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DTSTART;TZID=America/Chicago:20251120T133000
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UID:submissions.supercomputing.org_SC25_sess162_pap630@linklings.com
SUMMARY:What To Support When You’re Compressing: The State of Practice, Ga
 ps, and Opportunities for Scientific Data Compression
DESCRIPTION:Franck Cappello and Robert Underwood (Argonne National Laborat
 ory (ANL), University of Chicago); Yuri Alexeev (Argonne National Laborato
 ry (ANL)); Alison Baker (National Center for Atmospheric Research (NCAR));
  Ebru Bozdağ (Colorado School of Mines); Martin Burtscher (Texas State Uni
 versity); Kyle Chard (University of Chicago, Argonne National Laboratory (
 ANL)); Sheng Di (Argonne National Laboratory (ANL), University of Chicago)
 ; Kyle Gerard Felker (Argonne National Laboratory (ANL)); Paul Christopher
  O'Grady (SLAC National Accelerator Laboratory); Hanqi Guo (Ohio State Uni
 versity); Yafan Huang and Peng Jiang (University of Iowa); Sian Jin (Templ
 e University); Petter Johansson (KTH Royal Institute of Technology); Shaom
 eng Li (NVIDIA Corporation); Xin Liang (University of Kentucky); Erik Lind
 ahl (Stockholm University); Peter Lindstrom and Zarija Lukić (Lawrence Liv
 ermore National Laboratory (LLNL)); Magnus Lundborg (KTH Royal Institute o
 f Technology, Department of Applied Physics); Danylo Lykov (NVIDIA Corpora
 tion); Masaru Nagaso, Kento Sato, and Amarjit Singh (RIKEN Center for Comp
 utational Science (R-CCS)); Seung Woo Son (UMass Lowell); Shihui Song (Uni
 versity of Iowa); William Tang (Princeton Plasma Physics Laboratory); Ding
 wen Tao (Indiana University Bloomington); Jiannan Tian (University of Kent
 ucky); Kazutomo Yoshii (Argonne National Laboratory (ANL)); and Kai Zhao (
 Florida State University)\n\nOver the last nearly 20 years, lossy compress
 ion has become an essential aspect of HPC applications' data pipelines, al
 lowing them to overcome limitations in storage capacity and bandwidth and,
  in some cases, increase computational throughput and capacity. However, w
 ith the adoption of lossy compression comes the requirement to assess and 
 control the impact lossy compression has on scientific outcomes.    \n\nIn
  this work, we take a major step forward in describing the state of practi
 ce and characterizing workloads. We examine applications' needs and compre
 ssors' capabilities across nine different supercomputing application domai
 ns. We present 25 takeaways that provide best practices for applications, 
 operational impacts for facilities achieving compressed data, and gaps in 
 application needs not addressed by production compressors that point towar
 ds opportunities for future compression research.\n\nTag: Algorithms, Appl
 ications, State of the Practice\n\nRecording: Livestreamed, Recorded\n\nRe
 gistration Category: Technical Program Reg Pass\n\nSession Chair: Shaikh A
 rifuzzaman (University of Nevada, Las Vegas)\n\n
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