CS 6204: Parallel Visualization of Massive Scale Data 
Dr. Yong Cao
Fall 2013

Real-time visualization, including surface rendering and volume rendering,
requires a large amount of computing power to generate high-fidelity
images in real-time. The evergrowing size of the datasets makes the task
more challenging. Parallelization, as an essential solution for most of
computational challenges, has become the research frontier for visualizing
massive scale datasets. Because most of the rendering algorithms are not
easily parallelizable in nature, creative design of the new parallel
algorithms for real-time visualization is the main focus of this new
research area, and also this course. The case-study algorithms include
the basic Ray-Tracing algorithm, monte carlo integration, photon mapping,
ambient occlusion, volume rendering, and adaptive supersampling.