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@ARTICLE{Winkelmann:848080,
      author       = {Winkelmann, Jan and Springer, Paul and Di Napoli, Edoardo},
      title        = {{C}h{ASE}: {C}hebyshev {A}ccelerated {S}ubspace iteration
                      {E}igensolver for sequences of {H}ermitian eigenvalue
                      problems},
      journal      = {ACM transactions on mathematical software},
      volume       = {45},
      number       = {2},
      issn         = {0098-3500},
      address      = {New York, NY},
      publisher    = {ACM},
      reportid     = {FZJ-2018-03363},
      pages        = {21},
      year         = {2019},
      abstract     = {Solving dense Hermitian eigenproblems arranged in a
                      sequence with direct solvers fails to take advantage of
                      those spectral properties that are pertinent to the entire
                      sequence and not just to the single problem. When such
                      features take the form of correlations between the
                      eigenvectors of consecutive problems, as is the case in many
                      real-world applications, the potential benefit of exploiting
                      them can be substantial. We present the Chebyshev
                      Accelerated Subspace iteration Eigensolver (ChASE), a modern
                      algorithm and library based on subspace iteration with
                      polynomial acceleration. Novel to ChASE is the computation
                      of the spectral estimates that enter in the filter and an
                      optimization of the polynomial degree that further reduces
                      the necessary floating-point operations. ChASE is written in
                      C++ using the modern software engineering concepts that
                      favor a simple integration in application codes and a
                      straightforward portability over heterogeneous platforms.
                      When solving sequences of Hermitian eigenproblems for a
                      portion of their extremal spectrum, ChASE greatly benefits
                      from the sequence’s spectral properties and outperforms
                      direct solvers in many scenarios. The library ships with two
                      distinct parallelization schemes, supports execution over
                      distributed GPUs, and is easily extensible to other parallel
                      computing architectures.},
      cin          = {JSC},
      ddc          = {620},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / PhD no Grant - Doktorand ohne besondere
                      Förderung (PHD-NO-GRANT-20170405) / Simulation and Data
                      Laboratory Quantum Materials (SDLQM) (SDLQM)},
      pid          = {G:(DE-HGF)POF3-511 / G:(DE-Juel1)PHD-NO-GRANT-20170405 /
                      G:(DE-Juel1)SDLQM},
      typ          = {PUB:(DE-HGF)16},
      eprint       = {1805.10121},
      howpublished = {arXiv:1805.10121},
      archivePrefix = {arXiv},
      SLACcitation = {$\%\%CITATION$ = $arXiv:1805.10121;\%\%$},
      UT           = {WOS:000482133700008},
      doi          = {10.1145/3313828},
      url          = {https://juser.fz-juelich.de/record/848080},
}