Bachelor thesis (Dresden): Parallelisation of a Hierarchical Volume Data Preprocessor
Visualization of large three-dimensional data sets on consumer hardware requires pre-processing into hierarchical volume image data to reduce required data transfers onto GPUs, making the rendering process more efficient. This processing is typically an I/O-bound problem and can thus benefit from high bandwidth storage found in modern High Performance Computing (HPC) systems.
In this Bachelor thesis, a serial application for generating hierarchical volume image data will be extended to exploit multiple levels of parallelism on HPC hardware. In order to use the aggregated I/O bandwidth of multiple nodes, multi-process parallelism needs to be added to the application, e.g., using MPI. Additionally, thread-based parallelism will be required to better exploit the resources of a single compute node.
- Investigation of suitable parallelisation strategies
- Implementation of the proposed parallelisation strategy
- Validation and analysis of the proposed solution
- Speedup and parallel efficiency
- Efficiency of the use of the I/O subsystem
- Documentation of implementation and results in written form
For this work, basic knowledge of parallel programming in C/C++ will be required.
The language can be either German or English.