Contains all course materials from the HPML group Course environment: https://jupyter.snellius.surf.nl/jhssrf021
- Software installations on HPC systems
- Packed file formats for Machine Learning
- Parallel computing for deep learning
- Hardware (e.g. Tensor cores) and software features (e.g. low level libraries for deep learning) for accelerated deep learning
- Profiling PyTorch with TensorBoard
9:00 - 10:15 Software installations on HPC systems
10:15 – 10:30 Coffee break
10:30 – 11:00 Packed file formats
11:00 – 11:45 Hands-on: Packed file formats
11:45 – 12:45 Lunch Break
12:45 – 14:15 Hardware and software features to accelerate deep learning
14:15 – 14:30 Coffee Break
14:30 – 15:15 Parallel Computing for Deep Learning
15:15 – 16:15 Profiling to understand your neural network’s performance
16:15 – 17:00 Questions, wrap up
- AI Guide by LUMI: https://github.com/Lumi-supercomputer/LUMI-AI-Guide
- LLMs on supercomputers: https://gitlab.tuwien.ac.at/vsc-public/training/LLMs-on-supercomputers