Parallel Exact Inference.
Yinglong Xia, Viktor K. Prasanna · 2007
In this paper, we present complete message-passing implementation that shows scalable performance while performing exact inference on arbitrary Bayesian networks. Our work is based on a parallel version of the classical technique of converting a Bayesian network to a junction tree before computing inference. We propose a parallel algorithm for constructing potential tables for a junction tree and explore the parallelism of rerooting technique for multiple evidence propagation. Our implementation also uses pointer jumping for parallel inference over the junction tree. For an arbitrary Bayesian network with n vertices using p processors, we show an