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@MISC{Herten:1019123,
      author       = {Herten, Andreas and Meinke, Jan and Haghighi Mood, Kaveh
                      and Kraus, Jiri and Hrywniak, Markus},
      title        = {{GPU} {P}rogramming {P}art 1: {F}oundations},
      reportid     = {FZJ-2023-05176},
      year         = {2023},
      abstract     = {GPU-accelerated computing drives current scientific
                      research. Writing fast numeric algorithms for GPUs offers
                      high application performance by offloading compute-intensive
                      portions of the code to a GPU.The course covers aspects of
                      GPU architectures and programming. Focus is on the usage of
                      the parallel programming language CUDA C++, which allows
                      maximum control of NVIDIA GPU hardware. Examples of
                      increasing complexity are used to demonstrate optimization
                      and tuning of scientific applications.For the first time,
                      the GPU Programming with CUDA course is held in two parts.
                      This course is a basic course covering the foundations of
                      GPU programming including an introduction to GPU/parallel
                      computing, programming with CUDA, GPU libraries, tools for
                      debugging and profiling, and performance optimizations.An
                      advanced course with more involved and specific topics is
                      available as an individual entry.},
      month         = {Apr},
      date          = {2023-04-17},
      organization  = {JSC - as part of the Training
                       Programme of Forschungszentrum Jülich,
                       Jülich (Germany), 17 Apr 2023 - 19 Apr
                       2023},
      subtyp        = {Other},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
                      and Research Groups (POF4-511) / 5122 - Future Computing
                      $\&$ Big Data Systems (POF4-512) / 5111 - Domain-Specific
                      Simulation $\&$ Data Life Cycle Labs (SDLs) and Research
                      Groups (POF4-511) / ATML-X-DEV - ATML Accelerating Devices
                      (ATML-X-DEV)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(DE-HGF)POF4-5122 /
                      G:(DE-HGF)POF4-5111 / G:(DE-Juel-1)ATML-X-DEV},
      typ          = {PUB:(DE-HGF)17},
      doi          = {10.34734/FZJ-2023-05176},
      url          = {https://juser.fz-juelich.de/record/1019123},
}