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dc.contributor.authorFrank, S.en_US
dc.contributor.authorKaufman, A.en_US
dc.date.accessioned2015-02-23T09:07:47Z
dc.date.available2015-02-23T09:07:47Z
dc.date.issued2009en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttp://dx.doi.org/10.1111/j.1467-8659.2008.01307.xen_US
dc.description.abstractRay directed volume-rendering algorithms are well suited for parallel implementation in a distributed cluster environment. For distributed ray casting, the scene must be partitioned between nodes for good load balancing, and a strict view-dependent priority order is required for image composition. In this paper, we define the load balanced network distribution (LBND) problem and map it to the NP-complete precedence constrained job-shop scheduling problem. We introduce a kd-tree solution and a dynamic programming solution. To process a massive data set, either a parallel or an out-of-core approach is required. Parallel preprocessing is performed by render nodes on data, which are allocated using a static data structure. Volumetric data sets often contain a large portion of voxels that will never be rendered, or empty space. Parallel preprocessing fails to take advantage of this. OurA slab-projection slice, introduced in this paper, tracks empty space across consecutive slices of data to reduce the amount of data distributed and rendered. It is used to facilitate out-of-core bricking and kd-tree partitioning. Load balancing using each of our approaches is compared with traditional methods using several segmented regions of the Visible Korean data set.en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltden_US
dc.titleOut-of-Core and Dynamic Programming for Data Distribution on a Volume Visualization Clusteren_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume28en_US
dc.description.number1en_US
dc.identifier.doi10.1111/j.1467-8659.2008.01307.xen_US
dc.identifier.pages141-153en_US


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