Speaker
Description
A comprehensive assessment of the environmental impact of the LHCb distributed computing requires a detailed understanding of its carbon footprint sources. This involves moving beyond a simple comparison of regional carbon intensity, as the hardware executing the jobs exhibits significant variation in both energy efficiency and computational performance in HEP tasks.
In this work, we present the first estimates of the carbon footprint for individual LHCb jobs and entire computing sites. Our model integrates historical grid job data, hardware performance and power profiles, energy consumption models, and region-specific carbon intensity data. Key findings include and a comparative performance analysis of over 100 CPU models in events generation and per site rate of emission. Based on these results, we provide recommendations for computing sites, the LHCb experiment, and the wider WLCG community to optimize for sustainability.