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DTSTART;TZID=America/Denver:20231113T142700
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UID:submissions.supercomputing.org_SC23_sess442_ws_whpc116@linklings.com
SUMMARY:Operationalizing HPC Tasks for Space Weather Forecasting Using Cel
 ery and Django:  Making Automated, HPC-Powered Scientific Results Accessib
 le in Near-Real Time.
DESCRIPTION:Workshop\n\nJenny Wong (University of Birmingham, UK)\n\nForec
 asting space weather conditions in the Earth’s ionosphere is critical to p
 rotecting key infrastructure, such as satellite-based positioning and navi
 gation systems, high-frequency radio communications, and the electric powe
 r grid. Variations in space weather are caused by coronal mass ejections f
 rom the Sun’s surface, energizing electrons in the ionosphere to produce d
 isturbances in communications and electrical systems, as well as spectacul
 ar aurorae.\n\nWe present a system for operationalizing HPC tasks for data
  assimilation in space weather forecasting using Celery and Django. Celery
  is used to execute and distribute tasks asynchronously, while Django is a
  popular web framework. Our system integrates these tools to automate runn
 ing space weather simulations on an HPC cluster for data assimilation and 
 presenting outputs on a website in near real-time. Our system applies to a
  wide range of HPC tasks in research software, and we believe this is usef
 ul for researchers to operationalize similar workflows.\n\nTag: State of t
 he Practice\n\nRegistration Category: Workshop Reg Pass\n\nSession Chairs:
  Elsa J. Gonsiorowski (Lawrence Livermore National Laboratory (LLNL)) and 
 Mozhgan Kabiri chimeh (NVIDIA Corporation)
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