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@ARTICLE{Tarraf:1035001,
      author       = {Tarraf, Ahmad and Schreiber, Martin and Cascajo, Alberto
                      and Besnard, Jean-Baptiste and Vef, Marc-André and Huber,
                      Dominik and Happ, Sonja and Brinkmann, André and Singh,
                      David E. and Hoppe, Hans-Christian and Miranda, Alberto and
                      Peña, Antonio J. and Machado, Rui and Garcia-Gasulla, Marta
                      and Schulz, Martin and Carpenter, Paul and Pickartz, Simon
                      and Rotaru, Tiberiu and Iserte, Sergio and Lopez, Victor and
                      Ejarque, Jorge and Sirwani, Heena and Carretero, Jesus and
                      Wolf, Felix},
      title        = {{M}alleability in {M}odern {HPC} {S}ystems: {C}urrent
                      {E}xperiences, {C}hallenges, and {F}uture {O}pportunities},
      journal      = {IEEE transactions on parallel and distributed systems},
      volume       = {35},
      number       = {9},
      issn         = {2161-9883},
      address      = {New York, NY},
      publisher    = {IEEE},
      reportid     = {FZJ-2025-00107},
      pages        = {1551 - 1564},
      year         = {2024},
      abstract     = {With the increase of complex scientific simulations driven
                      by workflows and heterogeneous workload profiles, managing
                      system resources effectively is essential for improving
                      performance and system throughput, especially due to trends
                      like heterogeneous HPC and deeply integrated systems with
                      on-chip accelerators. For optimal resource utilization,
                      dynamic resource allocation can improve productivity across
                      all system and application levels, by adapting the
                      applications’ configurations to the system's resources. In
                      this context, malleable jobs, which can change resources at
                      runtime, can increase the system throughput and resource
                      utilization while bringing various advantages for HPC users
                      (e.g., shorter waiting time). Malleability has received much
                      attention recently, even though it has been an active
                      research area for more than two decades. This article
                      presents the state-of-the-art of malleable implementations
                      in HPC systems, targeting mainly malleability in compute and
                      I/O resources. Based on our experiences, we state our
                      current concerns and list future opportunities for
                      research.},
      cin          = {JSC},
      ddc          = {004},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5122 - Future Computing $\&$ Big Data Systems (POF4-512) /
                      DEEP-SEA - DEEP – SOFTWARE FOR EXASCALE ARCHITECTURES
                      (955606) / ADMIRE - Adaptive multi-tier intelligent data
                      manager for Exascale (956748) / TIME-X - TIME
                      parallelisation: for eXascale computing and beyond (955701)
                      / Verbundprojekt: TIME-X - Parallelisierung zeitabhängiger
                      Simulationen für das zukünftige Supercomputing (16HPC047)
                      / REGALE - An open architecture to equip next generation HPC
                      applications with exascale capabilities (956560)},
      pid          = {G:(DE-HGF)POF4-5122 / G:(EU-Grant)955606 /
                      G:(EU-Grant)956748 / G:(EU-Grant)955701 / G:(BMBF)16HPC047 /
                      G:(EU-Grant)956560},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001272190100002},
      doi          = {10.1109/TPDS.2024.3406764},
      url          = {https://juser.fz-juelich.de/record/1035001},
}