Python-based in situ analysis and visualization

Conference · Sun Dec 31 23:00:00 EST 2017

DOI:https://doi.org/10.1145/3281464.3281465· OSTI ID:1602814

Loring, Burlen ^[1]; Myers, Andrew ^[1]; Camp, David ^[1]; Bethel, E Wes ^[1]

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1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

This 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 rapidly growing collection of Python-based, third-party libraries for analysis and visualization, as well as lowering the barrier to entry for user-written Python analysis codes. Beginning with a simulation code that is instrumented to use the SENSEI in situ interface, we present how to couple it with 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 demonstrate 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 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 situ method run in parallel on a large-scale HPC platform.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
• DOE Contract Number: AC02-05CH11231
• OSTI ID: 1602814
• Country of Publication: United States
• Language: English