  The ALICE experiment will run with continuous readout at interaction rates of
up to 50 kHz in Pb-Pb collisions during Run 3 of the LHC. In order to achieve
this goal, a new data processing scheme and software are developed. This scheme
strongly relies on GPUs (Graphics Processing Unit) for fast online and offline
calibration and reconstruction as well as on efficient data compression. On the
hardware side, the Time Projection Chamber (TPC), among other detector systems,
received major upgrades to its readout chambers and readout electronics. The
multiwire proportional chambers were replaced by stacks of four Gas Electron
Multiplier foils to allow for continuous readout while keeping the ion backflow
below 1%, minimizing space-charge effects from amplification ions entering the
drift volume. Nevertheless, significant space-point distortions due to space
charge are expected at the highest interaction rates in Pb-Pb collisions. In
addition, space-charge density fluctuations lead to distortion fluctuations
which have to be corrected on time scales of 10 ms in order to preserve the
intrinsic tracking resolution of the TPC. While the average space-charge
distortions can be corrected using information from external detectors as a
reference, data-driven machine learning algorithms and convolutional neural
networks are foreseen to provide the correction for the distortion
fluctuations.
