  This paper discusses a parallelized event reconstruction of the COMET Phase-I
experiment. The experiment aims to discover charged lepton flavor violation by
observing 104.97 MeV electrons from neutrinoless muon-to-electron conversion in
muonic atoms. The event reconstruction of electrons with multiple helix turns
is a challenging problem because hit-to-turn classification requires a high
computation cost. The introduced algorithm finds an optimal seed of position
and momentum for each turn partition by investigating the residual sum of
squares based on distance-of-closest-approach (DCA) between hits and a track
extrapolated from the seed. Hits with DCA less than a cutoff value are
classified for the turn represented by the seed. The classification performance
was optimized by tuning the cutoff value and refining the set of classified
hits. The workload was parallelized over the seeds and the hits by defining two
GPU kernels, which record track parameters extrapolated from the seeds and
finds the DCAs of hits, respectively. A reasonable efficiency and momentum
resolution was obtained for a wide momentum region which covers both signal and
background electrons. The event reconstruction results from the CPU and GPU
were identical to each other. The benchmarked GPUs had an order of magnitude of
speedup over a CPU with 16 cores while the exact speed gains varied depending
on their architectures.
