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Design and Development of a Self-Adaptive Architecture for Online Data Stream Compression
Betreuer M.Sc. Seyyed Mahdi Najmabadi
Prüfer Prof. Dr.-Ing. Sven Simon

Online compression of I/O-data streams in general purpose computing will enhance the effective I/O bandwidth of processors, the bandwidth of the computer network as well as the storage capacity and the read/write performance of the storage. In this thesis, a self-adaptive dynamic partial reconfigurable architecture for the online compression of data streams is required. The proposed architecture will bring new possibilities in online compression due to its adaptivity to different factors like current data bandwidth, data statistics and the level of available resources and so forth. The architecture consists of multiple partially reconfigurable regions that are reconfigured dynamically with suited compression or decompression IP cores based on the above-mentioned factors at run time.

The main goal of the thesis is to use the FPGA resources more efficiently by allocating and alternating them during the runtime.

In this thesis the focus is on a system that consists of entropy encoders and decoders while the input bandwidth is dynamic. In order to have a real-time processing of the data the number or the type of the encoders will be changed while the other units e.g. controllers are running.


  • Good Knowledge of VHDL programing.


We are looking forward to your applications.

Contact: Seyyed Mahdi Najmabadi (Mahdi.Najmabadi@ipvs.uni-stuttgart.de)