Parallel Chromatic MCMC with Spatial Partitioning

Jun Song; David A. Moore

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arXiv · 1612.00595

Parallel Chromatic MCMC with Spatial Partitioning

Jun Song·David A. Moore

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Abstract

We introduce a novel approach for parallelizing MCMC inference in models with spatially determined conditional independence relationships, for which existing techniques exploiting graphical model structure are not applicable. Our approach is motivated by a model of seismic events and signals, where events detected in distant regions are approximately independent given those in intermediate regions. We perform parallel inference by coloring a factor graph defined over regions of latent space, rather than individual model variables. Evaluating on a model of seismic event detection, we achieve significant speedups over serial MCMC with no degradation in inference quality.

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Jun Song, David A. Moore. 2016-12-02. Parallel Chromatic MCMC with Spatial Partitioning. https://arxiv.org/abs/1612.00595

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