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BEGIN:VEVENT
DTSTAMP:20210402T160557Z
LOCATION:Track 10
DTSTART;TZID=America/New_York:20201109T143000
DTEND;TZID=America/New_York:20201109T183000
UID:submissions.supercomputing.org_SC20_sess258_tut133@linklings.com
SUMMARY:Lossy Compression for Scientific Data
DESCRIPTION:Tutorial\n\nLossy Compression for Scientific Data\n\nCappello,
  Lindstrom, Di\n\nLarge-scale numerical simulations, observations, experim
 ents and AI computations are generating or consuming very large datasets t
 hat are difficult to analyze, store and transfer. Data compression is an a
 ttractive and efficient technique to significantly reduce the size of scie
 ntific datasets. This tutorial reviews the state of the art in lossy compr
 ession of scientific datasets, discusses in detail two lossy compressors (
 SZ and ZFP), compression error assessment metrics and the Z-checker tool t
 o analyze the compression error. The tutorial addresses the following ques
 tions: why lossless and lossy compression; how does compression work; how 
 to measure and control compression error; and what are the current use cas
 es of lossy compression. The tutorial uses examples of real-world scientif
 ic datasets to illustrate the different compression techniques and their p
 erformance. The tutorial is given by two of the leading teams in this doma
 in and targets students, researchers and practitioners interested in lossy
  compression for scientific data.\n\nTag: Big Data, Data Analytics, Compre
 ssion, and Management, Introductory, Scientific Computing\n\nRegistration 
 Category: Tutorial Reg Pass
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