A framework for GPU-accelerated exploration of massive time-varying rectilinear scalar volumes

Fabio Marton, Marco Agus and Enrico Gobbetti

Computer Graphics Forum, Vol.38, No.3 (Proceedings Eurographics/IEEE Symposium on Visualization, Eurovis 2019), pp. 53-66 , 2019

We introduce a novel flexible approach to spatiotemporal exploration of rectilinear scalar volumes. Our out-of-core representation, based on per-frame levels of hierarchically tiled non-redundant 3D grids, efficiently supports spatiotemporal random access and streaming to the GPU in compressed formats. A novel low-bitrate codec able to store into fixed-size pages a variable-rate approximation based on sparse coding with learned dictionaries is exploited to meet stringent bandwidth constraint during time-critical operations, while a near-lossless representation is employed to support high-quality static frame rendering. A flexible high-speed GPU decoder and raycasting framework mixes and matches GPU kernels performing parallel object-space and image-space operations for seamless support, on fat and thin clients, of different exploration use cases, including animation and temporal browsing, dynamic exploration of single frames, and high-quality snapshots generated from near-lossless data. The quality and performance of our approach are demonstrated on large data sets with thousands of multi-billion-voxel frames.

@article{Agus2019ivv,
  author = {Fabio Marton and Marco Agus and Enrico Gobbetti},
  title = {A framework for GPU-accelerated exploration of massive time-varying rectilinear scalar volumes},
  journal = {Computer Graphics Forum (Proceedings Eurographics/IEEE Symposium on Visualization, Eurovis 2019},
  volume = {38},
  number = {3},
  pages = {53--66},
  year = {2019}
}