Predicting the efficiency of job scheduler actions

  • Ana Eloina Nascimento Kraus UDESC
  • Guilerme Diel UDESC
  • Guilherme Piêgas Koslovski UDESC


The order in which tasks are executed in High Performance Computing (HPC) infrastructures is fundamental to the efficiency of the virtual environment. This article covera a amachine learning- and polynomial regression-aided effort of predicting and thus, drawing out a better understanding of, the individual performances of various job scheduling algorithms.


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KRAUS, Ana Eloina Nascimento; DIEL, Guilerme; KOSLOVSKI, Guilherme Piêgas. Predicting the efficiency of job scheduler actions. In: ESCOLA REGIONAL DE ALTO DESEMPENHO DA REGIÃO SUL (ERAD-RS), 24. , 2024, Florianópolis/SC. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2024 . p. 33-36. ISSN 2595-4164. DOI: