Image-space decomposition algorithms for sort-first parallel volume rendering of unstructured grids

Abstract

In this thesis, image-space decomposition algorithms are proposed and utilized for parallel implementation of a direct volume rendering algorithm. Screen space bounding box of a primitive is used to approximate the coverage of the primitive on the screen. Number of bounding boxes in a region is used as a workload of the region. Exact model is proposed as a new workload array scheme to find exact number of bounding boxes in a rectangular region in O(1) time. Chains-on-chains partitioning algorithms are exploited for load balancing in some of the proposed decomposition schemes. Summed area table scheme is utilized to achieve more efficient optimal jagged decomposition and iterative rectilinear decomposition algorithms. These two 2D decomposition algorithms are utilized for image-space decomposition using the exact model. Also, new algorithms that use inverse area heuristic are implemented for image-space decomposition. Orthogonal recursive bisection algorithm with medians of medians scheme is applied on regular mesh and quadtree superimposed on the screen. Hilbert space filling curve is also exploited for image-space decomposition. 12 image-space decomposition algorithms are experimentally evaluated on a common framework with respect to the load balance performance, the number of shared primitives, and execution time of the decomposition algorithms.