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@INPROCEEDINGS{Reuter:1027498,
      author       = {Reuter, Jan Andre and Williams, William R. and Mohr, Bernd},
      title        = {{P}erformance {A}nalysis of {O}pen{MP} {T}arget
                      {O}ffloading in {S}core-{P}},
      reportid     = {FZJ-2024-03907},
      year         = {2024},
      abstract     = {With increasing demand in compute performance of HPC
                      systems, accelerators are getting the main focus for
                      application development. Many of the Top500 HPC systems now
                      include accelerators, with the top 3 systems alone having
                      accelerators of three different vendors. This diversity
                      requires application developers to choose portable
                      frameworks to support all at the same time, as developing
                      applications via each native API is time consuming. One of
                      the available frameworks is OpenMP with its offloading
                      capability and availability for C, C++ and Fortran. With
                      OpenMP offloading gaining more traction recently,
                      performance analysis becomes important as well. With this
                      poster, we present our first results in adding support for
                      OpenMP offloading to our instrumentation and measurement
                      infrastructure Score-P using the OpenMP Tools Interface. We
                      demonstrate how we can use both host side callbacks and the
                      device tracing interface to build a measurement adapter
                      capable of analyzing OpenMP applications effectively. We
                      show the current support landscape between different
                      compilers and present first results for profiles and event
                      traces based on the SPEC HPC 2021 $618.tealeaf_s$ benchmark
                      running on the LUMI HPC cluster at CSC in Finland.},
      month         = {May},
      date          = {2024-05-13},
      organization  = {ISC High Performance 2024, Hamburg
                       (Germany), 13 May 2024 - 15 May 2024},
      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) / BMBF 16ME0630 - ENSIMA -
                      Energieoptimiertes High-Performance Computing für
                      Finite-Elemente-Simulationen in der Produktentwicklung
                      (16ME0630) / ATMLPP - ATML Parallel Performance (ATMLPP)},
      pid          = {G:(DE-HGF)POF4-5112 / G:(BMBF)16ME0630 /
                      G:(DE-Juel-1)ATMLPP},
      typ          = {PUB:(DE-HGF)24},
      doi          = {10.34734/FZJ-2024-03907},
      url          = {https://juser.fz-juelich.de/record/1027498},
}