  The standard kinetic Monte Carlo algorithm is an extremely efficient method
to carry out serial simulations of dynamical processes such as thin-film
growth. However, in some cases it is necessary to study systems over extended
time and length scales, and therefore a parallel algorithm is desired. Here we
describe an efficient, semi-rigorous synchronous sublattice algorithm for
parallel kinetic Monte Carlo simulations. The accuracy and parallel efficiency
are studied as a function of diffusion rate, processor size, and number of
processors for a variety of simple models of epitaxial growth. The effects of
fluctuations on the parallel efficiency are also studied. Since only local
communications are required, linear scaling behavior is observed, e.g. the
parallel efficiency is independent of the number of processors for fixed
processor size.
