A fast and efficient SIMD track reconstruction algorithm for the LHCb upgrade 1 VELO-PIX detector

被引:3
作者
Hennequin, A. [1 ,2 ]
Couturier, B. [1 ]
Gligorov, V. V. [3 ]
Ponce, S. [1 ]
Quagliani, R. [3 ]
Lacassagne, L. [2 ]
机构
[1] CERN, LHCb Expt, Geneva, Switzerland
[2] Sorbonne Univ, CNRS, LIP6, Paris, France
[3] Sorbonne Univ, Paris Diderot Sorbonne Paris Cite, LPNHE, CNRS,IN2P3, Paris, France
来源
JOURNAL OF INSTRUMENTATION | 2020年 / 15卷 / 06期
关键词
Data processing methods; Data reduction methods; Pattern recognition; cluster finding; calibration and fitting methods; Computing; (architecture; farms; GRID for recording storage; archiving; and distribution of data);
D O I
10.1088/1748-0221/15/06/P06018
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
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.
引用
收藏
页数:22
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