  ALICE (A Large Heavy Ion Experiment) is one of the four major experiments at
the Large Hadron Collider (LHC) at CERN. The High Level Trigger (HLT) is an
online compute farm which reconstructs events measured by the ALICE detector in
real-time. The most compute-intensive part is the reconstruction of particle
trajectories called tracking and the most important detector for tracking is
the Time Projection Chamber (TPC). The HLT uses a GPU-accelerated algorithm for
TPC tracking that is based on the Cellular Automaton principle and on the
Kalman filter. The GPU tracking has been running in 24/7 operation since 2012
in LHC Run 1 and 2. In order to better leverage the potential of the GPUs, and
speed up the overall HLT reconstruction, we plan to bring more reconstruction
steps (e.g. the tracking for other detectors) onto the GPUs. There are several
tasks running so far on the CPU that could benefit from cooperation with the
tracking, which is hardly feasible at the moment due to the delay of the PCI
Express transfers. Moving more steps onto the GPU, and processing them on the
GPU at once, will reduce PCI Express transfers and free up CPU resources. On
top of that, modern GPUs and GPU programming APIs provide new features which
are not yet exploited by the TPC tracking. We present our new developments for
GPU reconstruction, both with a focus on the online reconstruction on GPU for
the online offline computing upgrade in ALICE during LHC Run 3, and also taking
into account how the current HLT in Run 2 can profit from these improvements.
