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Martin Schreiber

I'm a researcher on the adventurous path between high-performance computing and applied mathematics. Here, my strong belief is that only interdisciplinary knowledge and research can lead to the required breakthroughs needed in scientific computing. However, my research interests are also in other areas such as (real-time) visualization, computer architectures and basically everything which sounds exciting and challenging.

This website provides some information about myself, my finished, not finished and running projects as well as plenty of other information about my past, present and partly the future. If you need anything or want to kick off a collaboration, don't hesitate to contact me.


Research interests / expertise:

  • Architectures: CPU, GPU, (XeonPhi,) FPGAs
  • Parallel programming standards: OpenMP, OpenCL, MPI, PGAS (X10)
  • Applications (among others): Weather, Climate, Ocean
  • Algorithms: development of new algorithms for scientific computing
  • Parallelization: new algorithms on HPC architectures, new parallelization concepts/models, parallelization in time
  • Mesh: Focus on dynamically adaptive grids based on space-filling curves
  • Compute resources: Dynamic resource scheduling
  • Realtime: Interactive simulations
  • Visualization: Efficient on- and offline processing

In 2010, I wrote my diploma thesis in Computer Science at the Technical University of Munich (TUM) on simulation and visualization of the free surface lattice Boltzmann equation on GPUs.

At the end of 2010, I joined the research group of Prof. Bungartz at TUM as a doctoral candidate where I worked in the Invasive Computing Transregio Project (DFG funded). My work in this project was two-folded: In collaboration with other members of the project I redesigned algorithms to support dynamical resource management on embedded systems. For high-performance systems, I developed a new run-length encoded cluster-based parallelization method for efficiently running simulations on dynamically adaptive triangular grids with MPI+X parallelization models and presented the benefits of dynamic resource management for Tsunami parameter studies.

I was appointed as a proleptic lecturer in 2015 at the University of Exeter. Here, my research interests were in the interdisciplinary areas of scientific and high-performance computing. Areas are e.g. biological parameter estimation on accelerator cards, parallelization in time methods, ocean, climate and weather simulations, etc.

In 2018 I joined the Technical University of Munich as a postdoctoral researcher.