Area of research:
The position is suitable for part-time employment.
Parallel programming technologies are extremely important in the domain of scientific computing. Standard servers include CPUs with up to 64 cores. Modern GPUs are able to execute thousands of floating point operations in parallel and have become an invaluable tool in almost any scientific field with high computational throughput. In order to make use of the computational power it becomes more and more important to parallelize existing algorithms and tune the implementations to the recent hardware
architectures. For optimal performance, it is crucial to take the details of hardware architectures into account.
The student will perform optimization of selected image-processing algorithms for recent parallel architectures in one of our currently running projects.
advanced image reconstruction and segmentation algorithms in cooperation with the ANKA synchrotron at KIT,digital image tracking algorithms done in cooperation with the Institute for Thermal Process Engineering,simulation codes for the international KATRIN and Edelweiss collaborations.