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@MISC{Diaz:857783,
      author       = {Diaz, Sandra and Deepu, Rajalekshmi and Peyser, Alexander
                      and Klijn, Wouter},
      title        = {{T}raining course "{P}orting code from {M}atlab to
                      {P}ython"},
      reportid     = {FZJ-2018-06750},
      year         = {2018},
      abstract     = {Python is becoming a popular language for scientific
                      applications and is increasingly used for high performance
                      computing. In this course we want to introduce Matlab
                      programmers to the usage of Python. Matlab and Python have a
                      comparable language philosophy, but Python can offer better
                      performance using its optimizations and parallelization
                      interfaces. Python also increases the portability and
                      flexibility (interaction with other open source and
                      proprietary software packages) of solutions, and can be run
                      on supercomputing resources without high licensing costs.The
                      training course will be divided into three stages: First,
                      attendants will learn how to do a direct translation of
                      language concepts from Matlab to Python. Then, optimization
                      of scripts using more Pythonic data structures and functions
                      will be shown. Finally, code will be taken to the
                      supercomputers where basic parallel programming (MPI) will
                      be used to exploit parallelism in the computation.The course
                      will focus on numerical and statistical analysis as well as
                      on image processing applications.This course involves
                      theoretical and hands on sessions which will be guided by
                      experts in Python, Matlab and High Performance Computing.
                      Attendants are highly encouraged to bring their own Matlab
                      scripts.},
      month         = {Oct},
      date          = {2018-10-08},
      organization  = {Jülich (Germany), 8 Oct 2018 - 9 Oct
                       2018},
      subtyp        = {Other},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {511 - Computational Science and Mathematical Methods
                      (POF3-511) / 574 - Theory, modelling and simulation
                      (POF3-574) / SMHB - Supercomputing and Modelling for the
                      Human Brain (HGF-SMHB-2013-2017) / HBP SGA2 - Human Brain
                      Project Specific Grant Agreement 2 (785907) / Virtual
                      Connectomics - Deutschland - USA Zusammenarbeit in
                      Computational Science: Mechanistische Zusammenhänge
                      zwischen Struktur und funktioneller Dynamik im menschlichen
                      Gehirn (BMBF-01GQ1504B) / SLNS - SimLab Neuroscience
                      (Helmholtz-SLNS)},
      pid          = {G:(DE-HGF)POF3-511 / G:(DE-HGF)POF3-574 /
                      G:(DE-Juel1)HGF-SMHB-2013-2017 / G:(EU-Grant)785907 /
                      G:(DE-Juel1)BMBF-01GQ1504B / G:(DE-Juel1)Helmholtz-SLNS},
      typ          = {PUB:(DE-HGF)17},
      url          = {https://juser.fz-juelich.de/record/857783},
}