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DTSTAMP:20190719T085745Z
LOCATION:HG E 3
DTSTART;TZID=Europe/Stockholm:20190614T110000
DTEND;TZID=Europe/Stockholm:20190614T113000
UID:submissions.pasc-conference.org_PASC19_sess165_msa318@linklings.com
SUMMARY:Machine Learning and Inference for Particle Physics with HPC and t
 he Cloud
DESCRIPTION:Minisymposium\nComputer Science and Applied Mathematics, Physi
 cs\n\nMachine Learning and Inference for Particle Physics with HPC and the
  Cloud\n\nCranmer, Heinrich\n\nThere is an explosion of interest in machin
 e learning in particle physics, which has significant impact on the data a
 nalysis strategies used by the large experiments and theoretical efforts l
 ike lattice QCD. Simultaneously, there is pressure on the particle physics
  community to adapt our computing models to align with the rise of cloud c
 omputing and major investments in exascale HPC machines. I will describe e
 xamples of recent projects that explore this intersection between inferenc
 e and computing.
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