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@ARTICLE{Myers:619284,
      author       = {Myers, Andrew and Zhang, Weiqun and Almgren, Ann and
                      Antoun, Thierry and Bell, John and Huebl, Axel and Sinn,
                      Alexander},
      title        = {{AMR}e{X} and py{AMR}e{X}: {L}ooking beyond the exascale
                      computing project},
      journal      = {The international journal of high performance computing
                      applications},
      volume       = {38},
      number       = {6},
      issn         = {1094-3420},
      address      = {Thousand Oaks, Calif.},
      publisher    = {Sage Science Press},
      reportid     = {PUBDB-2024-07532},
      pages        = {599-611},
      year         = {2024},
      note         = {Waiting for fulltext},
      abstract     = {AMReX is a software framework for the development of
                      block-structured mesh applications with adaptive mesh
                      refinement (AMR). AMReX was initially developed and
                      supported by the AMReX Co-Design Center as part of the U.S.
                      DOE Exascale Computing Project (ECP), and is continuing to
                      grow post-ECP. In addition to adding new functionality and
                      performance improvements to the core AMReX framework, we
                      have also developed a Python binding, pyAMReX, that provides
                      a bridge between AMReX-based application codes and the data
                      science ecosystem. pyAMReX provides zero-copy application
                      GPU data access for AI/ML, in situ analysis and application
                      coupling, and enables rapid, massively parallel prototyping.
                      In this paper we review the overall functionality of AMReX
                      and pyAMReX, focusing on new developments, new
                      functionality, and optimizations of key operations. We also
                      summarize capabilities of ECP projects that used AMReX and
                      provide an overview of new, non-ECP applications.},
      cin          = {MPA1},
      ddc          = {004},
      cid          = {I:(DE-H253)MPA1-20210408},
      pnm          = {621 - Accelerator Research and Development (POF4-621)},
      pid          = {G:(DE-HGF)POF4-621},
      experiment   = {EXP:(DE-MLZ)NOSPEC-20140101},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001307506500001},
      doi          = {10.1177/10943420241271017},
      url          = {https://bib-pubdb1.desy.de/record/619284},
}