Title: Tracking performance in high multiplicities environment at ALICE,
Abstract: In LHC Run 3, ALICE will increase the data taking rate significantly to
50\,kHz continuous read out of minimum bias Pb-Pb events. This challenges the
online and offline computing infrastructure, requiring to process 50 times as
many events per second as in Run 2, and increasing the data compression ratio
from 5 to 20. Such high data compression is impossible by lossless ZIP-like
algorithms, but it must use results from online reconstruction, which in turn
requires online calibration. These important online processing steps are the
most computing-intense ones, and will use GPUs as hardware accelerators. The
new online features are already under test during Run 2 in the High Level
Trigger (HLT) online processing farm. The TPC (Time Projection Chamber)
tracking algorithm for Run 3 is derived from the current HLT online tracking
and is based on the Cellular Automaton and Kalman Filter. HLT has deployed
online calibration for the TPC drift time, which needs to be extended to space
charge distortions calibration. This requires online reconstruction for
additional detectors like TRD (Transition Radiation Detector) and TOF (Time Of
Flight). We present prototypes of these developments, in particular a data
compression algorithm that achieves a compression factor of~9 on Run 2 TPC
data, and the efficiency of online TRD tracking. We give an outlook to the
challenges of TPC tracking with continuous read out.