CoEC PATC: Introduction to machine learning in the application area of fluid mechanics and combustion using HPC
=========================
## Document Updates:
- 30.11.22, 10:00 : initial commit
## General Information:
- [CoEC, Event Webpage](https://coec-project.eu/training/patc-introduction-to-machine-learning-in-the-application-area-of-fluid-mechanics-and-combustion-using-hpc/)
- [PRACE, Event Webpage](https://events.prace-ri.eu/event/1453/registrations/1071/)
- [JSC, Event Webpage](https://www.fz-juelich.de/de/ias/jsc/aktuelles/termine/kurse/2022/ml-hpc-combustion)
**Title:**
[ONLINE] PATC: Introduction to machine learning in the application area of fluid mechanics and combustion using HPC
**Objectives:**
This training course will highlight interactive analysis for ML/AI applications in the research domain of combustion theory. The program will focus on fluid mechanics, fundamentals and current challenges in combustion, as well as the use of Machine Learning (ML) and High-Performance Computing (HPC) to approach simulations of turbulent reacting flows.
This course is offered as a PRACE training course in cooperation with the Centre of Excellence for Combustion.
## Main Data:
date
: Thu, 8 Dez 22
8:30am - 5pm (CET, UTC+1)
venue
: Online
Registration is closed - the course is fully booked.
Zoom-Link: https://zoom.us/j/91747519657?pwd=ZUNRRnBaU2FMRldodndONUw5d2p6dz09
(for more details see section "Zoom Details" below)
instructors
: see agenda
prerequisites
: Knowledge in Computational Fluid Dynamics (CFD)
workshop materials
: GitLab repository: https://gitlab.jsc.fz-juelich.de/goebbert1/coec_patc_ml4combustion
Shared notes: https://gitlab.jsc.fz-juelich.de/hedgedoc/dfPTsgYFSAOU_wgVwXkU1Q
## Recommended equipment:
We recommend using a computer with **two monitors** (if possible) for the online course.
- one monitor for the presentation or the lecturer's screen in full-screen mode
- one monitor for your own desktop
## Agenda:
| | Title | Presenter |
|:-------------:|:-------------------------------------------------|:-------------------------|
| 08.30 - 9.15 | Welcome and introduction to interactive supercomputing for machine learning on HPC | Mr. Jens Henrik Göbbert (Jülich Supercomputing Centre) |
| 09.15 – 10.00 | Introduction to machine learning: artificial and convolutional neural networks | Mr. Ludovico Nista (RWTH Aachen University) |
| 10.00 – 10.45 | Machine learning for combustion modeling: Flamet representation through ANN | Dr. Federica Ferraro (TU Darmstadt) |
| 10.45 – 11.15 | Coffee break
| 11.15 – 12.00 | Hands-on session: - linear regression and rain prediction via ANN, a digit classifier using CNN - a flamelet representation with ANN | Mr. T. Jeremy P. Karpowski (TU Darmstadt)
| 12.00 – 13.30 | Lunch break |
| 13.30 – 14.15 | Machine learning for combustion modeling: GAN modeling of sub-filter turbulence | Dr. Temistocle Grenga (RWTH Aachen University) |
| 14.15 – 15.00 | HPC with Machine Learning: multi-node multi-GPU training: theory and applications | Mr. Ludovico Nista (RWTH Aachen University) |
| 15.00 – 15.30 | Coffee Break |
| 15.30 – 16.15 | HPC and ML for Combustion Simulation: Embedding ML into CFD code | Dr. Peicho Petkov (NCSA) |
| 16.15 - 17.00 | Advanced applications of AI super-resolution to combustion | Mr. Mathis Bode (Jülich Supercomputing Centre) |
## Pre-Workshop Todos
- [ ] **Register** at https://judoor.fz-juelich.de - [**Video-Howto (1:10)**](https://drive.google.com/file/d/1-DfiNBP4Gta0av4lQmubkXIXzr2FW4a-/view)
- Click on "Register"
- Enter the email address you used to register for this event
- Click on "Send confirmation mail..."
- Open the confirmation email in your email program
- Click the confirmation link
- [ ] **Join** the training project
- [ ] by following this link:
- **https://judoor.fz-juelich.de/projects/join/coecschool22**
- [ ] **or** by choosing this general approach - [**Video-Howto (1:06)**](https://drive.google.com/file/d/1XdQSdML_jqGqvr_2WXqzlE-G6hiuYE2_/view)
- Login to https://judoor.fz-juelich.de
- Scroll to section "Projects"
- Hit the link "Join a project"
- Enter the Project id:
- "**coecschool22**" for this training course
- Click on "Join project"
- [ ] **Please be patient**
- **This takes as long as the PI needs to respond!**
- The PI has to accept your join-request first
- After acceptance
- project will be listed in section "Projects"
- systems will be listed in section "Systems"
- [ ] **Sign usage agreement** - [**Video-Howto (1:13)**](https://drive.google.com/file/d/1mEN1GmWyGFp75uMIi4d6Tpek2NC_X8eY/view)
- Login to https://judoor.fz-juelich.de
- Scroll to section "Systems"
- Click on "You need to _sign the usage agreement_ to access this system"
- Sign the usage agreement
- [ ] **Please be patient**
- **This may take up to 10 minutes!**
- Your HPC accounts will now be created on the desired systems.
- Shortly after your HPC accounts are prepared you will see
- "jupyter-jsc" in the section "Connected Services"
- [ ] **Login** at https://jupyter-jsc.fz-juelich.de - [**Video-Howto (1:34)**](https://drive.google.com/file/d/1S8_DaZRjBUOv7S3xT_KO8WFf44BqlR0O/view)
- Click on "Login"
- Login with your new **JSC account**
- If this is your first login
- click on "Register"
- agree to the terms of service
- click the link in the confirmation mail
- [ ] **CONGRATULATIONS - YOU ARE READY FOR THE TRAINING COURSE**
## FAQ:
-----------------------------------------------------
## Zoom Details
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