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DTSTART;TZID=America/Denver:20231112T144200
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UID:submissions.supercomputing.org_SC23_sess439_ws_worksp115@linklings.com
SUMMARY:End-to-End Workflows for Climate Science:  Integrating HPC Simulat
 ions, Big Data Processing, and Machine Learning
DESCRIPTION:Donatello Elia and Sonia Scardigno (Fondazione Centro Euro-Med
 iterraneo sui Cambiamenti Climatici); Jorge Ejarque (Barcelona Supercomput
 ing Center (BSC)); Alessandro D’Anca, Gabriele Accarino, Enrico Scoccimarr
 o, Davide Donno, and Daniele Peano (Fondazione Centro Euro-Mediterraneo su
 i Cambiamenti Climatici); and Francesco Immorlano and Giovanni Aloisio (Fo
 ndazione Centro Euro-Mediterraneo sui Cambiamenti Climatici; Department of
  Innovation Engineering, University of Salento)\n\nCurrent scientific work
 flow systems do not typically integrate simulation-centric and data-centri
 c aspects due to their very different software/infrastructure requirements
 . A transparent integration of such components into a single end-to-end wo
 rkflow would lead to a more efficient and automated way for generating ins
 ights from large simulation data. This work presents a complex case study 
 related to extreme events analysis of future climate data that integrates 
 in the same workflow numerical simulations, Big Data analytics and Machine
  Learning models. The case study is being implemented in the context of th
 e eFlows4HPC project using the project's software stack for deployment and
  orchestration of the workflow. The solution implemented in the project ha
 s shown to simplify the development and execution of end-to-end climate wo
 rkflows with heterogeneous software requirements. Moreover, such an approa
 ch can, in the long term, increase the reuse of workflows by scientists an
 d their portability over different HPC infrastructures.\n\nTag: Applicatio
 ns, Cloud Computing, Distributed Computing, Edge Computing, Large Scale Sy
 stems\n\nRegistration Category: Workshop Reg Pass\n\nSession Chairs: Silvi
 na Caino-Lores (National Institute for Research in Digital Science and Tec
 hnology (Inria)) and Anirban Mandal (Renaissance Computing Institute (RENC
 I), University of North Carolina at Chapel Hill)\n\n
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