Examples for HPC cluster usage at RWTH Aachen University
This repository contains a collection of examples, best practices, and guidelines for effectively using the High-Performance Computing (HPC) cluster at RWTH Aachen University. Whether you are new to HPC or an experienced user, you will find useful scripts, job submission templates, performance tuning tips, and troubleshooting advice.
For general help, documentation, and trainings please refer to the following pages:
- RWTH HPC user documentation
- RWTH HPC consultation hour
- HPC wiki
- HPC trainings
- RWTH technical support
What can you find here?
| Folder | Sub-Folder | Description |
|---|---|---|
| generic-job-scripts | - | General-purpose job submission scripts (our current workload is Slurm) for various workloads, including CPU and GPU-based computations. |
| machine-and-deep-learning | - | Collection of different examples in the context of Machine Learning (ML), Deep Learning (DL) and Large Language Models (LLMs) |
| ollama | Examples how to run and use LLMs with Ollama. | |
| pytorch | Example scripts and best practices for running PyTorch workloads on an HPC cluster, including distributed training and GPU utilization. | |
| scikit-learn | HPC-friendly examples of using Scikit-Learn, including job submission scripts for machine learning model training. | |
| tensorflow | TensorFlow job scripts and performance optimization techniques for running deep learning models on CPUs and GPUs in an HPC environment. | |
| vllm | Examples how to run and use LLMs with vLLM. |