001044104 001__ 1044104
001044104 005__ 20250801202300.0
001044104 0247_ $$2datacite_doi$$a10.34734/FZJ-2025-03027
001044104 037__ $$aFZJ-2025-03027
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001044104 1001_ $$0P:(DE-Juel1)200390$$aMaloney, Samuel$$b0$$eCorresponding author$$ufzj
001044104 1112_ $$aIAS Retreat 2025$$cJülich$$d2025-05-27 - 2025-05-27$$wGermany
001044104 245__ $$aSEANERGYS at JSC: Software for Efficient and Energy-Aware Supercomputers
001044104 260__ $$c2025
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001044104 520__ $$aSEANERGYS creates an integrated European software solution that optimises resource utilisation and reduces the energy used for real- world workload mixes. It therefore improves the throughput of HPC systems, generating more R&D results for a given energy budget. The solution consists of a comprehensive monitoring infrastructure (CMI), an Artificial Intelligence data analytics system (AIDAS), and a dynamic scheduling and resource management system (DSRM).The CMI gathers data from hardware and software sensors, and correlates it with scheduler information to identify jobs that do not fully utilize allocated resources. Users receive automatic feedback on energy and resource use for each run, plus information on how to optimize these. The AIDAS leverages AI models trained with a vast set of operational data from the participating HPC sites. It fingerprints resource usage patterns, predicts future job behaviour, and identifies complementary job profiles for potential co-scheduling. Finally, the DSRM utilizes these insights to develop scheduling policies that maximize resource utilization and energy efficiency, and supports jobs/applications with dynamic and adaptable resource profiles.
001044104 536__ $$0G:(DE-HGF)POF4-5122$$a5122 - Future Computing & Big Data Systems (POF4-512)$$cPOF4-512$$fPOF IV$$x0
001044104 536__ $$0G:(DE-HGF)POF4-5112$$a5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x1
001044104 536__ $$0G:(EU-Grant)101177590$$aSEANERGYS - Software for Efficient and Energy-Aware Supercomputers (101177590)$$c101177590$$x2
001044104 8564_ $$uhttps://juser.fz-juelich.de/record/1044104/files/SEANERGYS_Poster_IAS_Retreat_2025.pdf$$yOpenAccess
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001044104 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5112$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x1
001044104 9141_ $$y2025
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