Defesa de Dissertação de Mestrado: Modeling, simulation and analysis of job scheduling policy changes on supercomputers

Orientadores:
Antônio Tadeu Azevedo Gomes - Laboratório Nacional de Computação Científica - LNCC

Banca Examinadora:
Antônio Tadeu Azevedo Gomes - Laboratório Nacional de Computação Científica - LNCC (presidente)
Carla Osthoff Ferreira de Barros - Laboratório Nacional de Computação Científica - LNCC
Raphael Yokoingawa de Camargo - Universidade Federal de São Paulo - UNIFESP

Suplentes:
Roberto Pinto Souto - Laboratório Nacional de Computação Científica - LNCC
Alex Borges Vieira - Universidade Federal de Juiz de Fora - UFJF

Resumo:

Supercomputers play a pivotal role in advancing research and development across diverse scientific and engineering domains. A chief characteristic of typical supercomputers found in national laboratories is the highheterogeneity of jobs. This heterogeneity has made job schedulers increasingly complex to set up, especially whentaking into account the traditional algorithms currently employed by commercial tools. Because of that, it is notuncommon that scheduling policies be revisited on a regular basis. In this work, we propose a methodology for exploring the configuration space of job scheduling in supercomputers. This methodology combines twocomplementary approaches: (i) analyzing the effects of scheduling policy changes on user and system behavior,and (ii) applying job shaping strategies in workload-based, discrete-event simulations to accommodate varyingscheduling policies. Using the Santos Dumont supercomputer as a case study, we first reveal how the effects of achange in scheduling policy - aimed at reducing waiting times - have differential impacts on distinct job types anduser groups. Alongside this, we show that j ob shaping allows effectively capturing changes in systembehavior, regardless of parts of the workload traces used as input to the simulation are incompatible with the simulatedpolicies. By integrating empirical analysis and simulation, this work provides a comprehensive framework forenhancing supercomputer performance in volatile scheduling regimes.