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001014586 001__ 1014586
001014586 005__ 20251020082354.0
001014586 0247_ $$2datacite_doi$$a10.18154/RWTH-2025-06161
001014586 037__ $$aRWTH-2025-06161
001014586 041__ $$aEnglish
001014586 082__ $$a004
001014586 1001_ $$0P:(DE-82)1015311$$aSchlien, Paul$$b0$$urwth
001014586 245__ $$aA CI-based workflow for automating POP-driven performance assessments for HPC applications$$cPaul Schlien$$honline
001014586 246_3 $$aVerwendung von Continuous Integration zur Automatisierung von POP-basierten Leistungsbewertungen für HPC-Anwendungen$$yGerman
001014586 260__ $$aAachen$$bRWTH Aachen University$$c2025
001014586 300__ $$a1 Online-Ressource : Illustrationen
001014586 3367_ $$02$$2EndNote$$aThesis
001014586 3367_ $$0PUB:(DE-HGF)2$$2PUB:(DE-HGF)$$aBachelor Thesis$$bbachelor$$mbachelor
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001014586 500__ $$aVeröffentlicht auf dem Publikationsserver der RWTH Aachen University
001014586 502__ $$aBachelorarbeit, RWTH Aachen University, 2025$$bBachelorarbeit$$cRWTH Aachen University$$d2025$$gFak01$$o2025-05-07
001014586 5203_ $$lger
001014586 520__ $$aPerformance 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.$$leng
001014586 591__ $$aGermany
001014586 653_7 $$aHigh Performance Computing (HPC)
001014586 653_7 $$acontinuous integration
001014586 653_7 $$aperformance analysis
001014586 7001_ $$0P:(DE-82)IDM01074$$aMüller, Matthias S.$$b1$$eThesis advisor$$urwth
001014586 7001_ $$0P:(DE-82)956146$$aWolf, Felix$$b2$$eThesis advisor
001014586 7001_ $$0P:(DE-82)IDM05052$$aOrland, Fabian$$b3$$eConsultant$$urwth
001014586 7001_ $$0P:(DE-82)837502$$aTomski, Felix$$b4$$eConsultant$$urwth
001014586 8564_ $$uhttps://publications.rwth-aachen.de/record/1014586/files/1014586.pdf$$yOpenAccess
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001014586 9141_ $$y2025
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001014586 9201_ $$0I:(DE-82)120000_20140620$$k120000$$lFachgruppe Informatik$$x1
001014586 9201_ $$0I:(DE-82)022000_20140101$$k022000$$lIT Center$$x2
001014586 961__ $$c2025-07-23T08:06:44.583193$$x2025-07-14T23:42:54.189057$$z2025-07-23T08:06:44.583193
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