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@ARTICLE{Witzler:1033636,
      author       = {Witzler, Christian and Guimarães, Filipe Souza Mendes and
                      Mira, Daniel and Anzt, Hartwig and Göbbert, Jens Henrik and
                      Frings, Wolfgang and Bode, Mathis},
      title        = {{J}u{M}on{C}: {A} {REST}ful tool for enabling monitoring
                      and control of simulations at scale},
      journal      = {Future generation computer systems},
      volume       = {164},
      issn         = {0167-739X},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2024-06508},
      pages        = {107541 -},
      year         = {2025},
      abstract     = {As systems and simulations grow in size and complexity, it
                      is challenging to maintain efficient use of resources and
                      avoid failures. In this scenario, monitoring becomes even
                      more important and mandatory. This paper describes and
                      discusses the benefits of the advanced monitoring and
                      control tool JuMonC, which runs under user control alongside
                      HPC simulations and provides valuable metrics via REST-API.
                      In addition, plugin extensibility allows JuMonC to go a step
                      further and provide computational steering of the simulation
                      itself. To demonstrate the benefits and usability of JuMonC
                      for large-scale simulations, two use cases are described
                      employing nekRS and ICON on JURECA-DC, a supercomputer
                      located at the Jülich Supercomputing Centre (JSC).
                      Furthermore, a large-scale use case with nekRS on JSC’s
                      flagship system JUWELS Booster is described. Finally, the
                      interplay between JuMonC and LLview (a standard monitoring
                      tool for HPC systems) is presented using a simple and secure
                      JuMonC-LLview plugin, which collects performance metrics and
                      enables their analysis in LLview. Overall, the portability
                      and usefulness of JuMonC, together with its low performance
                      impact, make it an important application for both current
                      and future generations of exascale HPC systems.},
      cin          = {JSC},
      ddc          = {004},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
                      and Research Groups (POF4-511) / CoEC - Center of Excellence
                      in Combustion (952181) / IO-SEA - IO Software for Exascale
                      Architecture (955811) / DEEP-SEA - DEEP – SOFTWARE FOR
                      EXASCALE ARCHITECTURES (955606) / JLESC - Joint Laboratory
                      for Extreme Scale Computing (JLESC-20150708) / ATMLAO - ATML
                      Application Optimization and User Service Tools (ATMLAO)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(EU-Grant)952181 /
                      G:(EU-Grant)955811 / G:(EU-Grant)955606 /
                      G:(DE-Juel1)JLESC-20150708 / G:(DE-Juel-1)ATMLAO},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001358353300001},
      doi          = {10.1016/j.future.2024.107541},
      url          = {https://juser.fz-juelich.de/record/1033636},
}