  We combine parallelization and cluster Monte Carlo for hard sphere systems
and present a parallelized event chain algorithm for the hard disk system in
two dimensions. For parallelization we use a spatial partitioning approach into
simulation cells. We find that it is crucial for correctness to ensure detailed
balance on the level of Monte Carlo sweeps by drawing the starting sphere of
event chains within each simulation cell with replacement. We analyze the
performance gains for the parallelized event chain and find a criterion for an
optimal degree of parallelization. Because of the cluster nature of event chain
moves massive parallelization will not be optimal. Finally, we discuss first
applications of the event chain algorithm to dense polymer systems, i.e.,
bundle-forming solutions of attractive semiflexible polymers.
