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@INPROCEEDINGS{Krajsek:867721,
      author       = {Krajsek, Kai and Comito, Claudia and Götz, Markus and
                      Hagemeier, Björn and Knechtges, Philipp and Siggel, Martin},
      title        = {{T}he {H}elmholtz {A}nalytics {T}oolkit ({H}e{AT}) - {A}
                      {S}cientific {B}ig {D}ata {L}ibrary for {HPC} -},
      volume       = {40},
      address      = {Jülich},
      publisher    = {Forschungszentrum Jülich GmbH Zentralbibliothek},
      reportid     = {FZJ-2019-06336},
      isbn         = {978-3-95806-392-1},
      series       = {IAS Series},
      pages        = {57-60},
      year         = {2019},
      comment      = {Proceedings},
      booktitle     = {Proceedings},
      abstract     = {We present HeAT, a scientific big data librarysupporting
                      transparent computation on HPC systems. HeATbuilds on top of
                      PyTorch, which already provides many requiredfeatures like
                      automatic differentiation, CPU and GPU support,linear
                      algebra operations and basic MPI functionality as well asan
                      imperative programming paradigm allowing fast
                      prototypingessential in scientific research. These features
                      are generalized toa distributed tensor with a NumPy-like
                      interface allowing to port existing NumPy algorithms to HPC
                      systems nearly effortlessly.},
      month         = {Sep},
      date          = {2018-09-18},
      organization  = {Extreme Data Workshop 2018, Jülich
                       (Germany), 18 Sep 2018 - 19 Sep 2018},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / 512 - Data-Intensive Science and Federated
                      Computing (POF3-512) / HAF - Helmholtz Analytics Framework
                      (ZT-I-0003) / SLNS - SimLab Neuroscience (Helmholtz-SLNS)},
      pid          = {G:(DE-HGF)POF3-511 / G:(DE-HGF)POF3-512 /
                      G:(DE-HGF)ZT-I-0003 / G:(DE-Juel1)Helmholtz-SLNS},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      url          = {https://juser.fz-juelich.de/record/867721},
}