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@MISC{Feld:1043551,
      author       = {Feld, Christian and Jäkel, René and Lorenz, Daniel and
                      Wesarg, Bert and Schmidl, Dirk and Tschüter, Ronny and
                      Oleynik, Yury and Wagner, Michael and Eschweiler, Dominic
                      and Spazier, Johannes and Knüpfer, Andreas and Shende,
                      Sameer and Millstein, Suzanne and Biersdorff, Scott and
                      Geimer, Markus and Schlütter, Marc and Schmitt, Felix and
                      Ziegenbalg, Johannes and Zhukov, Ilya and Dietrich, Robert
                      and Geyer, Robin and Saviankou, Pavel and Knobloch, Michael
                      and Mijaković, Robert and Schöne, Robert and Winkler,
                      Frank and Ilsche, Thomas and Hermanns, Marc-André and
                      Brendel, Ronny and Oeste, Sebastian and Herold, Christian
                      and Sigl, Severin and Hilbrich, Tobias and Williams, Bill
                      and Klotz, Sven and Corbin, Gregor and Reuter, Jan André
                      and Grund, Alexander and Sander, Maximilian and Frenzel,
                      Jan},
      title        = {{S}core-{P}: {S}calable performance measurement
                      infrastructure for parallel codes (v9.1); v9.1},
      reportid     = {FZJ-2025-02925},
      year         = {2025},
      abstract     = {The instrumentation and measurement framework Score-P,
                      together with analysis tools build on top of its output
                      formats, provides insight into massively parallel HPC
                      applications, their communication, synchronization, I/O, and
                      scaling behavior to pinpoint performance bottlenecks and
                      their causes. Score-P is a highly scalable and easy-to-use
                      tool suite for profiling (summarizing program execution) and
                      event tracing (capturing events in chronological order) of
                      HPC applications. The scorep instrumentation command adds
                      instrumentation hooks into a user's application by either
                      prepending or replacing the compile and link commands. C,
                      C++, Fortran, and Python codes as well as contemporary HPC
                      programming models (MPI, threading, GPUs, I/O) are
                      supported. When running an instrumented application,
                      measurement event data is provided by the instrumentation
                      hooks to the measurement core. There, the events are
                      augmented with high-accuracy timestamps and potentially
                      hardware counters (a plugin-API allows querying additional
                      metric sources). The augmented events are then passed to one
                      or both of the built-in event consumers, profiling and
                      tracing (a plugin-API allows creation of additional event
                      consumers) which finally provide output in the formats CUBE4
                      and OTF2, respectively. These open and backwards-compatible
                      output formats can be consumed by established analysis
                      tools, e.g., like CubeGUI, the performance report explorer
                      for Scalasca and Score-P, a generic tool for displaying a
                      multidimensional performance space, Extra-P, an automatic
                      performance-modelling tool that supports the user in the
                      identification of scalability bugs, TAU's ParaProf, a
                      portable, scalable performance analysis tool, and
                      PerfExplorer, a framework for parallel performance data
                      mining and knowledge discovery, Scalasca Trace Tools, a
                      collection of trace-based performance analysis tools that
                      have been specifically designed for use on large-scale
                      systems featuring hundreds of thousands of CPU cores,
                      automatically identifying potential communication and
                      synchronization bottlenecks and offering guidance in
                      exploring their causes, and Vampir, a trace-based framework
                      that enables users to quickly display and analyze arbitrary
                      program behavior. Score-P is available under the 3-clause
                      BSD Open Source license. Version 9.1 is is a bugfix release
                      for version 9.0. For features/changes/improvements
                      introduced in the latest version, please see the Changelog
                      file.},
      keywords     = {Performance measurement (Other) / Score-P (Other) /
                      instrumentation (Other) / sampling (Other) / HPC (Other) /
                      profiling (Other) / tracing (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) / ATMLAO - ATML Application
                      Optimization and User Service Tools (ATMLAO)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(DE-Juel-1)ATMLPP /
                      G:(DE-Juel-1)ATMLAO},
      typ          = {PUB:(DE-HGF)33},
      doi          = {10.5281/ZENODO.15772775},
      url          = {https://juser.fz-juelich.de/record/1043551},
}