GPU Accelerated Nested Sampling

Nested Sampling is a powerful Monte Carlo method for Bayesian inference, but is often viewed as a legacy, CPU-bound algorithm. We reformulate Nested Sampling for modern GPU hardware, leveraging vectorization and a slice sampling-based inner kernel. Our implementation in the blackjax framework achieves state-of-the-art performance, enabling rapid and robust parameter estimation and model comparison for challenging problems in gravitational wave astronomy and cosmology.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-07-11
DOI
https://doi.org/10.5281/zenodo.15863506
Primary Topic
Gaussian Processes and Bayesian Inference
Type
article
Field-Weighted Citation Impact
0.00
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article

GPU Accelerated Nested Sampling

Zenodo (CERN European Organization for Nuclear Research)
Gaussian Processes and Bayesian Inference
article

GPU Accelerated Nested Sampling

article en

Abstract

Nested Sampling is a powerful Monte Carlo method for Bayesian inference, but is often viewed as a legacy, CPU-bound algorithm. We reformulate Nested Sampling for modern GPU hardware, leveraging vectorization and a slice sampling-based inner kernel. Our implementation in the blackjax framework achieves state-of-the-art performance, enabling rapid and robust parameter estimation and model comparison for challenging problems in gravitational wave astronomy and cosmology.

Zenodo (CERN European Organization for Nuclear Research)
University of Cambridge (GB), Canisius College (US)
Openalex Percentile: Top 74%
Gaussian Processes and Bayesian Inference
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GPU Accelerated Nested Sampling · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS