  We develop a simple algorithm to parallelize generation processes of Markov
chains. In this algorithm, multiple Markov chains are generated in parallel and
jointed together to make a longer Markov chain. The joints between the
constituent Markov chains are processed using the detailed balance. We apply
the parallelization algorithm to multicanonical calculations of the
two-dimensional Ising model and demonstrate accurate estimation of
multicanonical weights.
