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@INPROCEEDINGS{Gibbon:842520,
      author       = {Gibbon, Paul and Haefele, Matthieu and Rohe, Daniel and
                      Lührs, Sebastian and Ould-Rouis, Yacine and Latu, Guillaume
                      and Breuer, Thomas and Halver, Rene and Marin-Laflèche,
                      Abel and Lobet, Mathieu and Sharples, Wendy and Girard,
                      Nathalie and Audit, Edouard},
      title        = {{E}o{C}o{E} {P}erformance {B}enchmarking {M}ethodology for
                      {R}enewable {E}nergy {A}pplications},
      reportid     = {FZJ-2018-00744},
      year         = {2017},
      abstract     = {The global transition away from fossil fuels towards a
                      sustainable, decarbonized energy ecosystem will rely heavily
                      on digitization to drive necessary innovations in production
                      and storage technologies, mitigate power source
                      intermittency and manage its distribution via a complex grid
                      hierarchy. At the same time, supercomputing is also
                      experiencing a major paradigm shift: future exascale
                      technologies will open up unprecedented opportunities to
                      tackle complex physical problems – such as the design of
                      wind farms or smart materials for photovoltaics and
                      batteries – but will demand major restructuring of
                      application software, numerical algorithms and programming
                      models. These challenges motivated the creation of the
                      Energy Oriented Centre of Excellence (EoCoE) two years ago;
                      an EU-funded consortium twenty-one partners across eight
                      countries with strong engagements in both the HPC and energy
                      fields.This poster presents an optimisation strategy
                      developed by the Energy Oriented Centre of Excellence
                      (EoCoE) for computational models used in a variety of
                      renewable energy domains. It is found that typical
                      applications in this comparatively new sector cover the
                      widest possible range of HPC maturity, from simple
                      parallelization needs to near-exascale readiness. A key part
                      of this process has therefore been the quantitative,
                      reproducible performance assessment of applications
                      consolidated by follow-up actions by code-teams comprising
                      members of both developer groups and HPC centres involved
                      with the EoCoE consortium. Examples of early successes
                      achieved with this practice are given, together with an
                      outlook on challenges faced for energy applications with
                      next-generation, pre-exascale architectures.},
      month         = {Nov},
      date          = {2017-11-12},
      organization  = {Supercomputing 2017, Denver (USA), 12
                       Nov 2017 - 17 Nov 2017},
      subtyp        = {Other},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / EoCoE - Energy oriented Centre of Excellence
                      for computer applications (676629) / ATMLAO - ATML
                      Application Optimization and User Service Tools (ATMLAO)},
      pid          = {G:(DE-HGF)POF3-511 / G:(EU-Grant)676629 /
                      G:(DE-Juel-1)ATMLAO},
      typ          = {PUB:(DE-HGF)24},
      url          = {https://juser.fz-juelich.de/record/842520},
}