Ph.D. student in the Efficient Computing and Storage Group
Johannes Gutenberg-Universität Mainz
55128 Mainz, Germany
Frederic Schimmelpfennig is a Ph.D. candidate at the Johannes Gutenberg University Mainz. He started his Ph.D. in 2019 after receiving his B.Ed. and M.Ed. degrees in computer science and physics from the Johannes Gutenberg University Mainz.
Frederic's research interests include system scalability optimizations for data intensive workloads like Deep Learning. He is also developing file systems and explores current technologies like non-volatile main memories.
He was already known to the research group through his bachelor thesis. He continued to work on its results, a tool allowing multiple users to remotely work on three-dimensional visualizations of scientific data, for almost two years as a scientific assistant.
His master thesis in physics was about the simulation of wave optics for embedding in augmented reality experiments.
Frederic is member of the project Big Data in Atmospheric Physics (BINARY)
- Frederic Schimmelpfennig, Marc-André Vef, Reza Salkhordeh, Alberto Miranda, Ramon Nou, and André Brinkmann. 2021. Streamlining distributed Deep Learning I/O with ad hoc file systems. In 2021 IEEE International Conference on Cluster Computing (CLUSTER), 169–180. DOI Author/Publisher URL
- Nafiseh Moti, Frederic Schimmelpfennig, Reza Salkhordeh, David Klopp, Toni Cortes, Ulrich Rückert, and André Brinkmann. Simurgh: A Fully Decentralized and Secure NVMM User SpaceFile System. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC). Author/Publisher URL