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@INPROCEEDINGS{Tashakor:1022046,
      author       = {Tashakor, Ghazal},
      othercontributors = {Caviedes Voullieme, Daniel},
      title        = {{T}owards {E}xascale through {M}odularity {A}nd {I}/{O}
                      {M}anagement, {P}erformance study under {M}odular computing
                      with {TSMP}},
      reportid     = {FZJ-2024-01183},
      year         = {2024},
      note         = {Platform
                      link:https://www.hipeac.net/2024/munich/#/program/},
      abstract     = {This abstract highlights the pivotal role of the
                      Terrestrial Systems Modelling Platform (TSMP) as a core use
                      case in two pioneering projects, DEEP-SEA and IO-SEA, within
                      the context of the Modular Supercomputing Architecture
                      (MSA). The MSA, developed throughout the DEEP projects,
                      serves as a blueprint for heterogeneous HPC systems,
                      promoting the highest efficiency and scalability by
                      integrating different compute modules tailored to specific
                      performance characteristics for diverse workloads.The
                      Terrestrial Systems Modelling Platform (TSMP) stands as a
                      versatile, fully coupled Earth system model designed for
                      regional simulations, emphasizing complex interactions
                      within the geo-ecosystem. As an open community code, TSMP
                      integrates various atmospheric models like COSMO and ICON,
                      the Community Land Model (CLM), and the hydrological model
                      ParFlow. With modular coupling, TSMP supports multiple
                      programming languages, parallelization schemes, and hardware
                      architectures.In the DEEP-SEA project, TSMP is utilized as a
                      key use case to address the challenges of exascale computing
                      within the MSA. The modular approach of the MSA aligns with
                      TSMP's capabilities, allowing for the execution of different
                      components, such as CPU and GPU-enabled COSMO, CUDA-ported
                      ParFlow, and Fortran-based CLM, on the most suitable
                      platform. The focus within DEEP-SEA is on mapping these
                      specific components to optimize memory usage and
                      scalability. This approach enables TSMP to conduct
                      simulations at unprecedented resolutions and speeds,
                      leveraging the innovative capabilities of the DEEP
                      infrastructure.Simultaneously, in the IO-SEA project, TSMP
                      serves as a foundational use case to drive advancements in
                      data-centric I/O and workflow execution within the MSA. The
                      adaptability and scalability of the MSA align with the goals
                      of IO-SEA in optimizing data-centric workflows. The project
                      extends existing I/O instrumentation tools, such as Smart
                      burst buffering (SBB) and Data Access and Storage
                      application Interface (DASI), to accommodate the intricacies
                      of TSMP's coupled workflow.In conclusion, the integration of
                      TSMP within the DEEP projects exemplifies a collaborative
                      effort to address the challenges of exascale computing
                      within the innovative Modular Supercomputing Architecture.
                      TSMP's coupled approach aligns seamlessly with the
                      adaptability and scalability of the MSA, allowing for
                      enhanced efficiency and performance in the rapidly evolving
                      landscape of heterogeneous HPC systems. This collaborative
                      effort serves as a model for leveraging versatile Earth
                      system models to improve energy and resource use efficiency
                      in cutting-edge supercomputing infrastructures.},
      month         = {Jan},
      date          = {2024-01-16},
      organization  = {HiPEAC, Munich (Germany), 16 Jan 2024
                       - 19 Jan 2024},
      subtyp        = {Invited},
      cin          = {JSC / IBG-3 / IAS},
      cid          = {I:(DE-Juel1)JSC-20090406 / I:(DE-Juel1)IBG-3-20101118 /
                      I:(DE-Juel1)VDB1106},
      pnm          = {2A5 - Exascale Earth System Modeling (CARF - CCA)
                      (POF4-2A5) / 2173 - Agro-biogeosystems: controls, feedbacks
                      and impact (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2A5 / G:(DE-HGF)POF4-2173},
      experiment   = {EXP:(DE-MLZ)SCG-20150203},
      typ          = {PUB:(DE-HGF)24},
      doi          = {10.34734/FZJ-2024-01183},
      url          = {https://juser.fz-juelich.de/record/1022046},
}