Pigeons.jl: Distributed Sampling From Intractable Distributions
Abstract
We introduce a software package, Pigeons.jl, that provides a way to leverage distributed computation to obtain samples from complicated probability distributions, such as multimodal posteriors arising in Bayesian inference and high-dimensional distributions in statistical mechanics. Pigeons.jl provides simple APIs to perform such computations single-threaded, multi-threaded, and/or distributed over thousands of MPI-communicating machines. In addition, Pigeons.jl guarantees a property that we call strong parallelism invariance: the output for a given seed is identical irrespective of the number of threads and processes, which is crucial for scientific reproducibility and software validation. We describe the key features of Pigeons.jl and the approach taken to implement a distributed and randomized algorithm that satisfies strong parallelism invariance.
Cite
@article{arxiv.2308.09769,
title = {Pigeons.jl: Distributed Sampling From Intractable Distributions},
author = {Nikola Surjanovic and Miguel Biron-Lattes and Paul Tiede and Saifuddin Syed and Trevor Campbell and Alexandre Bouchard-Côté},
journal= {arXiv preprint arXiv:2308.09769},
year = {2023}
}