Parallel Markov Chain Monte Carlo Simulation by
In recent years, parallel processing has become widely available to
researchers. It can be applied in an obvious way in the context
of Monte Carlo simulation, but techniques for ``parallelizing'' Markov
Monte Carlo (MCMC) algorithms are not so obvious, apart from
the natural approach of generating multiple
chains in parallel. While generation of parallel chains is generally
the easiest approach,
in cases where burn-in is a serious problem, it is often desirable
to use parallelization to speed up generation of a single chain.
This paper briefly discusses some
existing methods for parallelization of MCMC algorithms,
and proposes a new ``pre-fetching'' algorithm to parallelize
generation of a single chain.
Keywords: parallel processing, Markov chain Monte Carlo,
Bayesian, inference, pre-fetching