Home > Publications database > Analyzing HPC Monitoring Data With a View Towards Efficient Resource Utilization > print |
001 | 1031786 | ||
005 | 20250317091735.0 | ||
024 | 7 | _ | |a 10.1109/SBAC-PAD63648.2024.00023 |2 doi |
024 | 7 | _ | |a 10.34734/FZJ-2024-05813 |2 datacite_doi |
037 | _ | _ | |a FZJ-2024-05813 |
041 | _ | _ | |a English |
100 | 1 | _ | |a Maloney, Samuel |0 P:(DE-Juel1)200390 |b 0 |e Corresponding author |u fzj |
111 | 2 | _ | |a 2024 IEEE 36th International Symposium on Computer Architecture and High Performance Computing |g SBAC-PAD |c Hilo, HI |d 2024-11-13 - 2024-11-15 |w USA |
245 | _ | _ | |a Analyzing HPC Monitoring Data With a View Towards Efficient Resource Utilization |
260 | _ | _ | |c 2024 |b IEEE |
295 | 1 | 0 | |a 2024 IEEE 36th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) |
300 | _ | _ | |a 170-181 |
336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
336 | 7 | _ | |a Journal Article |0 PUB:(DE-HGF)16 |2 PUB:(DE-HGF) |m journal |
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 |0 PUB:(DE-HGF)8 |s 1736144602_25368 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a Contribution to a book |0 PUB:(DE-HGF)7 |2 PUB:(DE-HGF) |m contb |
500 | _ | _ | |a The data used for this study are available at: https://doi.org/10.26165/JUELICH-DATA/BDFBPQ 979-8-3503-5616-8/24/$31.00 © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
520 | _ | _ | |a Compute nodes in modern HPC systems are growing in size and their hardware has become ever more diverse. Still, many HPC centers allocate the resources of full nodes exclusively to avoid contention, despite the associated risk of underutilization. This paper describes a thorough resource utilization study of CPU and GPU compute and memory capacity, and interconnect bandwidth on JUWELS, a mature leadership-class modular supercomputer, with the aim of identifying opportunities for improving utilization through advanced scheduling and node sharing. Separate analysis of CPU-only and GPU-accelerated nodes finds that CPU compute usage is already close to optimal for the CPU-only nodes, whereas there is plenty of scope for co-scheduling CPU-based jobs on GPU-accelerated nodes. Memory capacity and node-level interconnect bandwidth are sufficient to provision co-scheduled jobs. We analyze multiple one-month datasets to validate robustness of conclusions over time and compare with previous studies on other systems to establish generalizability of results. |
536 | _ | _ | |a 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) |0 G:(DE-HGF)POF4-5112 |c POF4-511 |f POF IV |x 0 |
536 | _ | _ | |a 5122 - Future Computing & Big Data Systems (POF4-512) |0 G:(DE-HGF)POF4-5122 |c POF4-512 |f POF IV |x 1 |
536 | _ | _ | |a DEEP-SEA - DEEP – SOFTWARE FOR EXASCALE ARCHITECTURES (955606) |0 G:(EU-Grant)955606 |c 955606 |f H2020-JTI-EuroHPC-2019-1 |x 2 |
536 | _ | _ | |0 G:(DE-Juel-1)ATMLAO |a ATMLAO - ATML Application Optimization and User Service Tools (ATMLAO) |c ATMLAO |x 3 |
588 | _ | _ | |a Dataset connected to CrossRef Conference |
700 | 1 | _ | |a Suarez, Estela |0 P:(DE-Juel1)142361 |b 1 |u fzj |
700 | 1 | _ | |a Eicker, Norbert |0 P:(DE-Juel1)132090 |b 2 |u fzj |
700 | 1 | _ | |a Guimaraes, Filipe |0 P:(DE-Juel1)162225 |b 3 |u fzj |
700 | 1 | _ | |a Frings, Wolfgang |0 P:(DE-Juel1)132108 |b 4 |u fzj |
773 | _ | _ | |a 10.1109/SBAC-PAD63648.2024.00023 |p 170-181 |t 2643-3001 |y 2024 |
856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/1031786/files/Maloney2024-postprint.pdf |
856 | 4 | _ | |y Restricted |u https://juser.fz-juelich.de/record/1031786/files/SBAC-PAD-24-presentation.pdf |
909 | C | O | |o oai:juser.fz-juelich.de:1031786 |p openaire |p open_access |p driver |p VDB |p ec_fundedresources |p dnbdelivery |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)200390 |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)142361 |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)132090 |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 3 |6 P:(DE-Juel1)162225 |
910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 4 |6 P:(DE-Juel1)132108 |
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 |x 0 |
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)POF4-512 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Supercomputing & Big Data Infrastructures |9 G:(DE-HGF)POF4-5122 |x 1 |
914 | 1 | _ | |y 2024 |
915 | _ | _ | |a OpenAccess |0 StatID:(DE-HGF)0510 |2 StatID |
920 | _ | _ | |l yes |
920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
980 | _ | _ | |a contrib |
980 | _ | _ | |a VDB |
980 | _ | _ | |a UNRESTRICTED |
980 | _ | _ | |a journal |
980 | _ | _ | |a contb |
980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
980 | 1 | _ | |a FullTexts |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|