This Bootcamp will provide researchers hands-on approaches on how to use NVIDIA Modulus, a framework that combines physics and partial differential equations (PDEs) with artificial intelligence (AI) to build robust models. Participants will also learn about the differences between Physics-driven and Data-driven approaches to AI. In addition, the Bootcamp will provide hands-on experience with visualizing the results of physics simulations using ParaView. This Lab will also introduce you to Earth2Studio where you get to try out different workflows for various Weather forecasting models!
The content is structured in multiple modules covering the following:
- Introduction to NVIDIA Modulus
- Module 1: Physics Informed approaches to an AI for Scientific application.
- Lab 1: Simulating Projectile Motion
- Lab 2: Steady State Diffusion in a Composite Bar using PINNs
- Lab 3: Forecasting weather using Navier-Stokes PDE
- Lab 4: Spring mass problem - Solving transient problems and inverse problems - Optional
- Module 2: Data-driven approach to an AI for Scientific application.
- Lab 1: Solving the Darcy-Flow problem using FNO
- Lab 2: Solving the Darcy-Flow problem using AFNO
- Lab 3: Forecasting weather using FourCastNet
- Module 3: Data-driven approach using Modulus Core and Introduction to Earth2Studio
- Lab 1: Training Physics-ML Models using Modulus Core
- Lab 2: Training Weather forecasting Models using Modulus Core
- Lab 3: Introduction to Earth2Studio - Deterministic Inference
- Lab 4: Introduction to Earth2Studio - Diagnostic & Ensemble Inference
The tools and frameworks used in the bootcamp are as follows:
The overall bootcamp will take approximately 14 hours.
Mathematical background in Differential equations, Python proficiency, and familiarity with deep learning fundamentals and frameworks are required.
For deploying the materials, please refer to the Deployment guide present here
This material originates from the OpenHackathons Github repository. Check out additional materials here
Don't forget to check out additional Open Hackathons Resources and join our OpenACC and Hackathons Slack Channel to share your experience and get more help from the community.
Copyright © 2024 OpenACC-Standard.org. This material is released by OpenACC-Standard.org, in collaboration with NVIDIA Corporation, under the Creative Commons Attribution 4.0 International (CC BY 4.0). These materials may include references to hardware and software developed by other entities; all applicable licensing and copyrights apply.
