The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Workshop: The 8th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-8) in Conjunction with SC22
Authors: Jinzhen Wang (New Jersey Institute of Technology) and Pascal Grosset, Terry Turton, and James Ahrens (Los Alamos National Laboratory (LANL))
Abstract: Cosmology simulations are among some of the largest simulations being currently run on supercomputers, generating terabytes to petabytes of data for each run. Consequently, scientists are seeking to reduce the amount of storage needed while preserving enough quality for analysis and visualization of the data. One of the most commonly used visualization techniques for cosmology simulations is volume rendering. Here, we investigate how different types of lossy error-bound compression algorithms affect the quality of volume-rendered images generated from reconstructed datasets. We also compute a number of image quality assessment metrics to determine which ones are the most effective at identifying artifacts in the visualizations.