001     1003814
005     20250317202727.0
024 7 _ |a 10.1109/ProTools56701.2022.00007
|2 doi
024 7 _ |a 2128/33953
|2 Handle
024 7 _ |a WOS:000964532800001
|2 WOS
037 _ _ |a FZJ-2023-01264
100 1 _ |a Ritter, Marcus
|0 P:(DE-HGF)0
|b 0
111 2 _ |a 2022 IEEE/ACM Workshop on Programming and Performance Visualization Tools (ProTools)
|c Dallas
|d 2022-11-13 - 2022-11-18
|w TX
245 _ _ |a Conquering Noise With Hardware Counters on HPC Systems
260 _ _ |c 2022
|b IEEE
295 1 0 |a 2022 IEEE/ACM Workshop on Programming and Performance Visualization Tools (ProTools) : [Proceedings] - IEEE, 2022. - ISBN 978-1-6654-7564-8 - doi:10.1109/ProTools56701.2022.00007
300 _ _ |a 1-10
336 7 _ |a CONFERENCE_PAPER
|2 ORCID
336 7 _ |a Conference Paper
|0 33
|2 EndNote
336 7 _ |a INPROCEEDINGS
|2 BibTeX
336 7 _ |a conferenceObject
|2 DRIVER
336 7 _ |a Output Types/Conference Paper
|2 DataCite
336 7 _ |a Contribution to a conference proceedings
|b contrib
|m contrib
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|2 PUB:(DE-HGF)
336 7 _ |a Contribution to a book
|0 PUB:(DE-HGF)7
|2 PUB:(DE-HGF)
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520 _ _ |a With increasing system performance and complexity, it is becoming increasingly crucial to examine the scaling behavior of an application and thus determine performance bottlenecks at early stages. Unfortunately, modeling this trend is a challenging task in the presence of noise, as the measurements can become irreproducible and misleading, thus resulting in strong deviations from the actual behavior. While noise impacts the application runtime, it has little to no effect on some hardware counters like floating-point operations. However, selecting the appropriate counters for performance modeling demands some investigation. In this paper, we perform a noise analysis on various hardware counters. Using our noise generator, we add additional noise on top of the system noise to inspect the counters' variability. We perform the analysis on five systems with three applications in the presence of various noise patterns and categorize the counters across the systems according to their noise resilience.
536 _ _ |a 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)
|0 G:(DE-HGF)POF4-5112
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|f POF IV
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536 _ _ |a DFG project G:(GEPRIS)449683531 - ExtraNoise – Leistungsanalyse von HPC-Anwendungen in verrauschten Umgebungen (449683531)
|0 G:(GEPRIS)449683531
|c 449683531
|x 1
536 _ _ |a ATMLPP - ATML Parallel Performance (ATMLPP)
|0 G:(DE-Juel-1)ATMLPP
|c ATMLPP
|x 2
588 _ _ |a Dataset connected to CrossRef Conference
700 1 _ |a Tarraf, Ahmad
|0 P:(DE-HGF)0
|b 1
|e Corresponding author
700 1 _ |a Geiß, Alexander
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Daoud, Nour
|0 P:(DE-Juel1)188664
|b 3
700 1 _ |a Mohr, Bernd
|0 P:(DE-Juel1)132199
|b 4
|e Corresponding author
700 1 _ |a Wolf, Felix
|0 P:(DE-HGF)0
|b 5
773 _ _ |a 10.1109/ProTools56701.2022.00007
856 4 _ |u https://juser.fz-juelich.de/record/1003814/files/HW_accepted.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:1003814
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910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
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|6 P:(DE-Juel1)188664
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
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913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|1 G:(DE-HGF)POF4-510
|0 G:(DE-HGF)POF4-511
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Enabling Computational- & Data-Intensive Science and Engineering
|9 G:(DE-HGF)POF4-5112
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914 1 _ |y 2022
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
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920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)JSC-20090406
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|l Jülich Supercomputing Center
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980 _ _ |a contrib
980 _ _ |a VDB
980 _ _ |a contb
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a UNRESTRICTED
980 1 _ |a FullTexts


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