Distributed volume rendering on a visualization cluster

We describe the rendering of massive volumes on a volume visualization cluster. We present our data distribution scheme and introduce an algorithm which reduces the memory requirement with no loss of accuracy. The volume is automatically cropped and partitioned into small volume blocks. The bounding boxes of these volume blocks are used at run-time for flexible partitioning of the volume across the network. We present results of rendering the full visible male color dataset, seismic data, and several large micro-CT scanned fossil and teeth datasets.