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SUMMARY:Reducing Data Movement Through Derived Quantity Generation
DTSTART;VALUE=DATE-TIME:20241203T133000Z
DTEND;VALUE=DATE-TIME:20241203T135000Z
DTSTAMP;VALUE=DATE-TIME:20260516T045741Z
UID:indico-contribution-2411@events.chpc.ac.za
DESCRIPTION:Speakers: Jay Lofstead* (Sandia National Laboratories)\nLearni
 ng from scientific simulations often relies not on the raw quantities calc
 ulated\, but instead from derived values. For example\, air pressures in a
  weather simulation in isolation are not as interesting as the air pressur
 e gradient. If the gradients are roughly parallel\, you have straight-line
  winds. If the gradient is rotating around a point\, it is a cyclone storm
 . Other uses\, such as reducing from a complex multi-quantity 3D model int
 o a 2D representation for the actual value required for analysis can radic
 ally reduce data movement from the large computational system to the local
  analysis system. We have built tools that enable automatically calculatin
 g these derived quantities as part of normal simulation output to enable e
 xtracting the derived quantities for movement to a different machine and o
 ther purposes.\n\nhttps://events.chpc.ac.za/event/139/contributions/2411/
LOCATION:Boardwalk Convention Centre BICC.G-D1 - D1 Tsitsikamma
URL:https://events.chpc.ac.za/event/139/contributions/2411/
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