Partial Evaluation in Junction Trees

Aug 31, 2022ยท
Martin Roa-Villescas
Martin Roa-Villescas
,
Patrick Wijnings
,
Sander Stuijk
,
Henk Corporaal
ยท 0 min read
Abstract
One prominent method to perform inference on probabilistic graphical models is the probability propagation in trees of clusters (PPTC) algorithm. In this paper, we demonstrate the use of partial evaluation, an established technique from the compiler domain, to improve the performance of online Bayesian inference using the PPTC algorithm in the context of observed evidence. We present a metaprogramming-based method to transform a base program into an optimized version by precomputing the static input at compile time while guaranteeing behavioral equivalence. We achieve an inference time reduction of 21% on average for the Promedas benchmark.
Type
Publication
In 2022 25th Euromicro Conference on Digital System Design (DSD)