Parallel Volume Rendering has been realized using various load distribution methods that subdivide either the screen, called image-space partitioning, or the volume dataset, called object-space partitioning. The major advantages of image-space partitioing are load balancing and low communication overhead, but processors require access to the full volume in order to render the volume with arbitrary views without frequent data redistributions. Subdividing the volume, on the other hand, provides storage scalability as more processors are added, but requires image compositing and thus higher communication bandwidth for producing the final image. In this paper, we present a parallel volume rendering algorithm that combines the benefits of both image-space and object-space partition schemes based on the idea of pixel and volume interleaving. We first subdivide the processors into groups. Each group is responsible for rendering a portion of the volume. Inside of a group, every member interleaves the datasamples of the volume and the pixels of the screen. Interleaving the data provides storage scalability and interleaving the pixels reduces communication overhead. Our hybrid object- and image-space partitioning scheme was able to reduce the image compositing cost, incur in low communication overhead and balance rendering workload at the expense of image quality. Experiments on a PC-cluster demonstrate encouraging results.
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