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DTSTAMP:20181221T160728Z
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:Workshop\nData Analytics, Data Management, Visualization, Work
 shop Reg Pass\n\nPython-Based In Situ Analysis and Visualization\n\nLoring
 , Myers, Camp, Bethel\n\nThis work focuses on enabling the use of Python-b
 ased methods for the purpose of performing in situ analysis and visualizat
 ion. This approach facilitates access to and use of a rapidly growing coll
 ection of Python-based, third-party libraries for analysis and visualizati
 on, as well as lowering the barrier to entry for user-written Python analy
 sis codes. Beginning with a simulation code that is instrumented to use th
 e SENSEI in situ interface, we present how to couple it with a Python-base
 d data consumer, which may be run in situ, and in parallel at the same con
 currency as the simulation. We present two examples that demonstrate the n
 ew capability. One is an analysis of the reaction rate in a proxy simulati
 on of a chemical reaction on a 2D substrate, while the other is a coupling
  of an AMR simulation to Yt, a parallel visualization and analysis library
  written in Python. In the examples, both the simulation and Python in sit
 u method run in parallel on a large-scale HPC platform.
URL:https://sc18.supercomputing.org/presentation/?id=ws_isav107&sess=sess1
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