Impact of a dynamic Allocation Policy for Resource and Job Management Systems in deadline-oriented Scenarios

  • Barry Linnert Technische Universität Berlin
  • Cesar Augusto F. De Rose PUCRS
  • Hans-Ulrich Heiss Technische Universität Berlin


As High Performance Computing (HPC) becomes a tool used in many different workflows, Quality of Service (QoS) becomes increasingly important. In many cases, this includes the reliable execution of an HPC job and the generation of the results by a certain deadline. The Resource and Job Management System (RJMS or simply RMS) is responsible for receiving the job requests and executing the jobs with a deadline-oriented policy to support the workflows. In this paper, we evaluate how well static resource management policies cope with deadline constrained HPC jobs, and explore two variations of a dynamic policy in this context. Our preliminary results clearly show that a dynamic policy is needed to meet the requirements of a modern deadline-oriented RMS scenario.


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LINNERT, Barry; DE ROSE, Cesar Augusto F.; HEISS, Hans-Ulrich. Impact of a dynamic Allocation Policy for Resource and Job Management Systems in deadline-oriented Scenarios. In: SIMPÓSIO EM SISTEMAS COMPUTACIONAIS DE ALTO DESEMPENHO (SSCAD), 24. , 2023, Porto Alegre/RS. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 337-348. DOI: