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Description
The 28th International Conference on Computing in High Energy Physics (CHEP 2026) brought together over 600 researchers from particle physics experiments and computational infrastructure projects to discuss the most pressing computing challenges facing the field over the next decade. As the Large Hadron Collider enters its high-luminosity era and next-generation experiments begin data acquisition, the computing demands have reached unprecedented scales—requiring innovations across data storage, real-time processing, archival strategies, and heterogeneous computing architectures.
This talk surveys the key findings and technical progress presented at CHEP 2026, spanning four main areas: (1) the WLCG computing roadmap for HL-LHC, addressing distributed data management and compute optimization across global collaborations; (2) prompt processing paradigms that leverage GPU acceleration and machine learning to reduce data volumes while preserving physics reach; (3) emerging archival and metadata strategies for multi-exabyte datasets, balancing long-term preservation with efficient recall; and (4) cross-domain insights from AI acceleration, cloud computing, and heterogeneous infrastructure.