TY  - CONF
AU  - Maloney, Samuel
TI  - SEANERGYS at JSC: Software for Efficient and Energy-Aware Supercomputers
M1  - FZJ-2025-03027
PY  - 2025
AB  - SEANERGYS 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.
T2  - IAS Retreat 2025
CY  - 27 May 2025 - 27 May 2025, Jülich (Germany)
Y2  - 27 May 2025 - 27 May 2025
M2  - Jülich, Germany
LB  - PUB:(DE-HGF)24
DO  - DOI:10.34734/FZJ-2025-03027
UR  - https://juser.fz-juelich.de/record/1044104
ER  -