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DTSTAMP:20230124T171521Z
LOCATION:C141
DTSTART;TZID=America/Chicago:20221113T103000
DTEND;TZID=America/Chicago:20221113T110000
UID:submissions.supercomputing.org_SC22_sess421_ws_drbsd103@linklings.com
SUMMARY:Analyzing the Impact of Lossy Data Reduction on Volume Rendering o
 f Cosmology Data
DESCRIPTION:Workshop\n\nAnalyzing the Impact of Lossy Data Reduction on Vo
 lume Rendering of Cosmology Data\n\nWang, Grosset, Turton, Ahrens\n\nCosmo
 logy 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 cosmo
 logy simulations is volume rendering. Here, we investigate how different t
 ypes of lossy error-bound compression algorithms affect the quality of vol
 ume-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.\n\nSess
 ion Format: Recorded\n\nRegistration Category: Workshop Reg Pass
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