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LOCATION:HG E 1.1
DTSTART;TZID=Europe/Stockholm:20240603T173000
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UID:submissions.pasc-conference.org_PASC24_sess175_pap138@linklings.com
SUMMARY:Libyt: A Tool for Parallel In Situ Analysis with yt, Python, and J
 upyter
DESCRIPTION:Paper\n\nShin-Rong Tsai (University of Illinois Urbana-Champai
 gn, National Taiwan University); Hsi-Yu Schive (National Taiwan University
 , National Center for Theoretical Sciences); and Matthew Turk (University 
 of Illinois Urbana-Champaign)\n\nIn the era of extreme-scale computing, la
 rge-scale data storage and analysis have become more critical and challeng
 ing. For post-processing, the simulation first needs to dump snapshots on 
 a hard disk before processing any data. This becomes a bottleneck for high
  spatial and temporal resolution simulation. In situ analysis provides a v
 iable solution for analyzing extreme scale simulations by processing data 
 in memory, which skips the step of storing data on disk. We present libyt,
  an open-source C library that allows researchers to analyze and visualize
  data using yt or other Python packages in parallel computing during simul
 ation runtime. We describe the code method for connecting simulation runti
 me data to Python, handling data transition and redistribution between Pyt
 hon and simulation processes with minimal memory overhead, and supporting 
 interactive Python prompt and Jupyter Notebook for users to probe the ongo
 ing simulation data at the current time step. We demonstrate how it solves
  the problem of visualizing large-scale astrophysical simulations, improvi
 ng disk usage efficiency, and monitoring simulations closely. We conclude 
 it with discussions and compare libyt to post-processing.\n\nDomain: Physi
 cs\n\nSession Chair: Emily Bourne (EPFL)
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