Poster (After Call)

FZJ-2025-03027

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png SEANERGYS at JSC: Software for Efficient and Energy-Aware Supercomputers

Maloney, S. (Corresponding author)FZJ*

2025

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Please use a persistent id in citations: doi:10.34734/FZJ-2025-03027

Abstract: 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.

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 5122 - Future Computing & Big Data Systems (POF4-512) (POF4-512)
2. 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511) (POF4-511)
3. SEANERGYS - Software for Efficient and Energy-Aware Supercomputers (101177590) (101177590)

Appears in the scientific report 2025

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