We present the first results of the prototype of a silicon tracker with trigger capabilities based on a novel approach for fast track finding. The working principle of the "artificial retina" is inspired by the processing of visual images by the brain and it is based on extensive parallelisation of data distribution and pattern recognition. The algorithm has been implemented in commercial FPGAs in three main logic modules: a switch for the routing of the detector hits, a pool of engines for the digital processing of the hits, and a block for the calculation of the track parameters. The architecture is fully pipelined and allows the reconstruction of real-time tracks with a latency less then 100 clock cycles, corresponding to 0.25 microsecond at 400 MHz clock. The silicon telescope consists of 8 layers of single-sided silicon strip detectors with 512 strips each. The detector size is about 10 cm × 10 cm and the strip pitch is 183 μm. The detectors are read out by the Beetle chip, a custom ASICs developed for LHCb, which provides the measurement of the hit position and pulse height of 128 channels. The "artificial retina" algorithm has been implemented on custom data acquisition boards based on FPGAs Xilinx Kintex 7 lx 160. The parameters of the tracks detected are finally transferred to host PC via USB 3.0. The boards manage the read-out ASICs and the sampling of the analog channels. The read-out is performed at 40 MHz on 4 channels for each ASIC that corresponds to a decoding of the telescope information at 1.1 MHz. We report on the first results of the fast tracking device and compare with simulations.

First results of the silicon telescope using an 'artificial retina' for fast track finding

Cenci R.;Marino P.;Morello M. J.;Stracka S.;
2015

Abstract

We present the first results of the prototype of a silicon tracker with trigger capabilities based on a novel approach for fast track finding. The working principle of the "artificial retina" is inspired by the processing of visual images by the brain and it is based on extensive parallelisation of data distribution and pattern recognition. The algorithm has been implemented in commercial FPGAs in three main logic modules: a switch for the routing of the detector hits, a pool of engines for the digital processing of the hits, and a block for the calculation of the track parameters. The architecture is fully pipelined and allows the reconstruction of real-time tracks with a latency less then 100 clock cycles, corresponding to 0.25 microsecond at 400 MHz clock. The silicon telescope consists of 8 layers of single-sided silicon strip detectors with 512 strips each. The detector size is about 10 cm × 10 cm and the strip pitch is 183 μm. The detectors are read out by the Beetle chip, a custom ASICs developed for LHCb, which provides the measurement of the hit position and pulse height of 128 channels. The "artificial retina" algorithm has been implemented on custom data acquisition boards based on FPGAs Xilinx Kintex 7 lx 160. The parameters of the tracks detected are finally transferred to host PC via USB 3.0. The boards manage the read-out ASICs and the sampling of the analog channels. The read-out is performed at 40 MHz on 4 channels for each ASIC that corresponds to a decoding of the telescope information at 1.1 MHz. We report on the first results of the fast tracking device and compare with simulations.
2015
Settore FIS/01 - Fisica Sperimentale
4th International Conference on Advancements in Nuclear Instrumentation Measurement Methods and their Applications (ANIMMA 2015)
Lisbona
20-24 April 2015
4th International Conference on Advancements in Nuclear Instrumentation Measurement Methods and their Applications (ANIMMA 2015)
Institute of Electrical and Electronics Engineers (IEEE)
9781479999194
Real time particle tracking. FPGA. Artificial retina algorithm. Silicon telescope
File in questo prodotto:
File Dimensione Formato  
First_results_of_the_silicon_telescope_using_an_artificial_retina_for_fast_track_finding.pdf

Accesso chiuso

Tipologia: Published version
Licenza: Non pubblico
Dimensione 795.73 kB
Formato Adobe PDF
795.73 kB Adobe PDF   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11384/141924
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact