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@ARTICLE{Shudler:872819,
      author       = {Shudler, Sergei and Berens, Yannick and Calotoiu, Alexandru
                      and Hoefler, Torsten and Strube, Alexandre and Wolf, Felix},
      title        = {{E}ngineering {A}lgorithms for {S}calability through
                      {C}ontinuous {V}alidation of {P}erformance {E}xpectations},
      journal      = {IEEE transactions on parallel and distributed systems},
      volume       = {30},
      number       = {8},
      issn         = {1045-9219},
      address      = {New York, NY},
      publisher    = {IEEE},
      reportid     = {FZJ-2020-00291},
      pages        = {1768 - 1785},
      year         = {2019},
      note         = {Bitte Post-Print ergänzen},
      abstract     = {Many libraries in the HPC field use sophisticated
                      algorithms with clear theoretical scalability expectations.
                      However, hardware constraints or programming bugs may
                      sometimes render these expectations inaccurate or even
                      plainly wrong. While algorithm and performance engineers
                      have already been advocating the systematic combination of
                      analytical performance models with practical measurements
                      for a very long time, we go one step further and show how
                      this comparison can become part of automated testing
                      procedures. The most important applications of our method
                      include initial validation, regression testing, and
                      benchmarking to compare implementation and platform
                      alternatives. Advancing the concept of performance
                      assertions, we verify asymptotic scaling trends rather than
                      precise analytical expressions, relieving the developer from
                      the burden of having to specify and maintain very
                      fine-grained and potentially non-portable expectations. In
                      this way, scalability validation can be continuously applied
                      throughout the whole development cycle with very little
                      effort. Using MPI and parallel sorting algorithms as
                      examples, we show how our method can help uncover
                      non-obvious limitations of both libraries and underlying
                      platforms.},
      ddc          = {004},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / Scalable Performance Analysis of Large-Scale
                      Parallel Applications $(jzam11_20091101)$ / ATMLPP - ATML
                      Parallel Performance (ATMLPP)},
      pid          = {G:(DE-HGF)POF3-511 / $G:(DE-Juel1)jzam11_20091101$ /
                      G:(DE-Juel-1)ATMLPP},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.1109/TPDS.2019.2896993},
      url          = {https://juser.fz-juelich.de/record/872819},
}