IPE 05-2022 Master Thesis or Internship A High Performance Computing Data Processing Pipeline for Container-Native Cloud Computing
Institut für Prozessdatenverarbeitung und Elektronik (IPE)
Technologies like Machine Learning and Artificial Intelligence rely on heterogeneous and highperformance computing (HPC) resources to deliver high processing and analytical capabilities to scientific data. However, HPC resources are expensive and require special IT administration techniques and technologies that are not easy to maintain in small computing infrastructures. On the other hand, HPC services e.g. HPCaaS are provided for the public by super computing centers and public clouds like AWS with negligible maintenance.
Using third-party HPC services in small computing infrastructures would increase their computing power by folds and enhance their processing and analytical capabilities. However, the integration should be automatic and seamless with the existing IT infrastructure and should provide users with easy interfaces to deploy their code e.g. Linux containers.
In this Master’s Thesis, you are expected to build a HPC data processing pipeline that would make HPC resources available to small cloud computing infrastructures by relying on 3rd party HPC services and containers. You are expected to get familiarized with Kubernetes cloud platform and container technologies for HPC e.g. Singularity. You will extend Kubernetes cloud platform to add the 3rd party HPC services as cloud resources and propose an efficient interface to use them based on container-native workflows.
- Excellent skills in Linux Containers.
- Good programming and scripting skills in a decent programming language e.g. Python
- Good understanding of HPC infrastructures e.g. Slurm, Singularity, MPI, etc is considered a plus
Contact person in line-management
Bitte bewerben Sie sich online über den unten stehenden Button für die Ausschreibungsnummer IPE 05-2022.
Ausschreibungsnummer: IPE 05-2022
Bei gleicher Eignung werden anerkannt schwerbehinderte Menschen bevorzugt berücksichtigt.
Bei allgemeinen Fragen zur Bewerbung:
Personalservice (PSE) - Personalbetreuung
Frau Carrasco Sanchez
Telefon: +49 721 608-42016,
Kaiserstr. 12, 76131 Karlsruhe