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@INPROCEEDINGS{Erlingsson:857816,
      author       = {Erlingsson, Ernir and Cavallaro, Gabriele and Riedel,
                      Morris and Neukirchen, Helmut},
      title        = {{S}caling {S}upport {V}ector {M}achines {T}owards
                      {E}xascale {C}omputing for {C}lassification of
                      {L}arge-{S}cale {H}igh-{R}esolution {R}emote {S}ensing
                      {I}mages},
      publisher    = {IEEE},
      reportid     = {FZJ-2018-06783},
      pages        = {1792-1795},
      year         = {2018},
      abstract     = {Progress in sensor technology leads to an ever-increasing
                      amount of remote sensing data which needs to be classified
                      in order to extract information. This big amount of data
                      requires parallel processing by running parallel
                      implementations of classification algorithms, such as
                      Support Vector Machines (SVMs), on High-Performance
                      Computing (HPC) clusters. Tomorrow's supercomputers will be
                      able to provide exascale computing performance by using
                      specialised hardware accelerators. However, existing
                      software processing chains need to be adapted to make use of
                      the best fitting accelerators. To address this problem, a
                      mapping of an SVM remote sensing classification chain to the
                      Dynamical Exascale Entry Platform (DEEP), a European
                      pre-exascale platform, is presented. It will allow to scale
                      SVM-based classifications on tomorrow's hardware towards
                      exascale performance.},
      month         = {Jul},
      date          = {2018-07-22},
      organization  = {IGARSS 2018 - 2018 IEEE International
                       Geoscience and Remote Sensing
                       Symposium, Valencia (Spain), 22 Jul
                       2018 - 27 Jul 2018},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {512 - Data-Intensive Science and Federated Computing
                      (POF3-512) / DEEP-EST - DEEP - Extreme Scale Technologies
                      (754304)},
      pid          = {G:(DE-HGF)POF3-512 / G:(EU-Grant)754304},
      typ          = {PUB:(DE-HGF)8},
      doi          = {10.1109/IGARSS.2018.8517378},
      url          = {https://juser.fz-juelich.de/record/857816},
}