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@MISC{Baumeister:1028638,
      author       = {Baumeister, Paul and Nassyr, Stepan and Li, Yanlong},
      title        = {tf{QMR}gpu v0.9 - a header-only {GPU}-accelerated iterative
                      linear solver for multiple right-hand sides},
      reportid     = {FZJ-2024-04705},
      year         = {2023},
      abstract     = {tfQMRgpu is a C++ header-only library written in CUDA.
                      Version 0.9 aims to offer the transpose-free Quasi Minimal
                      Residual method for the iterative solving of linear problems
                      with multiple right-hand sides using graphical processors
                      (GPUs).The library is shipped with the default use case of
                      complex block-sparse operators with a set of available block
                      sizes to be selected before compilation. C-interfaces expose
                      the APIs for both, single precision (float) and double
                      precision, to be called from other programming languages
                      such as C, Fortran, Julia or Python.The block-sparse matrix
                      solver version can be linked as shared object
                      tfQMRgpu.so.The header-only feature allows to provide a
                      custom C++/CUDA action operators to
                      $tfQMRgpu::solve<action_t>$ and compiles with the host
                      code.},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511)},
      pid          = {G:(DE-HGF)POF4-5111},
      typ          = {PUB:(DE-HGF)33},
      doi          = {10.5281/ZENODO.8333498},
      url          = {https://juser.fz-juelich.de/record/1028638},
}