supercomputing.
Online course Organizer: HLRS, University of Stuttgart, Germany
26. Apr 2023
27. Apr 2023
Computational Fluid Dynamics
Data in HPC / Deep Learning / Machine Learning
Scientific Machine Learning
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Learn more about course curricula and content levels.
Dr. Niki Andreas Loppi (NVIDIA) - Lead instructor.
Dr. Mozhgan Kabiri Chimeh (NVIDIA).
Dr. Tobias Haas, Dr. Lorenzo Zanon, Dr. Khatuna Kakhiani (HLRS).
(Subject to Change)
All times in CEST
Day 1 - Wednesday, April 26, 2023: 09:00 AM - 12:30 PM
Day 2 - Thursday, April 27, 2023: 09:00 AM - 05:30 PM
Attendees will be given access to a GPU cluster for the duration of the Bootcamp.
The code is publicly available on github (tba).
Register via the button at the top of this page.
Registration deadline: 05/04/2023.
This event is free of charge.
Khatuna Kakhiani, phone 0711 685 65796, kakhiani(at)hlrs.de
HLRS is part of the Gauss Centre for Supercomputing (GCS), which is one of the six PRACE Advanced Training Centres (PATCs) that started in Feb. 2012.
This course is not part of the PATC curriculum and is not sponsored by the PATC program.
HLRS is also member of the Baden-Württemberg initiative bwHPC.
http://www.hlrs.de/training/2023/BC-SciML-NV and https://www.openhackathons.org/s/siteevent/a0C5e000007ZWhIEAW/se000181.
See the training overview and the Supercomputing Academy pages.
Dezember 04, 2023
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+49 711 685-87209
Als Mitglied des Gauss Centre for Supercomputing ist das HLRS eines der drei Bundeshöchstleistungsrechenzentren.
Das HLRS ist eine zentrale Einrichtung der Universität Stuttgart.