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@ARTICLE{Nikitenko:894423,
      author       = {Nikitenko, D. A. and Wolf, F. and Mohr, B. and Hoefler, T.
                      and Stefanov, K. S. and Voevodin, Vad. V. and Antonov, A. S.
                      and Calotoiu, A.},
      title        = {{I}nfluence of {N}oisy {E}nvironments on {B}ehavior of
                      {HPC} {A}pplications},
      journal      = {Lobachevskii journal of mathematics},
      volume       = {42},
      number       = {7},
      issn         = {1818-9962},
      address      = {Heidelberg},
      publisher    = {Springer},
      reportid     = {FZJ-2021-03216},
      pages        = {1560 - 1570},
      year         = {2021},
      abstract     = {Many contemporary HPC systems expose their jobs to
                      substantial amounts of interference, leading to significant
                      run-to-run variation. For example, application runtimes on
                      Theta, a Cray XC40 system at Argonne National Laboratory,
                      vary by up to $70\%,$ caused by a mix of node-level and
                      system-level effects, including network and file-system
                      congestion in the presence of concurrently running jobs.
                      This makes performance measurements generally
                      irreproducible, heavily complicating performance analysis
                      and modeling. On noisy systems, performance analysts usually
                      have to repeat performance measurements several times and
                      then apply statistics to capture trends. First, this is
                      expensive and, second, extracting trends from a limited
                      series of experiments is far from trivial, as the noise can
                      follow quite irregular patterns. Attempts to learn from
                      performance data how a program would perform under different
                      execution configurations experience serious perturbation,
                      resulting in models that reflect noise rather than intrinsic
                      application behavior. On the other hand, although noise
                      heavily influences execution time and energy consumption, it
                      does not change the computational effort a program performs.
                      Effort metrics that count how many operations a machine
                      executes on behalf of a program, such as floating-point
                      operations, the exchange of MPI messages, or file reads and
                      writes, remain largely unaffected and—rare non-determinism
                      set aside—reproducible. This paper addresses initial stage
                      of an ExtraNoise project, which is aimed at revealing and
                      tackling key questions of system noise influence on HPC
                      applications.},
      cin          = {JSC},
      ddc          = {510},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
                      and Research Groups (POF4-511) / ExtraNoise –
                      Leistungsanalyse von HPC-Anwendungen in verrauschten
                      Umgebungen (449683531) / ATMLPP - ATML Parallel Performance
                      (ATMLPP)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(GEPRIS)449683531 /
                      G:(DE-Juel-1)ATMLPP},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000683368000009},
      doi          = {10.1134/S1995080221070192},
      url          = {https://juser.fz-juelich.de/record/894423},
}