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Bachelor and Master Theses


We permanently offer proposals for bachelor and master thesis projects in all areas across our research activities (see our research areas page) and related subjects which cover most topics in Virtual Reality and Scientific Visualization. The thesis topics are usually specified in cooperation with one of our research assistants and/or Prof. Kuhlen taking into account the student's individual interests and his/her previous knowledge as well as the current research agenda of the Virtual Reality group (e.g. in terms of ongoing academic or industrial cooperations). So if you are interested in a thesis project in Virtual Reality, please contact us. In order to guarantee a successful completion of the thesis, we usually expect our student to have

  • taken the "Basic Techniques in Computer Graphics" lecture if you are a bachelor student
  • taken at least on of the “Virtual Reality” lectures if you are a master student
  • a good working knowledge of C++ or C#
  • or an equivalent qualification.
Below you find a (non-complete) list of currently open theses and the respective supervisors to contact. If there is no suitable topic listed, please have a look at our research projects and drop the respective contacts of an interesting project a mail.



Master Thesis: The multi-device data- and task-parallelism library

There are various solutions for shared and distributed parallelism on CPUs and GPUs today: OpenMP and Intel Threading Building Blocks (TBB) for shared parallelism on the CPU, OpenCL and NVIDIA CUDA for shared parallelism on the GPU, MPI for distributed parallelism on both the CPU and the GPU. The majority of algorithms in scientific data analysis and visualization may be divided into two groups: data-parallel and task-parallel. Data-parallel approaches divide the domain into smaller chunks which are distributed to the processes, whereas task-parallel approaches divide the problem into smaller chunks and distribute them instead. The core idea of this engineering-oriented work is to develop a library enabling development of data-parallel and task-parallel visualization algorithms without explicit knowledge of the device the algorithm will run on.

Contact:
Ali Can Demiralp, M. Sc.


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