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Estimating the Impact of External Interference on Application Performance

Shah, Aamer ; Müller, Matthias S. ; Wolf, Felix (2018)
Estimating the Impact of External Interference on Application Performance.
24th International European Conference on Parallel and Distributed Computing. Turin, Italy (27.-31.08.2018)
doi: 10.1007/978-3-319-96983-1_4
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

The wall-clock execution time of applications on HPC clusters is commonly subject to run-to-run variation, often caused by external interference from concurrently running jobs. Because of the irregularity of this interference from the perspective of the affected job, performance analysts do not consider it an intrinsic part of application execution, which is why they wish to factor it out when measuring execution time. However, if chances are high enough that at least one interference event strikes while the job is running, merely repeating runs several times and picking the fastest run does not guarantee a measurement free of external influence. In this paper, we present a novel approach to estimate the impact of sporadic and high-impact interference on bulk-synchronous MPI applications. An evaluation with several realistic benchmarks shows that the impact of interference can be estimated already based on a single run.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2018
Autor(en): Shah, Aamer ; Müller, Matthias S. ; Wolf, Felix
Art des Eintrags: Bibliographie
Titel: Estimating the Impact of External Interference on Application Performance
Sprache: Englisch
Publikationsjahr: 1 August 2018
Verlag: Springer
Buchtitel: Euro-Par 2018: Parallel Processing
Reihe: Lecture Notes in Computer Science
Band einer Reihe: 11014
Veranstaltungstitel: 24th International European Conference on Parallel and Distributed Computing
Veranstaltungsort: Turin, Italy
Veranstaltungsdatum: 27.-31.08.2018
DOI: 10.1007/978-3-319-96983-1_4
Kurzbeschreibung (Abstract):

The wall-clock execution time of applications on HPC clusters is commonly subject to run-to-run variation, often caused by external interference from concurrently running jobs. Because of the irregularity of this interference from the perspective of the affected job, performance analysts do not consider it an intrinsic part of application execution, which is why they wish to factor it out when measuring execution time. However, if chances are high enough that at least one interference event strikes while the job is running, merely repeating runs several times and picking the fastest run does not guarantee a measurement free of external influence. In this paper, we present a novel approach to estimate the impact of sporadic and high-impact interference on bulk-synchronous MPI applications. An evaluation with several realistic benchmarks shows that the impact of interference can be estimated already based on a single run.

Freie Schlagworte: LOEWE|SF4.0, DFG|320898076, BMBF|01IH16008D, DoE|DE-SC0015524, LOEWE, DFG, DoE, BMBF
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Parallele Programmierung
Hinterlegungsdatum: 04 Apr 2024 11:36
Letzte Änderung: 30 Apr 2024 12:34
PPN: 517678454
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