Staged equivalence-preserving optimizations cut JUNO's OMILREC reconstruction time from 1524.8 to 189.2 ms/event (8.06x) on an Intel Xeon, with numerical drift below 1.3e-14.
Allen: A high level trigger on GPUs for LHCb
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abstract
We describe a fully GPU-based implementation of the first level trigger for the upgrade of the LHCb detector, due to start data taking in 2021. We demonstrate that our implementation, named Allen, can process the 40 Tbit/s data rate of the upgraded LHCb detector and perform a wide variety of pattern recognition tasks. These include finding the trajectories of charged particles, finding proton-proton collision points, identifying particles as hadrons or muons, and finding the displaced decay vertices of long-lived particles. We further demonstrate that Allen can be implemented in around 500 scientific or consumer GPU cards, that it is not I/O bound, and can be operated at the full LHC collision rate of 30 MHz. Allen is the first complete high-throughput GPU trigger proposed for a HEP experiment.
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physics.ins-det 1years
2026 1verdicts
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An eightfold equivalence-preserving speedup of the JUNO OMILREC vertex and energy reconstruction
Staged equivalence-preserving optimizations cut JUNO's OMILREC reconstruction time from 1524.8 to 189.2 ms/event (8.06x) on an Intel Xeon, with numerical drift below 1.3e-14.