Learn about transitioning from single-core Python to multi-GPU Julia implementations in this conference talk from JuliaCon 2024. Explore a real-world case study from Europe's Human Brain Project where domain scientists and HPC experts collaborated to transform a single-CPU-core Python prototype into a high-performance Julia application for Bayesian optimization of neurological network hyper-parameters. Discover how automatic correctness verification helped scientists without prior Julia experience gain confidence in the ported application. Examine the use of ParallelStencil.jl to unify prototyping and production in a single codebase that scales from a single CPU core to thousands of GPUs. Master techniques for implementing checkpoints to verify code blocks and automatically detect potential issues during refactoring or when handling new input classes.