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DTSTART:19700308T020000
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DTSTAMP:20260522T150119Z
LOCATION:D168
DTSTART;TZID=America/Chicago:20181112T114500
DTEND;TZID=America/Chicago:20181112T121000
UID:submissions.supercomputing.org_SC18_sess140_ws_isav107@linklings.com
SUMMARY:Python-Based In Situ Analysis and Visualization
DESCRIPTION:Burlen Loring, Andrew Myers, David Camp, and E. Wes Bethel (La
 wrence Berkeley National Laboratory)\n\nThis work focuses on enabling the 
 use of Python-based methods for the purpose of performing in situ analysis
  and visualization. This approach facilitates access to and use of a rapid
 ly growing collection of Python-based, third-party libraries for analysis 
 and visualization, as well as lowering the barrier to entry for user-writt
 en Python analysis codes. Beginning with a simulation code that is instrum
 ented to use the SENSEI in situ interface, we present how to couple it wit
 h a Python-based data consumer, which may be run in situ, and in parallel 
 at the same concurrency as the simulation. We present two examples that de
 monstrate the new capability. One is an analysis of the reaction rate in a
  proxy simulation of a chemical reaction on a 2D substrate, while the othe
 r is a coupling of an AMR simulation to Yt, a parallel visualization and a
 nalysis library written in Python. In the examples, both the simulation an
 d Python in situ method run in parallel on a large-scale HPC platform.\n\n
 Tag: Data Analytics, Data Management, Visualization\n\nRegistration Catego
 ry: Workshop Reg Pass\n\nSession Chairs: Earl P.N. Duque (Intelligent Ligh
 t); Nicola Ferrier (Argonne National Laboratory (ANL), University of Chica
 go); Kenneth Moreland (Oak Ridge National Laboratory (ORNL)); and Matthew 
 Wolf (Oak Ridge National Laboratory (ORNL))\n\n
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