Published February 8, 2022 | Version 0.2.0
Software Open

Artifact: Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference

Authors/Creators

  • 1. KTH Royal Institute of Technology
  • 2. AI Sweden
  • 3. BI Norwegian Business School
  • 4. Swedish Museum of Natural History

Description

Artifact accompanying the paper Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference (https://doi.org/10.1007/978-3-030-99336-8_2) published at the European Symposium on Programming (ESOP) 2022.

The file README.txt contains instructions on how to work with the artifact in Docker. The file 86.zip contains the artifact itself (ppl-smc-gpu.tar.gz) and source code for building the artifact (under docker/).

Files

86.zip

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