This introductory compact course will be a hands-on tutorial on how to access the tremendous compute capabilities of modern Graphics Processing Units (GPUs) to accelerate scientific and especially numerical codes. The compact course adresses the general hardware- and programming models which serve as the foundation of using GPUs as floating point arithmetic accelerators especially using NVIDIA's Compute Unified Device Architecture (CUDA) and provides practical insight into first steps as well as basic and some advanced techniques to port numerical code to GPUs and optimise it for this powerful hardware architecture.

The seminar will focus on various aspects of microstructures in solid mechanics, material science and applied mathematics:
* Theoretical and computational modeling of materials with evolving microstructures (plasticity, damage, phase transitions, electro-magneto-mechanics, ...)
* Experimental results on the formation and evolution of microstructure (lamination, phase transformation, ...)
* Mathematical analysis, variational formulations, treatment of non-convex problems, relaxation methods
* Multiscale methods and computational tools for the determination of effective properties of micro-heterogeneous materials
The seminar is intended to give the opportunity to discuss and compare different approaches to the above areas as well as to stimulate and create perspectives for future research.