PANDA is a future hadron and nuclear physics experiment at the FAIR facility in construction in Darmstadt, Germany. Unlike the majority of current experiments, PANDA's strategy for data acquisition is based on online event reconstruction from free-streaming data, performed in real time entirely by software algorithms using global detector information. This paper reports on the status of the development of algorithms for the reconstruction of charged particle tracks, targeted towards online data processing applications, designed for execution on data-parallel processors such as GPUs (Graphic Processing Units). Two parallel algorithms for track finding, derived from the Circle Hough algorithm, are being developed to extend the parallelism to all stages of the algorithm. The concepts of the algorithms are described, along with preliminary results and considerations about their implementations and performance.

\panda is a planned experiment at FAIR (Darmstadt) with a cooled antiproton beam in a range [1.5; 15] GeV/$c$, allowing a wide physics program in nuclear and particle physics. It is the only experiment worldwide, which combines a solenoid field (B=2T) and a dipole field (B=2Tm) in a spectrometer with a fixed target topology, in that energy regime. The tracking system of \panda involves the presence of a high performance silicon vertex detector, a GEM detector, a Straw- Tubes central tracker, a forward tracking system, and a luminosity monitor. The offline tracking algorithm is developed within the PandaRoot framework, which is a part of the FairRoot project. The tool here presented is based on algorithms containing the Kalman Filter equations and a deterministic annealing filter. This general fitting tool (GENFIT2) offers to users also a Runge-Kutta track representation, and interfaces with Millepede II (useful for alignment) and RAVE (vertex finder). It is independent on the detector geometry and the B field map, and written in C++ o.o. modular code. Several fitting algorithms are available with GENFIT2, with user-adjustable parameters; therefore the tool is of friendly usage. A check on the fit convergence is done by GENFIT2 as well. The Kalman-Filter-based algorithms have a wide range of applications; among those in particle physics they can perform extrapolations of track parameters and covariance matrices. The impact of GENFIT2 on physics simulations performed for the \panda experiment is shown, with the PandaRoot framework: significant improvement is reported for those channels where a good low momentum tracking is required ($\rm{p_T} <$ 400 MeV/$c$

The non-perturbative nature of the strong interaction leads to spectacular phenomena, such as the formation of hadronic matter, color confinement, and the generation of the mass of visible matter. To get deeper insight into the underlying mechanisms remains one of the most challenging tasks within the field of subatomic physics. The antiProton ANnihilations at DArmstadt (${\bar{\rm P}}$ANDA) collaboration has the ambition to address key questions in this field by exploiting a cooled beam of antiprotons at the High-Energy Storage Ring (HESR) at the future Facility for Antiproton and Ion Research (FAIR) combined with a state-of-the-art and versatile detector. In this contribution, I will address some of the unique features of ${\bar{\rm P}}$ANDA that give rise to a promising physics program together with state-of-the-art technological developments.