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@INPROCEEDINGS{Erlingsson:867901,
      author       = {Erlingsson, Ernir and Cavallaro, Gabriele and Neukirchen,
                      Helmut and Riedel, Morris},
      title        = {{S}calable {W}orkflows for {R}emote {S}ensing {D}ata
                      {P}rocessing with the {D}eep-{E}st {M}odular
                      {S}upercomputing {A}rchitecture},
      publisher    = {IEEE},
      reportid     = {FZJ-2019-06503},
      pages        = {5905-5908},
      year         = {2019},
      abstract     = {The implementation of efficient remote sensing workflows
                      isessential to improve the access to and analysis of the
                      vastamount of sensed data and to provide decision-makers
                      withclear, timely, and useful information. The Dynamical
                      Exascale Entry Platform (DEEP) is an European
                      pre-exascaleplatform that incorporates heterogeneous
                      High-PerformanceComputing (HPC) systems, i.e., hardware
                      modules which include specialised accelerators. This paper
                      demonstrates thepotential of such diverse modules for the
                      deployment of remote sensing data workflows that include
                      diverse processing tasks. Particular focus is put on
                      pipelines which can usethe Network Attached Memory (NAM),
                      which is a novel supercomputer module that allows near
                      processing and/or fastshared storage of big remote sensing
                      datasets.},
      month         = {Jul},
      date          = {2019-07-28},
      organization  = {IGARSS 2019 - 2019 IEEE International
                       Geoscience and Remote Sensing
                       Symposium, Yokohama (Japan), 28 Jul
                       2019 - 2 Aug 2019},
      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},
      UT           = {WOS:000519270605170},
      doi          = {10.1109/IGARSS.2019.8898487},
      url          = {https://juser.fz-juelich.de/record/867901},
}