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A fast and efficient SIMD track reconstruction algorithm for the LHCb Upgrade 1 VELO-PIX detector
The upgraded CERN LHCb detector, due to start data taking in 2021, will have to reconstruct 4 TB/s of raw detector data in real time using commodity processors. This is one of the biggest real-time data processing challenges in any scientific domain. We present an intrinsically parallel reconstructi...
Autores principales: | , , , , , |
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Lenguaje: | eng |
Publicado: |
2019
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1088/1748-0221/15/06/P06018 http://cds.cern.ch/record/2707185 |
_version_ | 1780964921607979008 |
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author | Hennequin, Arthur Couturier, Benjamin Gligorov, Vladimir Ponce, Sebastien Quagliani, Renato Lacassagne, Lionel |
author_facet | Hennequin, Arthur Couturier, Benjamin Gligorov, Vladimir Ponce, Sebastien Quagliani, Renato Lacassagne, Lionel |
author_sort | Hennequin, Arthur |
collection | CERN |
description | The upgraded CERN LHCb detector, due to start data taking in 2021, will have to reconstruct 4 TB/s of raw detector data in real time using commodity processors. This is one of the biggest real-time data processing challenges in any scientific domain. We present an intrinsically parallel reconstruction algorithm for the vertex detector of the LHCb experiment designed to optimally exploit multi-core general purpose architectures. We evaluate the algorithm on two high-end architectures from two different vendors and discuss in detail the impact of different SIMD Instruction Set Architecture extensions on the performance. We further compare the algorithm to current state-of-the-art scalar pattern recognition algorithms. We show a factor 2 speedup while achieving similar or better levels of physics performance. |
id | cern-2707185 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2019 |
record_format | invenio |
spelling | cern-27071852023-10-12T05:28:38Zdoi:10.1088/1748-0221/15/06/P06018http://cds.cern.ch/record/2707185engHennequin, ArthurCouturier, BenjaminGligorov, VladimirPonce, SebastienQuagliani, RenatoLacassagne, LionelA fast and efficient SIMD track reconstruction algorithm for the LHCb Upgrade 1 VELO-PIX detectorphysics.ins-detDetectors and Experimental TechniquesThe upgraded CERN LHCb detector, due to start data taking in 2021, will have to reconstruct 4 TB/s of raw detector data in real time using commodity processors. This is one of the biggest real-time data processing challenges in any scientific domain. We present an intrinsically parallel reconstruction algorithm for the vertex detector of the LHCb experiment designed to optimally exploit multi-core general purpose architectures. We evaluate the algorithm on two high-end architectures from two different vendors and discuss in detail the impact of different SIMD Instruction Set Architecture extensions on the performance. We further compare the algorithm to current state-of-the-art scalar pattern recognition algorithms. We show a factor 2 speedup while achieving similar or better levels of physics performance.The upgraded CERN LHCb detector, due to start data taking in 2021, will have to reconstruct 4 TB/s of raw detector data in real time using commodity processors. This is one of the biggest real-time data processing challenges in any scientific domain. We present an intrinsically parallel reconstruction algorithm for the vertex detector of the LHCb experiment designed to optimally exploit multi-core general purpose architectures. We compare it to previous state-of-the-art scalar pattern recognition algorithms and show significantly faster processing and in some cases increased physics performance over all current alternatives. We evaluate the algorithm on two high-end architectures from two different vendors and discuss in detail the impact of different SIMD Instruction Set Architecture extensions on the performance.arXiv:1912.09901oai:cds.cern.ch:27071852019-12-20 |
spellingShingle | physics.ins-det Detectors and Experimental Techniques Hennequin, Arthur Couturier, Benjamin Gligorov, Vladimir Ponce, Sebastien Quagliani, Renato Lacassagne, Lionel A fast and efficient SIMD track reconstruction algorithm for the LHCb Upgrade 1 VELO-PIX detector |
title | A fast and efficient SIMD track reconstruction algorithm for the LHCb Upgrade 1 VELO-PIX detector |
title_full | A fast and efficient SIMD track reconstruction algorithm for the LHCb Upgrade 1 VELO-PIX detector |
title_fullStr | A fast and efficient SIMD track reconstruction algorithm for the LHCb Upgrade 1 VELO-PIX detector |
title_full_unstemmed | A fast and efficient SIMD track reconstruction algorithm for the LHCb Upgrade 1 VELO-PIX detector |
title_short | A fast and efficient SIMD track reconstruction algorithm for the LHCb Upgrade 1 VELO-PIX detector |
title_sort | fast and efficient simd track reconstruction algorithm for the lhcb upgrade 1 velo-pix detector |
topic | physics.ins-det Detectors and Experimental Techniques |
url | https://dx.doi.org/10.1088/1748-0221/15/06/P06018 http://cds.cern.ch/record/2707185 |
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