Left to right: Paul Springer, Daniel Tameling, Diego Fabregat, Elmar Peise, Matthias Petschow, Paolo Bientinesi, Viola Wierschem, and Edoardo Di Napoli.
The High-Performance and Automatic Computing group is concerned with the development and analysis of accurate and efficient numerical algorithms, with focus on numerical linear algebra. We target applications from materials science, molecular dynamics and computational biology, and the whole range of high-performance architectures.
- Numerical linear algebra
- multilinear algebra
- automatic generation of algorithms and code
- performance modeling and prediction
- error analysis
- parallel eigensolvers.
- Genome analysis,
- long-range solvers for pair potentials
- symbolic AD for matrix operations
- sequence of eigenproblems in ab initio methods.
- Multicore, GPU-based, distributed-memory and hybrid forms of parallelism.
Projects for Bachelor and Master theses
Check list of available projects.