Looking Forward: A High-Throughput Track Following Algorithm for Parallel Architectures
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arXiv
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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866910580044988416 |
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| author | Bailly-Reyre, Aurelien Bian, Lingzhu Billoir, Pierre Perez, Daniel Hugo Campora Gligorov, Vladimir Vava Pisani, Flavio Quagliani, Renato Scarabotto, Alessandro Bruch, Dorothea vom |
| author_facet | Bailly-Reyre, Aurelien Bian, Lingzhu Billoir, Pierre Perez, Daniel Hugo Campora Gligorov, Vladimir Vava Pisani, Flavio Quagliani, Renato Scarabotto, Alessandro Bruch, Dorothea vom |
| contents | Real-time data processing is a central aspect of particle physics experiments with high requirements on computing resources. The LHCb experiment must cope with the 30 million proton-proton bunches collision per second rate of the Large Hadron Collider (LHC), producing $10^9$ particles/s. The large input data rate of 32 Tb/s needs to be processed in real time by the LHCb trigger system, which includes both reconstruction and selection algorithms to reduce the number of saved events. The trigger system is implemented in two stages and deployed in a custom data centre.
We present Looking Forward, a high-throughput track following algorithm designed for the first stage of the LHCb trigger and optimised for GPUs. The algorithm focuses on the reconstruction of particles traversing the whole LHCb detector and is developed to obtain the best physics performance while respecting the throughput limitations of the trigger. The physics and computing performances are discussed and validated with simulated samples. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_14670 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Looking Forward: A High-Throughput Track Following Algorithm for Parallel Architectures Bailly-Reyre, Aurelien Bian, Lingzhu Billoir, Pierre Perez, Daniel Hugo Campora Gligorov, Vladimir Vava Pisani, Flavio Quagliani, Renato Scarabotto, Alessandro Bruch, Dorothea vom High Energy Physics - Experiment Instrumentation and Detectors Real-time data processing is a central aspect of particle physics experiments with high requirements on computing resources. The LHCb experiment must cope with the 30 million proton-proton bunches collision per second rate of the Large Hadron Collider (LHC), producing $10^9$ particles/s. The large input data rate of 32 Tb/s needs to be processed in real time by the LHCb trigger system, which includes both reconstruction and selection algorithms to reduce the number of saved events. The trigger system is implemented in two stages and deployed in a custom data centre. We present Looking Forward, a high-throughput track following algorithm designed for the first stage of the LHCb trigger and optimised for GPUs. The algorithm focuses on the reconstruction of particles traversing the whole LHCb detector and is developed to obtain the best physics performance while respecting the throughput limitations of the trigger. The physics and computing performances are discussed and validated with simulated samples. |
| title | Looking Forward: A High-Throughput Track Following Algorithm for Parallel Architectures |
| topic | High Energy Physics - Experiment Instrumentation and Detectors |
| url | https://arxiv.org/abs/2402.14670 |