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020 _ _ |a 978-3-032-07611-3 (print)
020 _ _ |a 978-3-032-07612-0 (electronic)
024 7 _ |2 doi
|a 10.1007/978-3-032-07612-0
024 7 _ |2 ISSN
|a 0302-9743
024 7 _ |2 ISSN
|a 1611-3349
037 _ _ |a FZJ-2025-05008
041 _ _ |a English
100 1 _ |0 P:(DE-Juel1)162225
|a Guimarães, Filipe Souza Mendes
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111 2 _ |a 40th International Conference on High Performance Computing, ISC High Performance 2025.
|c Hamburg
|d 2025-06-10 - 2025-06-13
|w Germany
245 _ _ |a Supporting HPC Users with LLview
250 _ _ |a 1
260 _ _ |a Heidelberg
|b Springer
|c 2025
295 1 0 |a High Performance Computing / ISC High Performance 2025 International Workshops, Hamburg, Germany, June 10–13, 2025, Revised Selected Papers
300 _ _ |a 40 - 51
336 7 _ |2 ORCID
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490 0 _ |a Lecture Notes in Computer Science
|v 16091
520 _ _ |a Diagnosing and reporting operational issues to optimise system usage and performance is challenging on large-scale HPC systems due to their sheer complexity. At the Jülich Supercomputing Centre (JSC), we address this challenge with LLview, an open-source system and job reporting framework. LLview provides near real-time metrics for analysis through a web portal with role-based access for users, administrators, and support staff. In this paper, we present a series of use cases demonstrating how LLview enables efficient diagnosis and resolution of system and application issues, enhancing both reactive and proactive support for HPC users.
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700 1 _ |0 P:(DE-Juel1)200513
|a Sankaran, Aravind
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700 1 _ |0 P:(DE-Juel1)132108
|a Frings, Wolfgang
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773 _ _ |0 PERI:(DE-600)2018930-8
|a 10.1007/978-3-032-07612-0
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856 4 _ |u https://juser.fz-juelich.de/record/1048907/files/978-3-032-07612-0.pdf
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|v Enabling Computational- & Data-Intensive Science and Engineering
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914 1 _ |y 2025
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