h1

% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@MASTERSTHESIS{Schlien:1014586,
      author       = {Schlien, Paul},
      othercontributors = {Müller, Matthias S. and Wolf, Felix and Orland, Fabian and
                          Tomski, Felix},
      title        = {{A} {CI}-based workflow for automating {POP}-driven
                      performance assessments for {HPC} applications},
      school       = {RWTH Aachen University},
      type         = {Bachelorarbeit},
      address      = {Aachen},
      publisher    = {RWTH Aachen University},
      reportid     = {RWTH-2025-06161},
      pages        = {1 Online-Ressource : Illustrationen},
      year         = {2025},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University; Bachelorarbeit, RWTH Aachen University, 2025},
      abstract     = {Performance analysis of High-Performance Computing (HPC)
                      applications remains a highly manual and effort-intensive
                      task, requiring expert knowledge to apply and interpret a
                      diverse set of performance analysis tools. This slows down
                      performance-driven software development, which is
                      particularly critical in the HPC domain, as the manual
                      effort required for data collection diverts time away from
                      actual analysis and the identification of optimisation
                      opportunities. A particularly affected use case is the
                      Performance Optimisation and Productivity Centre of
                      Excellence (POP CoE) project, which provides consulting
                      services for performance analysis and optimisation for HPC
                      applications. Hence, their services heavily rely on
                      performance-oriented development workflows, where code and
                      configuration changes necessitate frequent evaluation of
                      their performance impact. To address this challenge, this
                      thesis proposes a Continuous Integration (CI)-based workflow
                      that automates key aspects of the POP-driven performance
                      assessment process. A template-based framework was developed
                      to systematise the application of performance analysis tools
                      to HPC applications in a CI context, which has been used in
                      the implementation of the performance assessment workflow,
                      realised on the GitLab CI/CD platform. The focus lies on
                      enabling automated performance data collection and laying
                      the groundwork for continuous performance evaluation. The
                      proposed approach was evaluated using a real-world HPC
                      application for which a prior manual POP assessment exists.
                      Results indicate that the template-based framework can
                      support the automation of performance assessments under
                      specific assumptions regarding the execution model of the
                      application and the behaviour of performance analysis tools
                      -- namely, non-interactivity and a predictable usage
                      pattern. In this setup, CI serves as an orchestrator, with
                      the primary analysis logic remaining within the performance
                      analysis tools. Furthermore, findings indicate that more
                      fine-grained improvements in pipeline efficiency are
                      necessary, along with enhanced mechanisms for assessing
                      performance trends over time. Overall, this work
                      demonstrates the feasibility of a CI-based, template-driven
                      performance assessment workflow and its applicability in
                      selected HPC contexts.},
      cin          = {123010 / 120000 / 022000},
      ddc          = {004},
      cid          = {$I:(DE-82)123010_20140620$ / $I:(DE-82)120000_20140620$ /
                      $I:(DE-82)022000_20140101$},
      typ          = {PUB:(DE-HGF)2},
      doi          = {10.18154/RWTH-2025-06161},
      url          = {https://publications.rwth-aachen.de/record/1014586},
}