ParaViz: A Spatially Decomposed Parallel Visualization Algorithm Using Hierarchical Visibility Ordering

A scalable parallel visualization algorithm has been designed to visualize large datasets that are spatially decomposed onto processors of a massively parallel computer. The ParaViz algorithm, which is based on hybrid sort-first/sort-last parallel visualization, employs distributed visibility ordering to implement a scalable hierarchical depth buffer. A visibility rank is computed for each processor depending on its relative position from the viewpoint. After each processor rasterizes its own primitives, individually rendered sub-images are hierarchically reduced to a final image using their visibility ranks. This technique allows on-thefly visualization of parallel simulation data without data migration. The algorithm has been tested on 8–1,024 processors for molecular-dynamics simulation data. In a weak-scaling test consisting of 64,000 spherical objects (atoms) per processor, the image integration time of the ParaViz algorithm is 40–50% less than that of the conventional global Z-buffer approach. A strong-scaling test involving 16,777,216 atoms achieves a parallel efficiency of 0.98 on 1,024 processors.