Back to Search Start Over

Pigeons.jl: Distributed Sampling From Intractable Distributions

Authors :
Surjanovic, Nikola
Biron-Lattes, Miguel
Tiede, Paul
Syed, Saifuddin
Campbell, Trevor
Bouchard-Côté, Alexandre
Publication Year :
2023

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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2308.09769
Document Type :
Working Paper