Multi-Resolution Rendering with Overlapping AMR: Difference between revisions
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# Sources/Filters produce meta-data in their RequestInformation() pass. This meta-data can be used by any sink to decide what are the blocks in the dataset, how are they positioned, what is the ''cost'' for processing that block of dataset. For AMR datasets, this meta-data is properly defined by vtkAMRInformation. For other composite datasets, users are free to come up with their own convention. So long as the sink and source are aware of the convention, we are good. | # Sources/Filters produce meta-data in their RequestInformation() pass. This meta-data can be used by any sink to decide what are the blocks in the dataset, how are they positioned, what is the ''cost'' for processing that block of dataset. For AMR datasets, this meta-data is properly defined by vtkAMRInformation. For other composite datasets, users are free to come up with their own convention. So long as the sink and source are aware of the convention, we are good. | ||
# A Sink can request a particular block (or blocks) from the source by providing appropriate keys in the RequestUpdateExtent() pass. The source then delivers those blocks. | # A Sink can request a particular block (or blocks) from the source by providing appropriate keys in the RequestUpdateExtent() pass. The source then delivers those blocks. | ||
This general streaming principal can be extended to views and representations too, for rendering. The representations, in this case, act as the sinks that process meta-data and request blocks from the sources. The render view in ParaView (vtkPVRenderView), provides mechanisms for representations to leverage to render the dataset in a streaming fashion. | This general streaming principal can be extended to views and representations too, for rendering. The representations, in this case, act as the sinks that process meta-data and request blocks from the sources. The render view in ParaView (vtkPVRenderView), provides mechanisms for representations to leverage to render the dataset in a streaming fashion. | ||
Revision as of 11:34, 10 October 2012
Motivation
With dataset sizes growing increasingly large, exploratory interactive visualization keeps on getting harder and harder. Multi-resoltuion visualization makes it possible to deal with large datasets while keeping the system requirements and response times low.
Design Overview
ParaView/VTK provides an infrastructure for multi-resolution analysis based on composite datasets (multiblock datasets or overlapping AMR datasets). The principle is as follows:
- Sources/Filters produce meta-data in their RequestInformation() pass. This meta-data can be used by any sink to decide what are the blocks in the dataset, how are they positioned, what is the cost for processing that block of dataset. For AMR datasets, this meta-data is properly defined by vtkAMRInformation. For other composite datasets, users are free to come up with their own convention. So long as the sink and source are aware of the convention, we are good.
- A Sink can request a particular block (or blocks) from the source by providing appropriate keys in the RequestUpdateExtent() pass. The source then delivers those blocks.
This general streaming principal can be extended to views and representations too, for rendering. The representations, in this case, act as the sinks that process meta-data and request blocks from the sources. The render view in ParaView (vtkPVRenderView), provides mechanisms for representations to leverage to render the dataset in a streaming fashion.
