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@INPROCEEDINGS{Geimer:1034058,
      author       = {Geimer, Markus},
      title        = {{P}arallel {P}erformance {A}nalysis},
      reportid     = {FZJ-2024-06879},
      year         = {2024},
      note         = {Tutorial slides},
      abstract     = {To effectively harness the computing capabilities of todays
                      and future supercomputing systems, performance analysis and
                      optimization should be a regular activity during scientific
                      software development. Instead of using do-it-yourself
                      solutions usually based on coarse-grained timers (e.g., time
                      per timestep or solver iteration), developers of scientific
                      code bases can resort to a variety of spezialized tools that
                      have been specifically developed to assist them with this
                      task. In this tutorial, we will introduce the open-source
                      tools Score-P and Cube, and explore their usage and
                      capabilities with a number of hands-on exercises.},
      month         = {Nov},
      date          = {2024-11-05},
      organization  = {3rd natESM Training Workshop, Jülich
                       (Germany), 5 Nov 2024 - 6 Nov 2024},
      subtyp        = {Other},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
                      and Research Groups (POF4-511) / ATMLPP - ATML Parallel
                      Performance (ATMLPP)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(DE-Juel-1)ATMLPP},
      typ          = {PUB:(DE-HGF)31},
      doi          = {10.34734/FZJ-2024-06879},
      url          = {https://juser.fz-juelich.de/record/1034058},
}