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UID:submissions.pasc-conference.org_PASC24_sess118_msa279@linklings.com
SUMMARY:Analysis Model and Future Challenges: A Perspective from the LHC
DESCRIPTION:Minisymposium\n\nVerena Ingrid Martinez Outschoorn (University
  of Massachusetts Amherst)\n\nThe Large Hadron Collider (LHC) is entering 
 an era where the experiments are collecting hundreds of petabytes of data 
 from which a wide variety of science goals can be pursued by distilling th
 e data to high-level observables. Current data analysis methods rely on a 
 combination of experiment-specific centrally-provided code, as well as com
 munity supported tools and analysis specific software. In addition, severa
 l computing and storage resources are used for processing the data in stag
 es. In the coming years, upgrades to the LHC and the experiments are expec
 ting to result in a major increase in the data volume. In addition, the co
 mplexity of the analyses is increasing. This presentation will discuss the
  current methods used for data analysis in big-science experiments at the 
 LHC, as well as ideas for the future to address challenges in areas such a
 s analysis techniques for parallelized data access, organization of workfl
 ows and the incorporation of new technologies such as heterogeneous resour
 ces.\n\nDomain: Engineering, Physics, Computational Methods and Applied Ma
 thematics\n\nSession Chair: Katherine Royston (Oak Ridge National Laborato
 ry)
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