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.
Institutions
- University of Cambridge (GB)
- Canisius College (US)
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