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DTSTAMP:20260422T000713Z
LOCATION:506
DTSTART;TZID=America/Denver:20231113T111000
DTEND;TZID=America/Denver:20231113T113000
UID:submissions.supercomputing.org_SC23_sess452_ws_isav104@linklings.com
SUMMARY:Trigger Smart Data Saving Applied to CO2 Capture in Metal-Organic 
 Frameworks
DESCRIPTION:Estelle Dirand, Ali Asad, and Yann Magnin (TotalEnergies SE)\n
 \nFacing the need for carbon emission reduction, processes such as CO2 cap
 ture in nanoporous Metal-Organic Frameworks (MOFs) have emerged. However, 
 such processes still need to be improved, by understanding the dynamic pro
 perties of CO2 molecules when confined in MOF nanopores. To do so, molecul
 ar dynamics (MD) simulations are run for several millions of iterations, e
 nabling to accurately compute the CO2 residency time. Nevertheless, this d
 ynamical parameter remains challenging to compute by standard post-process
 ing approaches and may require terabytes of memory when data are saved aft
 er each iteration. To tackle this issue, we developed a trigger-based in s
 itu approach that saves only the relevant data. We implement it by instrum
 enting the LAMMPS MD code with the SENSEI/Python in situ API. We show that
  this approach reduces the quantity of data saved by 4 orders of magnitude
  and can be up to 14% faster than traditional MD simulations without in si
 tu processing.\n\nTag: Data Analysis, Visualization, and Storage, Large Sc
 ale Systems, Performance Measurement, Modeling, and Tools\n\nRegistration 
 Category: Workshop Reg Pass\n\nSession Chairs: E. Wes Bethel (San Francisc
 o State University, Lawrence Berkeley National Laboratory (LBNL)); Nicola 
 Ferrier (Argonne National Laboratory (ANL), University of Chicago); Axel H
 uebl (Lawrence Berkeley National Laboratory (LBNL)); Tom Vierjahn (Westpha
 lian University of Applied Sciences); and Sean Ziegeler (US Department of 
 Defense HPC Modernization Program, Department of Defense High Performance 
 Computing Modernization Program (DoD HPCMP))\n\n
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