Adaptive Infrastructure and Efficiency Strategies at a GridKa WLCG Tier-1 Center

          @misc{ scivideos_oai:cds.cern.ch:3025606,
            doi = {},
            url = {https://videos.cern.ch/record/3025606},
            author = {},
            keywords = {},
            language = {en},
            title = {Adaptive Infrastructure and Efficiency Strategies at a GridKa WLCG Tier-1 Center},
            publisher = {},
            year = {2026},
            month = {may},
            note = {oai:cds.cern.ch:3025606 see, \url{https://scivideos.org/cern-cds/3025606}}
          }
          

Abstract

As resource demands for High Energy Physics (HEP) and other data-intensive scientific realms reach unprecedented levels, the environmental impact of large-scale computing has has increasingly moved into the focus. Facilities now face the dual challenge of increasing resource pledges while continuously reducing their carbon footprint and total energy consumption. At the GridKa WLCG Tier-1 Center, we have implemented several measures to address this. A detailed energy monitoring system enables energy-efficient operations. Combined with energy-aware procurement processes, which prioritize performance-per-watt over the entire hardware lifecycle, we have successfully reduced total power consumption even as our resource pledges increase. A further key ingredient of our strategy is extensive R&D and the early adoption of future technologies. Using our COBalD/TARDIS meta-scheduler for transparent, on-demand site extensions, we have enabled the migration of German University WLCG Tier-2 resources from legacy "basement" environments (PUE~1.x) to highly efficient NHR HPC centers (PUE ~ 1.0x). COBalD/TARDIS facilitates also a "follow-the-renewables" strategy, allowing Tier-1 workloads to overflow into carbon-neutral resources (e.g., LANCIUM Compute) without disrupting daily operations. Additionally, the early adoption of high-efficiency hardware, such as ARM CPUs providing a 20% efficiency increase, has delivered a significant positive impact. Future plans, alongside our partners in the recently founded SUSFECIT project, aim to facilitate the transition from a static compute model to a dynamic, energy-aware infrastructure. Through techniques like Power Efficiency via Clock Frequency Tuning, we are moving toward a "Breathing Compute Center" that scales in sync with renewable energy availability and grid demands, further supported by our recently installed rooftop solar plant at the GridKa data center. This talk provides a comprehensive look at how GridKa is successfully bridging the gap between massive-scale data processing and environmental sustainability.

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