Presentation: Python, Numba, and Algorithm Design: Building Efficient Models in Financial Services
Chad Schuster discusses bridging Python's developer velocity with C-like performance using Numba JIT and GPUs. Drawing from large-scale actuarial modeling, he explains LLVM pipeline architecture, performance gains up to 750x, and essential trade-offs like OOP limits, type inference errors, and compile-time overhead for engineering leaders scaling compute-heavy enterprise systems. By Chad Schuster
We haven't written up this one. InfoQ has the full story — the link below goes straight to it.
