HPML-course-materials

Contains all course materials from the HPML group Course environment: https://jupyter.snellius.surf.nl/jhssrf024

Course Overview

• 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

Profiling

python3 -m venv venv
source venv/bin/activate
pip install git+https://github.com/pytorch/kineto.git#subdirectory=tb_plugin

git clone --depth=1 https://github.com/SURF-ML/HPML-course-materials.git

tensorboard --logdir HPML-course-materials/Day2/notebooks/logs/

Other courses and resources

• 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