ML for the Trigger at LHCb
Carlos S´anchez Mayordomo (on behalf of the IFIC-LHCb group)
ARTEMISA Mini-Workshop on ML 29th May, 2019
The Group
People involved in the project:
• Arantza Oyanguren
• Luis Miguel Garc´ıa
• Carlos S´anchez
• Louis Henry
• Jos´e Mazorra
• Brij Jashal
LHCb detector: current
Current≡Run 1-2 (2011-2018)
• L0hardwaretrigger: 40→1 MHz
• HLTsoftware: 1 MHz→12.5 kHz
LHCb detector: upgrade
Upgrade≡Run 3 (2021 onwards)
https://cds.cern.ch/record/1701361
LHCb detector: upgrade
Upgrade≡Run 3 (2021 onwards)
Almost a brand-new detector!
LHCb detector: upgrade
Upgrade≡Run 3 (2021 onwards)
• Full-software trigger!
• 6x number of primary interactions
• Reconstruction at 25ns + alignment + calibration
• Stringent rate and timing constraints for the first trigger stage:
• Reduce event rate: 30→1 MHz
• Timing: ∼10 ms / event
• Storage: 40 Tb/s→10 GB/s
• Current algorithms are too slow!
https://cds.cern.ch/record/1701361
Track reconstruction
Different kind of tracks
• Current setup triggers onLong tracks only
• Try to extend to Downstreamfor the upgrade, to trigger long-lived particles
• But... new algorithms are needed! (and more computing power)
Computing challenges
• Events are required to run in parallel
• GPUs are a serious candidate for HEP triggering/tracking
Past (single process)
Future (parallel processing)
Allen project
• Run the HLT1 reconstruction on GPUs
• Scalable and modular framework
• SIMD implementation / SoA data types
• Parallelize between events (blocks) and within events (threads)
https://gitlab.cern.ch/lhcb-parallelization/Allen
Allen project
• Supports CUDA and x86, working on AMD porting
• Opportunity to try ML solutions!
https://gitlab.cern.ch/lhcb-parallelization/Allen
Tracking: NN pattern recognition
• Independent NN for each detector layer
Vertexing: hybrid deep learning
Trigger: Inclusive-B trigger
• Trigger events with B-meson signatures
• NN solution provides better rejection than existing algorithms
• CUDA much more performant for larger batch sizes
Other applications: Flavour tagging
• Tag the initial particle: B0 orB0?
• Using information of the full event
Successfully tried for jet flavour classification[arxiv:1607.08633]
TrackML challenge
• https://sites.google.com/site/trackmlparticle/
• Challenge: reconstruct tracks from 3D hits
• Accuracy phase (May-August 2018) 25k$price
• Throughput phase (Sept-March 2019) 15k$price
