Understanding Performance-Quality Trade-offs in Scientific Visualization Workflows with Lossy Compression

Conference · Fri Nov 01 00:00:00 EDT 2019

DOI:https://doi.org/10.1109/DRBSD-549595.2019.00006· OSTI ID:1648857

Chen, Jieyang ^[1]; Pugmire, Dave ^[1]; Wolf, Matthew D. ^[1]; Thompson, Nick ^[1]; Logan, Jeremy ^[1]; Mehta, Kshitij V. ^[1]; Wan, Lipeng ^[1]; Choi, Jong Youl ^[1]; Whitney, Ben ^[1]; Klasky, Scott A. ^[1]

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1. ORNL

The cost of I/O is a significant challenge on current supercomputers, and the trend is likely to continue into the foreseeable future. This challenge is amplified in scientific visualization because of the requirement to consume large amounts of data before processing can begin. Lossy compression has become an important technique in reducing the cost of performing I/O. In this paper we consider the implications of using compressed data for visualization within a scientific workflow. We use visualization operations on simulation data that is reduced using three different state-of-the-art compression techniques. We study the storage efficiency and preservation of visualization features on the resulting compressed data, and draw comparisons between the three techniques used. Our contributions can help inform both scientists and researchers in the use and design of compression techniques for preservation of important visualization details.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE; USDOE Office of Science (SC)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1648857
• Country of Publication: United States
• Language: English