A GPU-supported lossless compression scheme for rendering time-varying volume data

Authors:
Jörg Mensmann;Timo Ropinski;Klaus Hinrichs
Affiliations:
Visualization and Computer Graphics Research Group, Department of Computer Science, University of Münster, Germany;Visualization and Computer Graphics Research Group, Department of Computer Science, University of Münster, Germany;Visualization and Computer Graphics Research Group, Department of Computer Science, University of Münster, Germany
Venue:
VG'10 Proceedings of the 8th IEEE/EG international conference on Volume Graphics
Year:
2010

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Abstract

Since the size of time-varying volumetric data sets typically exceeds the amount of available GPU and main memory, out-of-core streaming techniques are required to support interactive rendering. To deal with the performance bottlenecks of hard-disk transfer rate and graphics bus bandwidth, we present a hybrid CPU/GPU scheme for lossless compression and data streaming that combines a temporal prediction model, which allows to exploit coherence between time steps, and variable-length coding with a fast block compression algorithm. This combination becomes possible by exploiting the CUDA computing architecture for unpacking and assembling data packets on the GPU. The system allows near-interactive performance even for rendering large real-world data sets with a low signal-to-noise-ratio, while not degrading image quality. It uses standard volume raycasting and can be easily combined with existing acceleration methods and advanced visualization techniques.