fast rotation of volume data on data parallel architectures
Data parallel computer architectures hold great promises for high performance computing. Volume visualization (raytracing) is an application that can greatly benefit from these architectures. We describe an algorithm for rendering of orthographic views of volume data on such architectures. In particular the problem of rotating the volume in regard to the communication overhead associated with finely distributed memory is analyzed. We extend an earlier technique (shear decomposition) to 3D and show how this can be mapped onto a data parallel architecture using only grid communication during the resampling associated with the rotation. The rendering uses efficient parallel computation constructs that allow us to use sophisticated shading models and still maintain high speed throughout. This algorithm has been implemented on the Connection Machine R parallel supercomputer and is used in an interactive volume rendering application, with multiple frames per second performance.
rotate data data parallelism parallel architecture parallel computation computer architecture high performance computing performance volume visualization applications algorithm rendering views communication association distributed memorialized decomposition 3d use grid efficiency model maintainability connection supercomputer interaction volume rendering