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Scientific Computing // Wissenschaftliches Rechnen

The group Scientific Computing conducts research and development on high performance storage systems. We develop HPC concepts and apply them to simulation software with a focus on earth system models.

The group offers products for research and teaching, and contributes to third-party projects.


Lehre im Wintersemester 2022/2023

Recent publications

Recent theses

  • Data-Aware Compression for HPC using Machine Learning (Julius Plehn), Master's Thesis, 2022-05-09, ThesisPublication details
  • Performance study on GPU offloading techniques using the Gauß matrix inverse algorithm (Yannik Koenneker), Bachelor's Thesis, 2022-03-04, ThesisPublication details
  • Analysis of elastic Cloud solutions in an HPC Environment (Johannes Coym), Master's Thesis, 2021-10-23, ThesisPublication details
  • Optimising Scientific Software for Heterogeneous Cluster Computers: Evaluation of Machine Learning Methods for Source Code Classification (Ruben Felgenhauer), Master's Thesis, 2021-09-23, ThesisPublication details
  • Scimon - Scientific Monitor for Automated Run Logging and Reproducibility (Daniel Bremer), Master's Thesis, 2021-06-09, Publication details

start.txt · Last modified: 2022-08-01 10:10 by

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