Visualization Research

Large-scale analysis and visualization is becoming increasingly important as supercomputers and their simulations produce larger and larger data. These large data sizes are pushing the limits of traditional rendering algorithms and tools. In order to better understand real-world performance with large data, this paper presents a detailed timing study on a large cluster with the widely used visualization tools ParaView and VisIt. The software ray tracer Manta was integrated into these programs in order to show that improved performance could be attained with software ray tracing on a distributed memory, GPU enabled, parallel visualization resource.

Rendering Improvements

Shading models that reproduce natural lighting conditions have been shown to better convey depth information and spatial relationships but they traditionally require considerable (pre)computation. We have developed a shading model for interactive direct volume rendering that provides perceptual cues similar to those of ambient occlusion, for both solid and transparent surface-like features. We have extended this to combine both volumetric and geometric primitives. Using the framework, we can also include depth of field rendering to highlight specific regions in still images.