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@INBOOK{Kohnke:889150,
      author       = {Kohnke, Bartosz and Ullmann, Thomas R. and Beckmann,
                      Andreas and Kabadshow, Ivo and Haensel, David and
                      Morgenstern, Laura and Dobrev, Plamen and Groenhof, Gerrit
                      and Kutzner, Carsten and Hess, Berk and Dachsel, Holger and
                      Grubmüller, Helmut},
      title        = {{GROMEX}: {A} {S}calable and {V}ersatile {F}ast {M}ultipole
                      {M}ethod for {B}iomolecular {S}imulation},
      address      = {Cham},
      publisher    = {Springer International Publishing},
      reportid     = {FZJ-2021-00075},
      series       = {Lecture Notes in Computational Science and Engineering},
      pages        = {517-543},
      year         = {2020},
      note         = {DOI: $10.1007/978-3-030-47956-5_17$},
      comment      = {Software for Exascale Computing - SPPEXA 2016-2019},
      booktitle     = {Software for Exascale Computing -
                       SPPEXA 2016-2019},
      abstract     = {Atomistic simulations of large biomolecular systems with
                      chemical variability such as constant pH dynamic protonation
                      offer multiple challenges in high performance computing. One
                      of them is the correct treatment of the involved
                      electrostatics in an efficient and highly scalable way. Here
                      we review and assess two of the main building blocks that
                      will permit such simulations: (1) An electrostatics library
                      based on the Fast Multipole Method (FMM) that treats local
                      alternative charge distributions with minimal overhead, and
                      (2) A λ-dynamics module working in tandem with the FMM that
                      enables various types of chemical transitions during the
                      simulation. Our λ-dynamics and FMM implementations do not
                      rely on third-party libraries but are exclusively using C++
                      language features and they are tailored to the specific
                      requirements of molecular dynamics simulation suites such as
                      GROMACS. The FMM library supports fractional tree depths and
                      allows for rigorous error control and automatic performance
                      optimization at runtime. Near-optimal performance is
                      achieved on various SIMD architectures and on GPUs using
                      CUDA. For exascale systems, we expect our approach to
                      outperform current implementations based on Particle Mesh
                      Ewald (PME) electrostatics, because FMM avoids the
                      communication bottlenecks caused by the parallel fast
                      Fourier transformations needed for PME.},
      cin          = {JSC / IAS-7},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)IAS-7-20180321},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / SPPEXA - Software for Exascale Computing
                      (214420555) / PhD no Grant - Doktorand ohne besondere
                      Förderung (PHD-NO-GRANT-20170405)},
      pid          = {G:(DE-HGF)POF3-511 / G:(GEPRIS)214420555 /
                      G:(DE-Juel1)PHD-NO-GRANT-20170405},
      typ          = {PUB:(DE-HGF)7},
      url          = {https://juser.fz-juelich.de/record/889150},
}