SOURCE-LINKED INTELLIGENCE

Software for Efficient and Energy-Aware Supercomputers

CORDIS · observation · Publication date unknown

ven energy budget, or produce a fixed set of R&D results with less energy, while striving to keep response times constant. 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 DAIS leverages AI models trained with a vast set of operational data of 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. The SEANERGYS solution will be ready for

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recordType

award

status

SIGNED

region

EU

value

16473566.3

unit

EUR