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Team Member: Matthias Maiterth

Email maiterth _at_
Phone +49 89 2180-9146
Fax +49 89 2180-9147
External Member Please refer to the personal website.

Note: Working external at Intel & LRZ.

Research interests

  • Energy efficient High Performance Computing
  • Scalable Performance Tools
  • Exascale Computing
  • Performance Engineering in HPC
  • Scalability and portable performance
  • Parallel Programming Models
  • Tightly coupled Distributed Systems

Student Works

Students interested in High Performance Computing, Scalability and Tools, as well as scientific computing, are always welcome.

I do offer topics for

  • bachelor theses
  • master theses
  • and practical courses
on request.
A short email about your interests is always a good start to find a topic that is exciting for you and fits my research interests.


  • Maiterth, M., Schulz, M., Rountree, B., Kranzlmüller, D., Power Balancing in an Emulated Exascale Environment, In The 12th IEEE Workshop on High–Performance, Power–Aware Computing (HPPAC) 2016, Chicago, IL, Mai, 2016.
  • Patki, T., Lowenthal, D. K., Sasidharan, A., Maiterth, M., Rountree, B., Schulz, M., Supinski, B. R., Practical Resource Management in Power–Constrained, High Performance Computing, In Proceedings of the 24th International Symposium on High–Performance Parallel and Distributed Computing, HPDC 2015, Portland, OR, USA, June 15–19, 2015, 121 — 132, ACM, Juni, 2015.
  • Fuerlinger, K., Glass, C., Gracia, J., Knüpfer, A., Tao, J., Hünich, D., Idrees, K., Maiterth, M., Mbedheb, Y., Zhou, H., DASH: Data Structures and Algorithms with Support for Hierarchical Locality, In Euro–Par 2014 Workshops , Porto, Portugal, August, 2014.