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@INPROCEEDINGS{GarciadeGonzalo:1049812,
      author       = {Garcia de Gonzalo, Simon and Herten, Andreas and Hrywniak,
                      Markus and Kraus, Jiri and Oden, Lena and Appelhans, David},
      title        = {{E}fficient {D}istributed {GPU} {P}rogramming for
                      {E}xascale},
      reportid     = {FZJ-2025-05596},
      year         = {2025},
      note         = {Tutorial},
      abstract     = {Over the past decade, GPUs became ubiquitous in HPC
                      installations around the world, delivering the majority of
                      performance of some of the largest supercomputers, steadily
                      increasing the available compute capacity. Finally, four
                      exascale systems are deployed (Frontier, Aurora, El Capitan,
                      JUPITER), using GPUs as the core computing devices for this
                      era of HPC. To take advantage of these GPU-accelerated
                      systems with tens of thousands of devices, application
                      developers need to have the proper skills and tools to
                      understand, manage, and optimize distributed GPU
                      applications. In this tutorial, participants will learn
                      techniques to efficiently program large-scale multi-GPU
                      systems. While programming multiple GPUs with MPI is
                      explained in detail, also advanced tuning techniques and
                      complementing programming models like NCCL and NVSHMEM are
                      presented. Tools for analysis are shown and used to motivate
                      and implement performance optimizations. The tutorial
                      teaches fundamental concepts that apply to GPU-accelerated
                      systems of any vendor in general, taking the NVIDIA platform
                      as an example. It is a combination of lectures and hands-on
                      exercises, using the JUPITER system for interactive learning
                      and discovery.},
      month         = {Nov},
      date          = {2025-11-16},
      organization  = {The International Conference for High
                       Performance Computing, St. Louis (USA),
                       16 Nov 2025 - 22 Nov 2025},
      subtyp        = {After Call},
      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) / ATML-X-DEV - ATML
                      Accelerating Devices (ATML-X-DEV)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(DE-HGF)POF4-5122 /
                      G:(DE-Juel-1)ATML-X-DEV},
      typ          = {PUB:(DE-HGF)6},
      doi          = {10.5281/ZENODO.17804012},
      url          = {https://juser.fz-juelich.de/record/1049812},
}