Distributed terascale volume visualization using distributed shared virtual memory
Each cluster node is running its own pipeline for ray-casting, virtual vol- ume and memory management, and paging. Ray-casting is per- formed on a huge virtual 3D volume, which is conceptually given on a regular grid in 3D. However, this volume is virtual because the data that are sampled by the ray...
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| Vydáno v: | 2011 IEEE Symposium on Large Data Analysis and Visualization s. 127 - 128 |
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| Hlavní autoři: | , , , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
01.10.2011
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| Témata: | |
| ISBN: | 9781467301565, 1467301566 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Each cluster node is running its own pipeline for ray-casting, virtual vol- ume and memory management, and paging. Ray-casting is per- formed on a huge virtual 3D volume, which is conceptually given on a regular grid in 3D. However, this volume is virtual because the data that are sampled by the ray-caster are only created on demand (i.e., read from disk or reconstructed on-the-fly), as determined by the actual visibility of small cubical blocks or memory pages of 32 voxels each. In order to be able to adapt the data resolution used for ray-casting to the output screen resolution, we represent the whole virtual volume as a virtual octree multi-resolution hier- archy, which is mapped to a large shared virtual memory address space. |
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| ISBN: | 9781467301565 1467301566 |
| DOI: | 10.1109/LDAV.2011.6092332 |

