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Fast Parallel Exact Inference on Bayesian Networks: Poster

2022-12-08Code Available0· sign in to hype

Jiantong Jiang, Zeyi Wen, Atif Mansoor, Ajmal Mian

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Abstract

Bayesian networks (BNs) are attractive, because they are graphical and interpretable machine learning models. However, exact inference on BNs is time-consuming, especially for complex problems. To improve the efficiency, we propose a fast BN exact inference solution named Fast-BNI on multi-core CPUs. Fast-BNI enhances the efficiency of exact inference through hybrid parallelism that tightly integrates coarse- and fine-grained parallelism. We also propose techniques to further simplify the bottleneck operations of BN exact inference. Fast-BNI source code is freely available at https://github.com/jjiantong/FastBN.

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