Evacuation Simulation as the Fitness Function: GPU Generative Design with NVIDIA Warp
GD–AI Loop 2.0 · Lab Notes #6 In the previous post our GPU generative-design pipeline scored evacuation with a travel-distance formula. This time the genetic algorithm's fitness function runs a crowd evacuation simulation — dozens of people queuing and slowing down in the exit stairs — as an NVIDIA Warp kernel on the GPU. The buildings it picks changed. Then we varied the site shape 320 ways and tested again whether machine learning can propose designs for unseen sites. Oct 25, 2026 (updated Nov 1–2; English edition and CPU vs GPU benchmark Nov 6) · Previous: Lab Notes #5, "80 million buildings in 42 minutes" Update, Nov 6, 2026 — the crowd model in this post has been replaced. The experiments below used the v1 crowd model: one person per 1.5 m cell (so at most 0.44 persons/m²), one-cell doors, single-file stairs, 42–62 people per building and no validation. Lab Notes #8 (rewritten) replaces it with a continuous agent model (the collision-free speed model used by JuP...