we recently got approval for our 250m CPU-hour GCS supercomputing project named “Bayesian Inference of the Reactive Shock-Bubble Interaction - Probabilistic Programming at Scale”.
A rough sketch:
The Bayesian inference is performed using an adapted version of @Marco_Cusumano-Towne 's GEN with custom inference algorithms, which are coupled with JAX for amortization and are then routed through a probabilistic programming execution protocol to control the reacting-flow simulations.
For this we are using HLRS’s new HAWK supercomputer made up of ~10k AMD EPYC 7742s with multiple GPU cluster working concurrently to run the machine learning stack and support the probabilistic programs.
Together with HLRS we hope to pave the way for large-scale HPC deployments of Julia in the German supercomputing community, which will also be accessible to all other European researchers through PRACE.
Oh, and really push the limits of probabilistic programming and distributed computing in Julia of course :))