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

JOURNAL OF INSTRUMENTATION(2020)

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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.
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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)
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