A FPGA-based architecture for real-time cluster finding in the LHCb silicon pixel detector (2302.03972v3)
Abstract: This article describes a custom VHDL firmware implementation of a two-dimensional cluster-finder architecture for reconstructing hit positions in the new vertex pixel detector (VELO) that is part of the LHCb Upgrade. This firmware has been deployed to the existing FPGA cards that perform the readout of the VELO, as a further enhancement of the DAQ system, and will run in real time during physics data taking, reconstructing VELO hits coordinates on-the-fly at the LHC collision rate. This pre-processing allows the first level of the software trigger to accept a 11% higher rate of events, as the ready-made hits coordinates accelerate the track reconstruction and consumes significantly less electrical power. It additionally allows the raw pixel data to be dropped at the readout level, thus saving approximately 14% of the DAQ bandwidth. Detailed simulation studies have shown that the use of this real-time cluster finding does not introduce any appreciable degradation in the tracking performance in comparison to a full-fledged software implementation. This work is part of a wider effort aimed at boosting the real-time processing capability of HEP experiments by delegating intensive tasks to dedicated computing accelerators deployed at the earliest stages of the data acquisition chain.
- LHCb Collaboration, “LHCb Trigger and Online Upgrade Technical Design Report,” CERN, Geneva, Tech. Rep. CERN-LHCC-2014-016, 2014. [Online]. Available: https://cds.cern.ch/record/1701361
- LHCb Collaboration, “Expression of Interest for a Phase-II LHCb Upgrade: Opportunities in flavour physics, and beyond, in the HL-LHC era,” CERN, Geneva, Tech. Rep., Feb 2017. [Online]. Available: https://cds.cern.ch/record/2244311
- LHCb Collaboration, “LHCb Upgrade GPU High Level Trigger Technical Design Report,” CERN, Geneva, Tech. Rep. CERN-LHCC-2020-006, May 2020. [Online]. Available: https://cds.cern.ch/record/2717938
- R. Cenci et al., “Development of a High-Throughput Tracking Processor on FPGA Boards,” in Proc. Topical Workshop on Electronics for Particle Physics (TWEPP 2017), Santa Cruz, CA, USA, 2017. [Online]. Available: https://pos.sissa.it/313/136/
- LHCb Collaboration, “LHCb VELO Upgrade Technical Design Report,” CERN, Geneva, Tech. Rep. CERN-LHCC-2013-021. LHCB-TDR-013, 2013. [Online]. Available: https://cds.cern.ch/record/1624070
- G. Bassi et al., “FPGA implemention of a fast 2D clustering algorithm (VHDL language),” 2019. [Online]. Available: https://doi.org/10.15161/oar.it/23524
- T. Poikela et al., “VeloPix: the pixel ASIC for the LHCb upgrade,” JINST, vol. 10, no. 01, p. C01057, 2015. [Online]. Available: https://doi.org/10.1088/1748-0221/10/01/C01057
- K. Hennessy et al., “Readout Firmware of the Vertex Locator for LHCb Run 3 and Beyond,” IEEE Transactions on Nuclear Science, vol. 68, no. 10, pp. 2472–2479, 2021. [Online]. Available: https://cds.cern.ch/record/2789034
- J. P. Cachemiche et al., “The PCIe-based readout system for the LHCb experiment,” JINST, vol. 11, p. P02013. 12 p, 2016. [Online]. Available: http://cds.cern.ch/record/2262859
- S. Miglioranzi et al., “The LHCb Simulation Application, Gauss: Design, Evolution and Experience,” CERN, Geneva, Tech. Rep. LHCb-PROC-2011-006. CERN-LHCb-PROC-2011-006, Jan 2011. [Online]. Available: https://cds.cern.ch/record/1322402
- L. Giambastiani, “A 2D FPGA-based clustering algorithm for the LHCb silicon pixel detector running at 30 MHz,” Master’s thesis, Università di Pisa, Pisa, IT, 2020, presented 16 Jul 2020. [Online]. Available: https://cds.cern.ch/record/2725831
- G. Bassi, “A FPGA-based architecture for real-time cluster finding in the LHCb silicon pixel detector,” Ph.D. dissertation, Scuola Normale Superiore, Pisa, IT, 2023. [Online]. Available: https://cds.cern.ch/record/2845901
- R. Litvinov, “LHCb: Heavy-ion physics results and prospects,” International Journal of Modern Physics E, vol. 30, no. 11, p. 2141004, 2021. [Online]. Available: https://cds.cern.ch/record/2804032
- LHCb Collaboration, “LHCb Tracker Upgrade Technical Design Report,” CERN, Geneva, Tech. Rep. CERN-LHCC-2014-001, 2014. [Online]. Available: http://cds.cern.ch/record/1647400/
- LHCb Collaboration, “Tracking Definitions and Conventions for Run 3 and Beyond,” CERN, Geneva, Tech. Rep., Feb 2021. [Online]. Available: https://cds.cern.ch/record/2752971
- C.-L. Sotiropoulou et al., “A Multi-Core FPGA-Based 2D-Clustering Implementation for Real-Time Image Processing,” IEEE Transactions on Nuclear Science, vol. 6, 12 2014. [Online]. Available: https://doi.org/10.1109/TNS.2014.2364183
- D. H. Cámpora Pérez, “Optimization of high-throughput real-time processes in physics reconstruction,” Ph.D. dissertation, Universidad de Sevilla, 2019, VELO clustering is discussed in chapter 3.1. [Online]. Available: http://cds.cern.ch/record/2718278
- R. Aaij et al., “Evolution of the energy efficiency of LHCb’s real-time processing,” EPJ Web Conf., vol. 251, p. 04009, 2021. [Online]. Available: https://cds.cern.ch/record/2773126
- A. Hennequin et al., “SparseCCL: Connected Components Labeling and Analysis for sparse images,” in DASIP 2019 - The Conference on Design and Architectures for Signal and Image Processing, Montréal, Canada, 2019. [Online]. Available: https://hal.archives-ouvertes.fr/hal-02343598
- F. Spagnolo et al., “An Efficient Connected Component Labeling Architecture for Embedded Systems,” Journal of Low Power Electronics and Applications, vol. 8, no. 1, 2018. [Online]. Available: https://www.mdpi.com/2079-9268/8/1/7
- M. J. Klaiber et al., “A high-throughput FPGA architecture for parallel connected components analysis based on label reuse,” in 2013 International Conference on Field-Programmable Technology (FPT), Kyoto, Japan, 2013.