Prof. Dr. Michael Georg Bader
Academic Career and Research Areas
Professor Bader (b. 1971) works on hardware-aware algorithms in computational science and engineering and in high performance computing. His main focus is on the challenges imposed by the latest supercomputing platforms and the development of suitable efficient and scalable algorithms and software for simulation tasks in science and engineering. His research group is located at the Leibniz Supercomputing Center.
Professor Bader studied computer science and earned his PhD in 2001 at TUM. He subsequently acted as a coordinator of the elite master’s program in computational engineering (as part of the Elite Network Bavaria) and of the Munich Center of Advanced Computing. From 2009 to 2011, before assuming the position of professor at TUM, he worked as an assistant professor at the SimTech Cluster of Excellence at the University of Stuttgart.
Key Publications (alle Publikationen)
Meister O, Bader M: “2D adaptivity for 3D problems: Parallel SPE10 reservoir simulation on dynamically adaptive prism grids”. Journal of Computational Science. 2015; 9: 101-106.Abstract
Heinecke A, Breuer A, Rettenberger S, Bader M, Gabriel AA, Pelties C, Bode A, Barth W, Liao XK, Vaidyanathan K, Smelyanskiy M, Dubey P: “Petascale High Order Dynamic Rupture Earthquake Simulations on Heterogeneous Supercomputers”. Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. 2014; 3-14.Abstract
Breuer A, Heinecke A, Rettenberger S, Bader M, Gabriel AA, Pelties C: “Sustained Petascale Performance of Seismic Simulations with SeisSol on SuperMUC”. In: Supercomputing - 29th International Conference, ISC 2014, Volume 8488 of Lecture Notes in Computer Science. Editor: Kunkel JM, Ludwig TT, Meuer HW. Heidelberg: Springer, 2014: 1-18.Abstract
Bader M: Space-Filling Curves - An Introduction with Applications in Scientific Computing. Berlin, Heidelberg: Springer-Verlag, 2013.Abstract
Bader M, Böck C, Schwaiger J, Vigh CA: “Dynamically Adaptive Simulations with Minimal Memory Requirement – Solving the Shallow Water Equations Using Sierpinski Curves”. SIAM Journal of Scientific Computing. 2010; 32(1): 212–228.Abstract