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arXiv:1212.2991cs.SE

Accelerating Inference: towards a full Language, Compiler and Hardware stack

Shawn Hershey, Jeff Bernstein, Bill Bradley, Andrew Schweitzer, Noah Stein, Theo Weber, Ben Vigoda

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Abstract

We introduce Dimple, a fully open-source API for probabilistic modeling. Dimple allows the user to specify probabilistic models in the form of graphical models, Bayesian networks, or factor graphs, and performs inference (by automatically deriving an inference engine from a variety of algorithms) on the model. Dimple also serves as a compiler for GP5, a hardware accelerator for inference.

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DOI
Subjects
cs.SESoftware Engineering cs.AIArtificial Intelligence stat.MLMachine Learning (Statistics)

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  1. Why Probabilistic Programming Matters 1 comment

    • I think the most exciting opportunity here is actually compiling models to run in specialized inference hardware! Lyric semiconductor a.k.a. Lyric Labs of Analog Devices is working towards such goals (http://dimple.probprog.org/, http://arxiv.org/abs/1212.2991). I hope that they…

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