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DTSTART;TZID=America/New_York:20241118T104000
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UID:submissions.supercomputing.org_SC24_sess749_ws_drbsd107@linklings.com
SUMMARY:Enabling Data Reduction for Flash-X Simulations
DESCRIPTION:Rajeev Jain (Argonne National Laboratory (ANL)), Houjun Tang (
 Lawrence Berkeley National Laboratory (LBNL)), Akash Dhruv (Argonne Nation
 al Laboratory (ANL)), and Suren Byna (The Ohio State University)\n\nHigh-f
 idelity physics simulation codes, such as Flash-X, generate large amounts 
 of simulation data. Much of the data written to files is sparse and can be
  compressed without significantly impacting the accuracy of the simulation
  or the quality of the visualizations. Reduced file sizes can significantl
 y save storage space and bandwidth, and offer improved performance of visu
 alization tools. Reduction in file size also allows the simulation to outp
 ut more data for higher resolution/fidelity analysis. We introduced SZ3 an
 d ZFP compression technologies into Flash-X as an effective data reduction
  strategy. We conducted experiments on the Frontier exascale supercomputer
 , evaluating both lossless and lossy compression techniques and quantifyin
 g their effects. We examined the impact of accuracy variations and chunk s
 ize variations for different Flash-X problems. Our study provides valuable
  insights and guidelines for simulation developers, helping them understan
 d the best ways to adopt compression tailored to their specific problems.\
 n\nTag: Data Compression, Data Movement and Memory, Middleware and System 
 Software\n\nRegistration Category: Workshop Reg Pass\n\nSession Chairs: Sh
 eng Di (Argonne National Laboratory (ANL), University of Chicago); Ana Gai
 naru (Oak Ridge National Laboratory (ORNL)); Sian Jin (Temple University);
  Xin Liang (Oregon State University); Kento Sato (RIKEN Center for Computa
 tional Science (R-CCS)); and Dingwen Tao (Institute of Computing Technolog
 y, Chinese Academy of Sciences; University of Chinese Academy of Sciences)
 \n\n
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