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The CMS experiment at CERN’s LHC produces an immense volume of collision data in real time, relying on a two-level trigger system to reduce event rates before storage. To meet rising computational demands, CMS has integrated GPU acceleration into its High-Level Trigger (HLT) pipeline, with around 40% of the runtime already executed on GPUs. However, current GPU use is limited to local resources, which will become problematic as more algorithms are ported to heterogeneous execution in the upcoming upgrade phases. To address this, we propose a method for extending compute capacity by offloading parts of the filtering pipeline to additional GPU-equipped machines, without requiring major changes to the CMS software framework or hardware layout.

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