A Framework for GPU-accelerated Exploration of Massive Time-varying Rectilinear Scalar Volumes
| dc.contributor.author | Marton, Fabio | en_US |
| dc.contributor.author | Agus, Marco | en_US |
| dc.contributor.author | Gobbetti, Enrico | en_US |
| dc.contributor.editor | Gleicher, Michael and Viola, Ivan and Leitte, Heike | en_US |
| dc.date.accessioned | 2019-06-02T18:27:15Z | |
| dc.date.available | 2019-06-02T18:27:15Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | 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. | en_US |
| dc.description.number | 3 | |
| dc.description.sectionheaders | Best Paper Award Nominees | |
| dc.description.seriesinformation | Computer Graphics Forum | |
| dc.description.volume | 38 | |
| dc.identifier.doi | 10.1111/cgf.13671 | |
| dc.identifier.issn | 1467-8659 | |
| dc.identifier.pages | 53-66 | |
| dc.identifier.uri | https://doi.org/10.1111/cgf.13671 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.1111/cgf13671 | |
| dc.publisher | The Eurographics Association and John Wiley & Sons Ltd. | en_US |
| dc.subject | Human | |
| dc.subject | centered computing | |
| dc.subject | Scientific visualization | |
| dc.subject | Computing methodologies | |
| dc.subject | Computer graphics | |
| dc.subject | Graphics systems and interfaces | |
| dc.title | A Framework for GPU-accelerated Exploration of Massive Time-varying Rectilinear Scalar Volumes | en_US |